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In March 2025, 37signals published a letter [1], as part of their hiring effort, where they connect writing with design. They want a product designer, yes. But they also want a writer. What they gave us, connected with writing, solves what they want: 37signals We're looking for a designer, not a decorator. A product builder, not a picture maker. A shipper, not a prototyper. We're looking for a designer, not a decorator. A product builder, not a picture maker. A shipper, not a prototyper. When reading that letter [1], I was able to see the role of a designer through the writer’s lenses, to see how writing is at the center of it. I connected with that because I share the values presented in the letter. The moment of listening became a reflective moment. And it took me to write, to engage with a reflective exercise. That reflective exercise turned out to be a cover letter, the following cover letter. Thanks to 37signals for giving us that letter. The Cover Letter The Cover Letter That idea of a “shipper, not a prototyper” freaks me out, I confess. It always did. But today, differently, I fear that prototyper role. This is so because we miss a point, right there, about what is in between: writing writing To explain, and to let you know who I am, let me start with the situation that UX, UI, front-end development, and copywriter should be seen as one role. I agree, designers are generalists. But right there it starts the complication, right? To even think about that is wrong, right? This, a perceived complication, sets us to face the real complication that takes us away from that truth - that writing is in between - and on the way of the shippers. Here is what I have told Mr. Jason, about the days when I was the “Fastest Keyboard in the West,” that non-writer one: Mr. Jason Fastest Keyboard in the West, Jason, I tried to, too many times, to do that “right” thing, to do it by being that fast prototyper. So I did it. My brother, around 2000 and during the DHTML days, said that I was the “King of the Little Menus.” Jason, Netscape took me, from Brazil and to the USA, with that 20+ pages “H1-B” justification [here was a hint for me] for taking the job of an American. And then, Jason, I arrived at Netscape. And someone important at some point said “Marcio, whatever you are smoking, please keep doing that.” WYASPKDT. I received claps, for prototyping and that is that, and for inspiring them. Professionally, indeed. Even Brendan Eich once wondered “Can we do that with JavaScript?” Jason, I tried to, too many times, to do that “right” thing, to do it by being that fast prototyper. So I did it. My brother, around 2000 and during the DHTML days, said that I was the “King of the Little Menus.” Jason, Netscape took me, from Brazil and to the USA, with that 20+ pages “H1-B” justification [here was a hint for me] for taking the job of an American. And then, Jason, I arrived at Netscape. And someone important at some point said “Marcio, whatever you are smoking, please keep doing that.” WYASPKDT. I received claps, for prototyping and that is that, and for inspiring them. Professionally, indeed. Even Brendan Eich once wondered “Can we do that with JavaScript?” Kings to me, a king of prototypes, or perhaps a non-writer fast typer. But like a king, I had to pay the price. The price, from being okay with WYASPKDT, went along with that anxious corporate agenda which, again and again, does take advantage of the fresh new employee, the next in line. WYASPKDT, we say. The prize as a price to pay is us taking ourselves away from seeing things. No one had even the time to ask “Hey man, were you smoking?” Having started there, it took me 25 years between that said specialist and the truth, the hard way, indeed. Running the risk of entering that 800+ page novel, the problem-solution could be introduced with what Steve Job had said, that we can’t see the dots while doing it. But back to what matters and at the core of this journey too, the real problem has to do with how we see ourselves - or how we do not see ourselves - when we are running, there, into that jungle of trees, of code, demos, prototypes, meetings, activities, and everything else: If we had the time, to look, perhaps we would see the flip side of “what you see is what we get” and “what we don’t see is what we don’t get.” If we could see, then we would ask “Man, if you are not talking about it, you will miss it!” And then, see that you and I need to write about the things that we want to ship. Now, I wonder, have I avoided writing? (Have I avoided engaging with that reflective writing for myself and for colleagues?) It may be so because I was too busy with claps. Or I was trapped by the idea that WYASPKDT meant “no need to engage with reflective writing,” and the other writings from there. Having paid the price, I started to value writing. Not as a tool to make things beautiful. But as a way to see beyond those black boxes - beyond the prototype - and to transcend. As the thing that takes us to connect the dots. Now, am I good at doing that? Of course, this is not the point. It matters more that it is life-changing - writers know it. Having paid the price, I started to value writing. Not as a tool to make things beautiful. But as a way to see beyond those black boxes - beyond the prototype - and to transcend. As the thing that takes us to connect the dots. Now, am I good at doing that? Of course, this is not the point. It matters more that it is life-changing - writers know it. To address the point of “Why do you love the web?” I say, “Yes I love it” as it is the big canvas we made for ourselves. But I also hate it, depending on how we do the things we do: Hot links? I fear them as they get cold and are lost in the dark too soon Hot links? I fear them as they get cold and are lost in the dark too soon Hot links? I fear them as they get cold and are lost in the dark too soon In other words, that comfortable specialist-prototypist as a goal is a path to a dead end, to miss talking about things, with that to miss evolving things and to miss the shipping thing. What you see, what we see, is what you and I write about, and is on the way of what we will get and of what becomes real. In other words, it is through writing, or through exposing it, that we open ourselves, to collaborate. Regarding other’s work, I appreciate the work of Andy Grove (High Output Management and Only the Paranoid Survive). Andy teaches us about design too. In terms of slowing down, the Blizscaling lectures were helpful for me. In terms of founder and self-management, Michael Dearing helped me rewrite part of my OS. In terms of writing vs. self, I am thankful to Julia Cameron’s The Artist’s Way, which also took me to other life-changing paths. Blizscaling Blizscaling These are some pointers that make me think that I write therefore I am. As a plus, and going back to the other things that matter too, when I write, I see that outcomes - such as UX/UI - get better. In other words, I feel closer to design, to the design work that ships. With that, to close, I hope to find a team, and minds, who support me to grow as a person and to grow as a colleague who supports our growth. [1] “Web App Product Designer” Job Specification by 37signals I say thanks to the following writing. The following is a masterpiece. And I know it is the truth, that it tells us about how 37signals do things. The following, for me, was also a great starting point for a moment of reflection about the role of a designer. More than that, the following document is an opportunity for all of us, as a reflective writing exercise. The following document helps us to pause, to listen, to consider, to reflect, to engage, to cross-check an examination, to learn, to assess, and it serves for us to buy in. I buy. “37signals is hiring a Web App Product Designer. We don't hire for this position often, so this is a rare opportunity. We're looking for a designer, not a decorator. A product builder, not a picture maker. A shipper, not a prototyper. There's plenty of the latter, but we're after the former. We've built a close-knit team of five wonderful designers, and we'd be thrilled to have you as our sixth. Depending on your skills and experience, you'll either come in at the Senior or Lead level. Senior pays $193,858, Lead pays $229,064. Additional perks, benefits, profit sharing, and more are detailed in the handbook. “37signals is hiring a Web App Product Designer. We don't hire for this position often, so this is a rare opportunity. We're looking for a designer, not a decorator. A product builder, not a picture maker. A shipper, not a prototyper. There's plenty of the latter, but we're after the former. We've built a close-knit team of five wonderful designers, and we'd be thrilled to have you as our sixth. Depending on your skills and experience, you'll either come in at the Senior or Lead level. Senior pays $193,858, Lead pays $229,064. Additional perks, benefits, profit sharing, and more are detailed in the handbook. 37signals 37signals in the handbook in the handbook About the Job About the Job About the Job At many companies, product design is split into different roles: UX, UI, front-end development, copywriter, etc. At 37signals, it’s all one role. This means our designers are exceptional generalists. Along with having great visual taste and sensibilities, you must be able to write your own production-quality front-end HTML, CSS, and English. You'll pair up with a back-end programmer to bring designs, features, and products to life. At many companies, product design is split into different roles: UX, UI, front-end development, copywriter, etc. At 37signals, it’s all one role. This means our designers are exceptional generalists. Along with having great visual taste and sensibilities, you must be able to write your own production-quality front-end HTML, CSS, and English. You'll pair up with a back-end programmer to bring designs, features, and products to life. We believe the best designs come from someone who can see it all through, from ideas to visuals to the finished product. We work from the interface first — starting with design, rather than ending with it — so you'll be involved in the work right from the beginning. Our projects are design-led, so you’ll have a lot of flexibility, freedom, influence, and impact right away. We follow the 6-week cycle Shape Up process, invented here. We believe the best designs come from someone who can see it all through, from ideas to visuals to the finished product. We work from the interface first — starting with design, rather than ending with it — so you'll be involved in the work right from the beginning. Our projects are design-led, so you’ll have a lot of flexibility, freedom, influence, and impact right away. We follow the 6-week cycle Shape Up process, invented here. Shape Up Shape Up You'll get to work on heavily-used products like Basecamp and HEY that push the industry forward. You won't be sequestered on a team that only gets to work on a slice of something — you'll work on all of everything. Working at 37signals as a designer means working on whole products. Existing products, brand new unreleased ones, and internal tools, too. You'll get to work on heavily-used products like Basecamp and HEY that push the industry forward. You won't be sequestered on a team that only gets to work on a slice of something — you'll work on all of everything. Working at 37signals as a designer means working on whole products. Existing products, brand new unreleased ones, and internal tools, too. As a manager of one, you’ll drive shaped projects, big and small, over six-week cycles. You’ll set direction, take ownership, make calls, and ultimately, once situated and comfortable, see things through without a lot of oversight. As a manager of one, you’ll drive shaped projects, big and small, over six-week cycles. You’ll set direction, take ownership, make calls, and ultimately, once situated and comfortable, see things through without a lot of oversight. You love writing, too. You understand that copywriting is design. The words matter as much as the pixels. No matter how great the visuals are, bad writing is bad design. You should care about how things are phrased as much as you care about how they look. “ You love writing, too. You understand that copywriting is design. The words matter as much as the pixels. No matter how great the visuals are, bad writing is bad design. You should care about how things are phrased as much as you care about how they look. “ [2]A Note About HackerNoon What you see, the above reflection tells you a bit about the life of one who went through a struggle. And about the one who had found, through writing, an enlighted path. This is also an opportunity to say thanks to HackerNoon, and to this community. To you, for being a platform that supported my development toward becoming a writer. And for doing that for many of us. We are all writers, we are all better learners through writing. We are all designers.

A Shipper, Not a Prototyper - A Reflective Writing and a Cover Letter

HackerNoon editorial team has launched this interview series with women in tech to celebrate their achievements and share their struggles. We need more women in technology, and by sharing stories, we can encourage many girls to follow their dreams. Share your story today! Tell us about yourself! Hi! I'm Lutsia, and I work in HR in IT. I've been doing this for over 12 years now, and I've worked with some amazing companies like gamedev, dating, music-tech, and social. Now, I'm the HR director of an international company that's doing well developing cool mobile apps for social media. My job is all about making sure the company has a great HR strategy, taking care of all the employees, and helping the business grow by developing its people. My company's products are doing well (currently, only Tinder has more installs than us) and we're seeing over 6 million installs every month. I am an active mentor in various communities such as Women in Tech, Miranna.io, ADP.list, I have done more than 100 consultations and helped more than 100 people to achieve their goals in IT. Why did you choose this field in the first place? I've always loved studying people and watching talent grow, so it's a perfect fit for me. In HR, it's all about communication, and in the tech industry, it's a bit of a challenge because there are so many introverts who need individual attention. I've got a Master's in Human Resources Management, and I absolutely love what I do. What tech are you most worried about right now and why? I'm really interested in technologies that can predict how long employees will stay with a company (like prediction models for employee tenure) and assessing soft skills. Human psychology is such a complex system, isn't it? I find the standard approaches don't always work, which makes it a constant challenge in the world of people management to assess team effectiveness. What are your hobbies and interests outside of tech? When I'm not doing that, I love nothing more than spending time with my family and friends, or enjoying a good book. I'm a music lover – playing the keyboard and singing are two of my favourite pastimes. I'm also a keen outdoorsy person, and I love nothing more than a good hike! A couple of years ago, I discovered the wonderful world of mentoring, which is a really cool side activity that energises me by interacting with talented people and being useful. Let's talk about breaking the glass ceiling. What were the biggest challenges you faced as a woman in tech, and how did you deal with them? I started my career in the tech industry, in startups and scale-ups, so I had direct contact with founders and was lucky to avoid unpleasant situations with the glass ceiling. But I would like to see more girls among CEOs and founders of companies. I plan to launch my own project one day. Any questionable misogynistic story/situation you faced/handled, and you want to share with the HackerNoon Fam? When I was just starting out in my career, over 12 years ago now, I was working in talent acquisition. I remember how hiring managers would sometimes reject female candidates for developer positions just because they were girls, or because they thought programming was just not a job for women. I remember my first driving instructor always telling me that driving was not for women, but I don't encounter this now. As a HR leader, I try to nip such stories in the bud. What was the biggest setback/failure that you faced, and how did you manage it? My biggest failure was my personal and professional burnout in 2019. I was deeply immersed in the topic and clearly knew the markers of this condition, but unfortunately, I was not able to prevent it in time. However, I learnt my lesson, and I am now much more attentive to my energy levels and have improved my delegating skills even more! What's your biggest achievement that you're really proud of? I have reached a high position just in 7 years - HR director in a fast-growing global technology company, every day I do what I love and develop not only the team, overseeing the unlocking of immense human potential, but also being involved in creating products that make a difference in this world and make life better for millions of people. I have extensive mentoring experience and have helped hundreds of people find their successful path to self-realisation in the industry. I am surrounded by amazingly smart and caring people who create beautiful things. In your opinion, why do we see this huge gender gap in the tech industry, and how can we reduce it? The tech industry is still pretty new, so I think there are some historical and cultural things going on that are holding it back. But I do see a lot of tech companies trying to make things better, which is great. They're putting in place these DEI policies, which is really important. I'm part of a group that supports women in IT, and I think it's a vital mission. I would love to see more support, grants, quotas and investments for start-ups created by women.It would be great to change the media narrative and promote the idea that technology is a universal field where gender doesn't matter. We should be creating content that's focused on engaging women and breaking stereotypes. From a company perspective and as a C-Level, it's important to implement training to overcome unconscious bias. Who is your tech idol? Why? I really look up to Sheryl Sandberg, ex-COO of Meta and author of Lean In: Women, Work, and the Will to Lead. She started the global Lean In movement, which connects women through professional networks, support circles, and educational programs. This movement helps women in IT find like-minded people, develop skills and build careers. I really admire how she's so open about the personal struggles she's had, including the loss of her husband. It's so inspiring to see how she's managed to be so successful and still remain human and vulnerable. Do you have any advice for aspiring girls who want to join the field? My advice for girls starting out in HR Tech is to be tenacious in achieving results, and you'll be glad to hear that there are so many opportunities for training and projects now, including through tech communities where you can find first projects and get hands-on experience.It's also great to find a mentor who has already travelled this path and will help you overcome any obstacles and move faster in your professional development. Be open, ask for advice and share your experiences – you'll be amazed at the opportunities out there! HackerNoon editorial team has launched this interview series with women in tech to celebrate their achievements and share their struggles. We need more women in technology, and by sharing stories, we can encourage many girls to follow their dreams. Share your story today! HackerNoon editorial team has launched this interview series with women in tech to celebrate their achievements and share their struggles. We need more women in technology, and by sharing stories, we can encourage many girls to follow their dreams. Share your story today! HackerNoon editorial team has launched this interview series with women in tech to celebrate their achievements and share their struggles. We need more women in technology, and by sharing stories, we can encourage many girls to follow their dreams. Share your story today! HackerNoon editorial team has launched this interview series with women in tech to celebrate their achievements and share their struggles. We need more women in technology, and by sharing stories, we can encourage many girls to follow their dreams. Share your story today ! this interview series with women in tech Share your story today Tell us about yourself! Tell us about yourself! Hi! I'm Lutsia, and I work in HR in IT. I've been doing this for over 12 years now, and I've worked with some amazing companies like gamedev, dating, music-tech, and social. Now, I'm the HR director of an international company that's doing well developing cool mobile apps for social media. My job is all about making sure the company has a great HR strategy, taking care of all the employees, and helping the business grow by developing its people. My company's products are doing well (currently, only Tinder has more installs than us) and we're seeing over 6 million installs every month. I am an active mentor in various communities such as Women in Tech, Miranna.io, ADP.list, I have done more than 100 consultations and helped more than 100 people to achieve their goals in IT. Why did you choose this field in the first place? Why did you choose this field in the first place? I've always loved studying people and watching talent grow, so it's a perfect fit for me. In HR, it's all about communication, and in the tech industry, it's a bit of a challenge because there are so many introverts who need individual attention. I've got a Master's in Human Resources Management, and I absolutely love what I do. What tech are you most worried about right now and why? What tech are you most worried about right now and why? I'm really interested in technologies that can predict how long employees will stay with a company (like prediction models for employee tenure) and assessing soft skills. Human psychology is such a complex system, isn't it? I find the standard approaches don't always work, which makes it a constant challenge in the world of people management to assess team effectiveness. What are your hobbies and interests outside of tech? What are your hobbies and interests outside of tech? When I'm not doing that, I love nothing more than spending time with my family and friends, or enjoying a good book. I'm a music lover – playing the keyboard and singing are two of my favourite pastimes. I'm also a keen outdoorsy person, and I love nothing more than a good hike! A couple of years ago, I discovered the wonderful world of mentoring, which is a really cool side activity that energises me by interacting with talented people and being useful. Let's talk about breaking the glass ceiling. What were the biggest challenges you faced as a woman in tech, and how did you deal with them? Let's talk about breaking the glass ceiling. What were the biggest challenges you faced as a woman in tech, and how did you deal with them? I started my career in the tech industry, in startups and scale-ups, so I had direct contact with founders and was lucky to avoid unpleasant situations with the glass ceiling. But I would like to see more girls among CEOs and founders of companies. I plan to launch my own project one day. Any questionable misogynistic story/situation you faced/handled, and you want to share with the HackerNoon Fam? Any questionable misogynistic story/situation you faced/handled, and you want to share with the HackerNoon Fam? When I was just starting out in my career, over 12 years ago now, I was working in talent acquisition. I remember how hiring managers would sometimes reject female candidates for developer positions just because they were girls, or because they thought programming was just not a job for women. I remember my first driving instructor always telling me that driving was not for women, but I don't encounter this now. As a HR leader, I try to nip such stories in the bud. What was the biggest setback/failure that you faced, and how did you manage it? What was the biggest setback/failure that you faced, and how did you manage it? My biggest failure was my personal and professional burnout in 2019. I was deeply immersed in the topic and clearly knew the markers of this condition, but unfortunately, I was not able to prevent it in time. However, I learnt my lesson, and I am now much more attentive to my energy levels and have improved my delegating skills even more! What's your biggest achievement that you're really proud of? What's your biggest achievement that you're really proud of? I have reached a high position just in 7 years - HR director in a fast-growing global technology company, every day I do what I love and develop not only the team, overseeing the unlocking of immense human potential, but also being involved in creating products that make a difference in this world and make life better for millions of people. I have extensive mentoring experience and have helped hundreds of people find their successful path to self-realisation in the industry. I am surrounded by amazingly smart and caring people who create beautiful things. In your opinion, why do we see this huge gender gap in the tech industry, and how can we reduce it? In your opinion, why do we see this huge gender gap in the tech industry, and how can we reduce it? The tech industry is still pretty new, so I think there are some historical and cultural things going on that are holding it back. But I do see a lot of tech companies trying to make things better, which is great. They're putting in place these DEI policies, which is really important. I'm part of a group that supports women in IT, and I think it's a vital mission. I would love to see more support, grants, quotas and investments for start-ups created by women.It would be great to change the media narrative and promote the idea that technology is a universal field where gender doesn't matter. We should be creating content that's focused on engaging women and breaking stereotypes. From a company perspective and as a C-Level, it's important to implement training to overcome unconscious bias. Who is your tech idol? Why? Who is your tech idol? Why? I really look up to Sheryl Sandberg, ex-COO of Meta and author of Lean In: Women, Work, and the Will to Lead. She started the global Lean In movement, which connects women through professional networks, support circles, and educational programs. This movement helps women in IT find like-minded people, develop skills and build careers. I really admire how she's so open about the personal struggles she's had, including the loss of her husband. It's so inspiring to see how she's managed to be so successful and still remain human and vulnerable. Do you have any advice for aspiring girls who want to join the field? Do you have any advice for aspiring girls who want to join the field? My advice for girls starting out in HR Tech is to be tenacious in achieving results, and you'll be glad to hear that there are so many opportunities for training and projects now, including through tech communities where you can find first projects and get hands-on experience.It's also great to find a mentor who has already travelled this path and will help you overcome any obstacles and move faster in your professional development. Be open, ask for advice and share your experiences – you'll be amazed at the opportunities out there!

HR Director Lutsia Gorelova Reflects on What's Changed In IT Hiring Over The Past Few Decades

Authors:
(1) Howard Zhong, MIT CSAIL (howardzh@mit.edu);
(2) Mark Hamilton, MIT CSAIL, Microsoft (markth@mit.edu). Table of Links Abstract and 1 Introduction 2 Methodology 3 Results 3.1 CryptoPunks 3.2 Aggregate NFT Market 4 Discussion 5. Conclusion/ Acknowledgements/ References A Appendix A.1 Implementation Details A.2 Detailed NFT Information & A.3 Google NFT Searches Map 4. Discussion We seek to determine what mechanisms produce the different biases and why there exists racial bias but not gender bias in the prices of NFTs. Most NFTs in the market, especially those with gender and race attributes, represent avatars. These NFTs, especially expensive ones like CryptoPunks, can be used as profile picture, and thus people may prefer NFTs that look similar to themselves. We thus believe the demographics of NFT investors are the mechanisms that produce these biases. According to a data by Statistica [2] [4], among the age group (18-34) with the largest interest in NFTs, men and women own NFTs fairly equally with 24% men and 21% women of total investor population. Thus, the fact we do not observe gender bias in NFT prices could be due to investors being roughly balanced across gender. However, the distribution of NFT buyers may be skewed white, which explains the existence of racial bias. Using Google searches as a proxy on the amount of NFT investors in a region, in the past five years, we found that the term “NFT” was most searched in East Asia and North America and least searched in Africa and India. Thus, more lighter-skinned people are interested in NFTs compared to darker-skinned people and may be why lighter-skinned NFTs are more in demand. The full map of Google searches can be found in Figure 7 in Appendix A.3. This paper is available on arxiv under CC BY 4.0 DEED license. Authors: (1) Howard Zhong, MIT CSAIL (howardzh@mit.edu); (2) Mark Hamilton, MIT CSAIL, Microsoft (markth@mit.edu). Authors: Authors: (1) Howard Zhong, MIT CSAIL (howardzh@mit.edu); (2) Mark Hamilton, MIT CSAIL, Microsoft (markth@mit.edu). Table of Links Abstract and 1 Introduction Abstract and 1 Introduction 2 Methodology 2 Methodology 3 Results 3.1 CryptoPunks 3.1 CryptoPunks 3.2 Aggregate NFT Market 3.2 Aggregate NFT Market 4 Discussion 4 Discussion 5. Conclusion/ Acknowledgements/ References Conclusion/ Acknowledgements/ References A Appendix A Appendix A.1 Implementation Details A.1 Implementation Details A.2 Detailed NFT Information & A.3 Google NFT Searches Map A.2 Detailed NFT Information & A.3 Google NFT Searches Map 4. Discussion We seek to determine what mechanisms produce the different biases and why there exists racial bias but not gender bias in the prices of NFTs. Most NFTs in the market, especially those with gender and race attributes, represent avatars. These NFTs, especially expensive ones like CryptoPunks, can be used as profile picture, and thus people may prefer NFTs that look similar to themselves. We thus believe the demographics of NFT investors are the mechanisms that produce these biases. According to a data by Statistica [2] [4], among the age group (18-34) with the largest interest in NFTs, men and women own NFTs fairly equally with 24% men and 21% women of total investor population. Thus, the fact we do not observe gender bias in NFT prices could be due to investors being roughly balanced across gender. However, the distribution of NFT buyers may be skewed white, which explains the existence of racial bias. Using Google searches as a proxy on the amount of NFT investors in a region, in the past five years, we found that the term “NFT” was most searched in East Asia and North America and least searched in Africa and India. Thus, more lighter-skinned people are interested in NFTs compared to darker-skinned people and may be why lighter-skinned NFTs are more in demand. The full map of Google searches can be found in Figure 7 in Appendix A.3. This paper is available on arxiv under CC BY 4.0 DEED license. This paper is available on arxiv under CC BY 4.0 DEED license. available on arxiv

Absence of Gender Bias in NFT Prices Likely Reflects Balanced Investor Demographics

Why Homo Sapiens Are Addicted to Self-Reflections: A Spotify Wrapped Introspective

Author:
(1) David Staines. Table of Links Abstract 1 Introduction 2 Mathematical Arguments 3 Outline and Preview 4 Calvo Framework and 4.1 Household’s Problem 4.2 Preferences 4.3 Household Equilibrium Conditions 4.4 Price-Setting Problem 4.5 Nominal Equilibrium Conditions 4.6 Real Equilibrium Conditions and 4.7 Shocks 4.8 Recursive Equilibrium 5 Existing Solutions 5.1 Singular Phillips Curve 5.2 Persistence and Policy Puzzles 5.3 Two Comparison Models 5.4 Lucas Critique 6 Stochastic Equilibrium and 6.1 Ergodic Theory and Random Dynamical Systems 6.2 Equilibrium Construction 6.3 Literature Comparison 6.4 Equilibrium Analysis 7 General Linearized Phillips Curve 7.1 Slope Coefficients 7.2 Error Coefficients 8 Existence Results and 8.1 Main Results 8.2 Key Proofs 8.3 Discussion 9 Bifurcation Analysis 9.1 Analytic Aspects 9.2 Algebraic Aspects (I) Singularities and Covers 9.3 Algebraic Aspects (II) Homology 9.4 Algebraic Aspects (III) Schemes 9.5 Wider Economic Interpretations 10 Econometric and Theoretical Implications and 10.1 Identification and Trade-offs 10.2 Econometric Duality 10.3 Coefficient Properties 10.4 Microeconomic Interpretation 11 Policy Rule 12 Conclusions and References Appendices A Proof of Theorem 2 and A.1 Proof of Part (i) A.2 Behaviour of ∆ A.3 Proof Part (iii) B Proofs from Section 4 and B.1 Individual Product Demand (4.2) B.2 Flexible Price Equilibrium and ZINSS (4.4) B.3 Price Dispersion (4.5) B.4 Cost Minimization (4.6) and (10.4) B.5 Consolidation (4.8) C Proofs from Section 5, and C.1 Puzzles, Policy and Persistence C.2 Extending No Persistence D Stochastic Equilibrium and D.1 Non-Stochastic Equilibrium D.2 Profits and Long-Run Growth E Slopes and Eigenvalues and E.1 Slope Coefficients E.2 Linearized DSGE Solution E.3 Eigenvalue Conditions E.4 Rouche’s Theorem Conditions F Abstract Algebra and F.1 Homology Groups F.2 Basic Categories F.3 De Rham Cohomology F.4 Marginal Costs and Inflation G Further Keynesian Models and G.1 Taylor Pricing G.2 Calvo Wage Phillips Curve G.3 Unconventional Policy Settings H Empirical Robustness and H.1 Parameter Selection H.2 Phillips Curve I Additional Evidence and I.1 Other Structural Parameters I.2 Lucas Critique I.3 Trend Inflation Volatility 7.2 Error Coefficients 7.2.1 Coefficient Expressions The starting point is the infinite horizon solutions, which states how present deviations depend on present and past shocks. For the expectation variables it implies The first two steps remove expectations to focus on future variables. The third treats lag terms. The fourth is consolidation, the fifth deals with the Euler and the sixth puts them all together. Proceeding through the derivation in order, it is clear that The coefficients have been organised so that the bracketed terms will be positive when computed in the small noise limit at strictly positive rates of trend inflation, as this is a focal alternative to ZINSS.[57] To dig down to primitives it is necessary to expand out the weighting term as follows: Expanding forward using (139), (140) and the primitive properties of the errors yields Thus, I can substitute back into (146) to solve for the third error in terms of the canonical expansions. The unwieldy expression is suppressed. An algorithm for a solution, in terms of the stochastic equilibrium expansion coefficients, would be useful, alongside a method of numerical approximation. However, these tasks lie beyond the boundaries of this investigation. The rest of the derivation is quite simple Combining (139), (140), (149)-(151) gives the following cumbersome expression for the Phillips curve errors All subsequent error forms can be derived easily from this point. 7.2.2 Limiting Solution Now denoting the errors in (117) in the style of the slope coefficients Hence, I am able to solve for the error coefficient using the output term in (112), the error expression (150) and the symmetry implied by (151) and (152) This paper is available on arxiv under CC 4.0 license. Author: (1) David Staines. Author: Author: (1) David Staines. Table of Links Abstract Abstract 1 Introduction 1 Introduction 2 Mathematical Arguments 2 Mathematical Arguments 3 Outline and Preview 3 Outline and Preview 4 Calvo Framework and 4.1 Household’s Problem 4 Calvo Framework and 4.1 Household’s Problem 4.2 Preferences 4.2 Preferences 4.3 Household Equilibrium Conditions 4.3 Household Equilibrium Conditions 4.4 Price-Setting Problem 4.4 Price-Setting Problem 4.5 Nominal Equilibrium Conditions 4.5 Nominal Equilibrium Conditions 4.6 Real Equilibrium Conditions and 4.7 Shocks 4.6 Real Equilibrium Conditions and 4.7 Shocks 4.8 Recursive Equilibrium 4.8 Recursive Equilibrium 5 Existing Solutions 5 Existing Solutions 5.1 Singular Phillips Curve 5.1 Singular Phillips Curve 5.2 Persistence and Policy Puzzles 5.2 Persistence and Policy Puzzles 5.3 Two Comparison Models 5.3 Two Comparison Models 5.4 Lucas Critique 5.4 Lucas Critique 6 Stochastic Equilibrium and 6.1 Ergodic Theory and Random Dynamical Systems 6 Stochastic Equilibrium and 6.1 Ergodic Theory and Random Dynamical Systems 6.2 Equilibrium Construction 6.2 Equilibrium Construction 6.3 Literature Comparison 6.3 Literature Comparison 6.4 Equilibrium Analysis 6.4 Equilibrium Analysis 7 General Linearized Phillips Curve 7 General Linearized Phillips Curve 7.1 Slope Coefficients 7.1 Slope Coefficients 7.2 Error Coefficients 7.2 Error Coefficients 8 Existence Results and 8.1 Main Results 8 Existence Results and 8.1 Main Results 8.2 Key Proofs 8.2 Key Proofs 8.3 Discussion 8.3 Discussion 9 Bifurcation Analysis 9 Bifurcation Analysis 9.1 Analytic Aspects 9.1 Analytic Aspects 9.2 Algebraic Aspects (I) Singularities and Covers 9.2 Algebraic Aspects (I) Singularities and Covers 9.3 Algebraic Aspects (II) Homology 9.3 Algebraic Aspects (II) Homology 9.4 Algebraic Aspects (III) Schemes 9.4 Algebraic Aspects (III) Schemes 9.5 Wider Economic Interpretations 9.5 Wider Economic Interpretations 10 Econometric and Theoretical Implications and 10.1 Identification and Trade-offs 10 Econometric and Theoretical Implications and 10.1 Identification and Trade-offs 10.2 Econometric Duality 10.2 Econometric Duality 10.3 Coefficient Properties 10.3 Coefficient Properties 10.4 Microeconomic Interpretation 10.4 Microeconomic Interpretation 11 Policy Rule 11 Policy Rule 12 Conclusions and References 12 Conclusions and References Appendices Appendices A Proof of Theorem 2 and A.1 Proof of Part (i) A Proof of Theorem 2 and A.1 Proof of Part (i) A.2 Behaviour of ∆ A.2 Behaviour of ∆ A.3 Proof Part (iii) A.3 Proof Part (iii) B Proofs from Section 4 and B.1 Individual Product Demand (4.2) B Proofs from Section 4 and B.1 Individual Product Demand (4.2) B.2 Flexible Price Equilibrium and ZINSS (4.4) B.2 Flexible Price Equilibrium and ZINSS (4.4) B.3 Price Dispersion (4.5) B.3 Price Dispersion (4.5) B.4 Cost Minimization (4.6) and (10.4) B.4 Cost Minimization (4.6) and (10.4) B.5 Consolidation (4.8) B.5 Consolidation (4.8) C Proofs from Section 5, and C.1 Puzzles, Policy and Persistence C Proofs from Section 5, and C.1 Puzzles, Policy and Persistence C.2 Extending No Persistence C.2 Extending No Persistence D Stochastic Equilibrium and D.1 Non-Stochastic Equilibrium D Stochastic Equilibrium and D.1 Non-Stochastic Equilibrium D.2 Profits and Long-Run Growth D.2 Profits and Long-Run Growth E Slopes and Eigenvalues and E.1 Slope Coefficients E Slopes and Eigenvalues and E.1 Slope Coefficients E.2 Linearized DSGE Solution E.2 Linearized DSGE Solution E.3 Eigenvalue Conditions E.3 Eigenvalue Conditions E.4 Rouche’s Theorem Conditions E.4 Rouche’s Theorem Conditions F Abstract Algebra and F.1 Homology Groups F Abstract Algebra and F.1 Homology Groups F.2 Basic Categories F.2 Basic Categories F.3 De Rham Cohomology F.3 De Rham Cohomology F.4 Marginal Costs and Inflation F.4 Marginal Costs and Inflation G Further Keynesian Models and G.1 Taylor Pricing G Further Keynesian Models and G.1 Taylor Pricing G.2 Calvo Wage Phillips Curve G.2 Calvo Wage Phillips Curve G.3 Unconventional Policy Settings G.3 Unconventional Policy Settings H Empirical Robustness and H.1 Parameter Selection H Empirical Robustness and H.1 Parameter Selection H.2 Phillips Curve H.2 Phillips Curve I Additional Evidence and I.1 Other Structural Parameters I Additional Evidence and I.1 Other Structural Parameters I.2 Lucas Critique I.2 Lucas Critique I.3 Trend Inflation Volatility I.3 Trend Inflation Volatility 7.2 Error Coefficients 7.2.1 Coefficient Expressions The starting point is the infinite horizon solutions, which states how present deviations depend on present and past shocks. For the expectation variables it implies The first two steps remove expectations to focus on future variables. The third treats lag terms. The fourth is consolidation, the fifth deals with the Euler and the sixth puts them all together. Proceeding through the derivation in order, it is clear that The coefficients have been organised so that the bracketed terms will be positive when computed in the small noise limit at strictly positive rates of trend inflation, as this is a focal alternative to ZINSS.[57] To dig down to primitives it is necessary to expand out the weighting term as follows: Expanding forward using (139), (140) and the primitive properties of the errors yields Thus, I can substitute back into (146) to solve for the third error in terms of the canonical expansions. The unwieldy expression is suppressed. An algorithm for a solution, in terms of the stochastic equilibrium expansion coefficients, would be useful, alongside a method of numerical approximation. However, these tasks lie beyond the boundaries of this investigation. The rest of the derivation is quite simple Combining (139), (140), (149)-(151) gives the following cumbersome expression for the Phillips curve errors All subsequent error forms can be derived easily from this point. 7.2.2 Limiting Solution 7.2.2 Limiting Solution Now denoting the errors in (117) in the style of the slope coefficients Hence, I am able to solve for the error coefficient using the output term in (112), the error expression (150) and the symmetry implied by (151) and (152) This paper is available on arxiv under CC 4.0 license. This paper is available on arxiv under CC 4.0 license. available on arxiv

How Error Coefficients Reflect Stochastic Equilibrium Expansions in Inflation Models

You heard it right, Startups of The Year is back for its 3rd season! Startups of The Year is a community-driven event created and powered by HackerNoon’s proprietary software, dedicated to recognizing and celebrating tech startups that are making a positive impact on technology and the world. Closing on Startups of The Year 2023, we have achieved a total of 623K+ votes from the community (triple from the prior year) to 30,000+ startups across 4200+ cities ✨🙌 This year we set out to shine the Spotlight on Tech’s Shining Stars (yes, all 150,000 of them 🤭) Coming on to the podium, have you prepared a speech? If not, let this article be your guide to 2024’s Startups of The Year 🚀 Let’s take a trip down memory lane, while also learning from how last year’s nominees flaunted the news of their nominations 🔎 FYI, with Startups of The Year 2024, we're introducing industry awards, categorizing startups by sector. You can find more info here. My Startups Got Nominated. What Should I Do? The FIRST thing that you’re going to do… well after you claim and verify your company, you PROMOTE the heck out of your Startup 💚 Here’s how 2023 Startups did it… PRO TIP: Content is your best friend! Utilize social media strengths to spread the word about your Startups of The Year nomination! Facebook, LinkedIn, X… the more the merrier. You have bragging rights, so post on EVERY social platform possible🔥
Don’t forget to tag HackerNoon, we’d love to support your company to the top 1️⃣ by featuring you on our testimonials site and social media! Here’s How 2023 Startups Did It, On LinkedIn Whether it is a simple call for voting with the Startups of The Year’s key visual or having the Founder/CEO post on their page for increased reach, let your creativity run wild: repost, run a campaign, write an article on HackerNoon, and blast it everywhere! Be vocal and be proud - your startup DESERVES all the recognition! Show the world why they should vote for you!
➡️ Write about your startup mission and vision using this interview template Remember to follow up! You know that one call for voting post isn’t enough - Divide to conquer! Remind your followers that you are still running for the title. Create a sense of urgency and competition like these startups did in 2023 ⬇️ See more on how nominated Startups called for voting in 2023 on LinkedIn here What About Facebook? You bet! Aside from LinkedIn, Facebook is also a good platform to announce your Startups of The Year nomination. See more on how nominated Startups called for voting in 2023 on Facebook here And Don’t Forget To Tweet About Your Nomination I know we all have *diverse* opinions on X (Twitter). Regardless, tweeting is still a good way to brag about your Startups of The Year nomination and call for voting. See more on how nominated Startups called for voting in 2023 on X here I’m sad…my Startup wasn’t nominated… 😔 You have two options: You can either nominate yourself… (it's completely legitimate - see the criteria here)


Or, let your community surprise you with a nomination and revel in the unexpected recognition!
Wojciech Sierocki, co-founder and CEO of Data Lake was taken by surprise too when their startup, Data Lake, got nominated for Startups of The Year 2023. Still have questions about nominations? Check out this guide! About HackerNoon’s Startups of The Year Startups of The Year 2024 is HackerNoon’s flagship community-driven event celebrating startups, technology, and the spirit of innovation. Currently in its third iteration, the prestigious Internet award recognizes and celebrates tech startups of all shapes and sizes. This year, over 150,000 entities across 4200+ cities, 6 continents, and 100+ industries will participate in a bid to be crowned the best startup of the year! Millions of votes have been cast over the past few years, and many stories have been written about these daring and rising startups. The winners will get a free interview on HackerNoon and an Evergreen Tech Company News page. Visit ourFAQ page to learn more. Download our design assets here. Check out the Startups of the Year Merch Shop here. HackerNoon’s Startups of The Year is a branding opportunity unlike any other. Whether your goal is brand awareness or lead generation, HackerNoon has curated startup-friendly packages to solve your marketing challenges. Meet our sponsors: Wellfound: At Wellfound, we're not just a job board—we're the place where top startup talent and the world's most exciting companies connect to build the future. Notion: Notion is trusted and loved by thousands of startups as their connected workspace—from building product roadmaps to tracking fundraising. Try Notion with unlimited AI, FREE for up to 6 months, to build and scale your company with one powerful tool. Get your offer now! Hubspot: If you’re looking for a smart CRM platform that meets the needs of small businesses, look no further than HubSpot. Seamlessly connect your data, teams and customers in one easy-to-use scalable platform that grows with your business. Bright Data: Startups that leverage public web data can make faster, data-driven decisions, giving them a competitive edge. With Bright Data’s scalable web data collection, businesses can grow from a small operation to an enterprise by harnessing insights at every stage. Algolia: Algolia NeuralSearch is the world's only AI end-to-end Search and Discovery Platform combining powerful keyword and natural language processing in a single API. You heard it right, Startups of The Year is back for its 3rd season! Startups of The Year is a community-driven event created and powered by HackerNoon’s proprietary software, dedicated to recognizing and celebrating tech startups that are making a positive impact on technology and the world. Closing on Startups of The Year 2023 , we have achieved a total of 623K+ votes from the community (triple from the prior year) to 30,000+ startups across 4200+ cities ✨🙌 Startups of The Year is back Startups of The Year is back Startups of The Year is back Startups of The Year 2023 Startups of The Year 2023 Startups of The Year 2023 This year we set out to shine the Spotlight on Tech’s Shining Stars (yes, all 150,000 of them 🤭) Coming on to the podium, have you prepared a speech? If not, let this article be your guide to 2024’s Startups of The Year 🚀 Startups of The Year Let’s take a trip down memory lane, while also learning from how last year’s nominees flaunted the news of their nominations 🔎 FYI, with Startups of The Year 2024, we're introducing industry awards, categorizing startups by sector. You can find more info here. FYI, with Startups of The Year 2024 , we're introducing industry awards, categorizing startups by sector. You can find more info here. Startups of The Year 2024 here. here . here My Startups Got Nominated. What Should I Do? The FIRST thing that you’re going to do… well after you claim and verify your company, you PROMOTE the heck out of your Startup 💚 Here’s how 2023 Startups did it… claim claim claim verify verify PROMOTE the heck out of your Startup PROMOTE the heck out of your Startup PRO TIP: Content is your best friend! Utilize social media strengths to spread the word about your Startups of The Year nomination! Facebook, LinkedIn, X… the more the merrier. You have bragging rights, so post on EVERY social platform possible🔥 Don’t forget to tag HackerNoon, we’d love to support your company to the top 1️⃣ by featuring you on our testimonials site and social media! PRO TIP: Content is your best friend! Utilize social media strengths to spread the word about your Startups of The Year nomination ! Facebook, LinkedIn, X… the more the merrier. You have bragging rights , so post on EVERY social platform possible🔥 PRO TIP: Startups of The Year nomination You have bragging rights EVERY Don’t forget to tag HackerNoon, we’d love to support your company to the top 1️⃣ by featuring you on our testimonials site and social media! testimonials site testimonials site testimonials site social media! social media! Here’s How 2023 Startups Did It, On LinkedIn Whether it is a simple call for voting with the Startups of The Year’s key visual or having the Founder/CEO post on their page for increased reach, let your creativity run wild: repost, run a campaign, write an article on HackerNoon, and blast it everywhere ! Be vocal and be proud - your startup DESERVES all the recognition! write an article on HackerNoon, and blast it everywhere write an article on HackerNoon, and blast it everywhere DESERVES DESERVES Show the world why they should vote for you! ➡️ Write about your startup mission and vision using this interview template Show the world why they should vote for you! Show the world why they should vote for you! ➡️ Write about your startup mission and vision using this interview template interview template interview template Remember to follow up! You know that one call for voting post isn’t enough - Divide to conquer! Remind your followers that you are still running for the title. Create a sense of urgency and competition like these startups did in 2023 ⬇️ Remember to follow up ! You know that one call for voting post isn’t enough - Divide to conquer ! Remind your followers that you are still running for the title. Create a sense of urgency and competition like these startups did in 2023 ⬇️ Remember to follow up Remember to follow up one Divide to conquer Divide to conquer Create a sense of urgency and competition See more on how nominated Startups called for voting in 2023 on LinkedIn here See more on how nominated Startups called for voting in 2023 on LinkedIn here here here here What About Facebook? You bet! Aside from LinkedIn, Facebook is also a good platform to announce your Startups of The Year nomination. See more on how nominated Startups called for voting in 2023 on Facebook here See more on how nominated Startups called for voting in 2023 on Facebook here here here here And Don’t Forget To Tweet About Your Nomination I know we all have *diverse* opinions on X (Twitter). Regardless, tweeting is still a good way to brag about your Startups of The Year nomination and call for voting. *diverse* *diverse* See more on how nominated Startups called for voting in 2023 on X here See more on how nominated Startups called for voting in 2023 on X here here here here I’m sad…my Startup wasn’t nominated… 😔 You have two options: You can either nominate yourself… (it's completely legitimate - see the criteria here) Or, let your community surprise you with a nomination and revel in the unexpected recognition!
Wojciech Sierocki, co-founder and CEO of Data Lake was taken by surprise too when their startup, Data Lake, got nominated for Startups of The Year 2023. You can either nominate yourself… (it's completely legitimate - see the criteria here) You can either nominate yourself… (it's completely legitimate - see the criteria here ) here Or, let your community surprise you with a nomination and revel in the unexpected recognition! Wojciech Sierocki, co-founder and CEO of Data Lake was taken by surprise too when their startup, Data Lake, got nominated for Startups of The Year 2023. Or, let your community surprise you with a nomination and revel in the unexpected recognition! Wojciech Sierocki, co-founder and CEO of Data Lake was taken by surprise too when their startup, Data Lake, got nominated for Startups of The Year 2023. Data Lake Still have questions about nominations? Check out this guide! Still have questions about nominations? Check out this guide! Still have questions about nominations? Check out this guide ! this guide About HackerNoon’s Startups of The Year Startups of The Year 2024 is HackerNoon’s flagship community-driven event celebrating startups, technology, and the spirit of innovation. Currently in its third iteration, the prestigious Internet award recognizes and celebrates tech startups of all shapes and sizes. This year, over 150,000 entities across 4200+ cities, 6 continents, and 100+ industries will participate in a bid to be crowned the best startup of the year! Millions of votes have been cast over the past few years, and many stories have been written about these daring and rising startups. Startups of The Year 2024 many stories The winners will get a free interview on HackerNoon and an Evergreen Tech Company News page. free interview Evergreen Tech Company News Visit our FAQ page to learn more. FAQ page Download our design assets here . here Check out the Startups of the Year Merch Shop here . here HackerNoon’s Startups of The Year is a branding opportunity unlike any other. Whether your goal is brand awareness or lead generation, HackerNoon has curated startup-friendly packages to solve your marketing challenges. startup-friendly packages Meet our sponsors: Meet our sponsors: Wellfound: At Wellfound, we're not just a job board—we're the place where top startup talent and the world's most exciting companies connect to build the future. Wellfound: Notion: Notion is trusted and loved by thousands of startups as their connected workspace—from building product roadmaps to tracking fundraising. Try Notion with unlimited AI, FREE for up to 6 months , to build and scale your company with one powerful tool. Get your offer now ! Notion: Try Notion with unlimited AI, FREE for up to 6 months Get your offer now ! Hubspot: If you’re looking for a smart CRM platform that meets the needs of small businesses, look no further than HubSpot. Seamlessly connect your data, teams and customers in one easy-to-use scalable platform that grows with your business. Hubspot: Bright Data: Startups that leverage public web data can make faster, data-driven decisions, giving them a competitive edge. With Bright Data’s scalable web data collection , businesses can grow from a small operation to an enterprise by harnessing insights at every stage. Bright Data: Bright Data’s scalable web data collection Algolia: Algolia NeuralSearch is the world's only AI end-to-end Search and Discovery Platform combining powerful keyword and natural language processing in a single API. Algolia: AI end-to-end Search and Discovery Platform

The Impact of HackerNoon's Startups of The Year: Reflections from Last Year’s Nominees

Die impak van HackerNoon se Startups of The Year: Refleksies van verlede jaar se genomineerdes

L'impacte de les startups de l'any de HackerNoon: reflexions dels nominats de l'any passat

El impacto de las startups del año de HackerNoon: reflexiones de los nominados del año pasado

O impacto das startups do ano de HackerNoon: reflexións dos nomeados do ano pasado

HackerNoon の「今年のスタートアップ」の影響: 昨年のノミネート企業からの考察

HackerNoon компаниясының жыл стартаптарының әсері: өткен жылғы үміткерлердің ойлары

ຜົນກະທົບຂອງການເລີ່ມຕົ້ນຂອງປີຂອງ HackerNoon: ການສະທ້ອນຈາກຜູ້ຖືກແຕ່ງຕັ້ງໃນປີກາຍນີ້

ह्याकरनूनको स्टार्टअप अफ द इयरको प्रभाव: गत वर्षका मनोनयनहरूबाट प्रतिबिम्ब

Kgahlamelo ya Dithomelo tša HackerNoon tša Ngwaga: Ditlhathollo go tšwa go Bakgethwa ba Ngwaga wo o fetilego

Athari za Mwanzo wa Mwaka wa HackerNoon: Tafakari kutoka kwa Walioteuliwa Mwaka Jana.

ผลกระทบของ Startups of The Year จาก HackerNoon: บทสะท้อนจากผู้เข้าชิงในปีที่แล้ว

“HackerNoon” -yň ýylyň başlangyçlarynyň täsiri: Geçen ýyl dalaşgärleriň pikirleri

To write in public or not... Note: This piece is intentionally raw and unpolished, reflecting a direct flow of thoughts—a mental dialogue. I like to write... words and code... both are close to my heart... one allows me to open up my thoughts, and the other allows me to play and find joy. But why write in public?... keep it private... write whatever... why draw attention here?... will you not be judged? Well... I have given it some thought... yes! Opinions can create distractions... I don't intend to seek attention... I have written a lot in private... but I aspire to connect with thinkers and creators of our time... a clan I believe I belong to. I aspire to have conversations with thinkers... and explore possibilities of human endeavors... The world has largely become transactional... society has created these factories of workers... called companies and corporations... where I see humans being treated as resources... and have processes to put them on some kind of efficiency machine to churn out all their energies for transactional needs... Very few, I find, are truly alive. Yes! These factories help us thrive in financial security, family, kids, friends, and travel... we seek happiness in these forms... but most end up spending more than 60% of their life doing things they don't enjoy. Add on top... instead of earning and acquiring, we shift to taking loans and acquiring... repaying in installments forever making life even heavier. I also see people who retire out of these factories with earned comforts and loved ones around... yet most find it difficult to restructure life to fathom boredom... spending time alone feels lonely and burdensome. It’s a tradeoff, and many die long before mortal death arrives... and one day we are erased... maybe remembered by the world for some time... but our identity fades into this vast cosmos. Is this all there is to life... a set pattern of to-dos? Our education system... seems like another kind of factory... they invite and lure us with promises of a great life ahead... conditioning us for 3-5 years to be part of these work factories. It seems like both factories are conspiring to make us believe that we are no more than human resources. I do find small startups... the small factories... small teams with no hierarchy... where we are not treated as resources. It looks like a great place to be if we are driven... if we are problem-solvers... deep divers... don’t always wait for orders to act... believe in collaboration. Here, we all take responsibility for our work... we feel valued... and many of us truly enjoy the process... trying to build something together... amidst a lot of uncertainty. I see many alive here. Now there is a new entrant—AI, which is evolving at a pace that has started shaking things apart for these old factories that train and treat humans as resources. I see it as a great enabler of discovery and exploration... capable of solving complex problems with human collaboration... but it will also reduce the current factories, and existing human resources will need to adapt quickly and explore a new set of possibilities. I now see micro-factories emerging... just 2-3 people building things with AI... this looks even better, giving rise to solo or micro-entrepreneurship... a small group of creators and innovators building and collaborating with AI agents, ushering in a new era of innovations and discoveries. As I explore life, I keep discovering many such factories (big and small) that society has created for personal and transactional needs... and I am cautious about where I choose to tune in. This is just the beginning of my exploration—I'd love to exchange ideas with others on this journey. To write in public or not... To write in public or not... Note: This piece is intentionally raw and unpolished, reflecting a direct flow of thoughts—a mental dialogue. Note: This piece is intentionally raw and unpolished, reflecting a direct flow of thoughts—a mental dialogue. Note: This piece is intentionally raw and unpolished, reflecting a direct flow of thoughts—a mental dialogue. I like to write... words and code... both are close to my heart... one allows me to open up my thoughts, and the other allows me to play and find joy. But why write in public?... keep it private... write whatever... why draw attention here?... will you not be judged? Well... I have given it some thought... yes! Opinions can create distractions... I don't intend to seek attention... I have written a lot in private... but I aspire to connect with thinkers and creators of our time... a clan I believe I belong to. I aspire to have conversations with thinkers... and explore possibilities of human endeavors... The world has largely become transactional... society has created these factories of workers... called companies and corporations... where I see humans being treated as resources... and have processes to put them on some kind of efficiency machine to churn out all their energies for transactional needs... Very few, I find, are truly alive. Yes! These factories help us thrive in financial security, family, kids, friends, and travel... we seek happiness in these forms... but most end up spending more than 60% of their life doing things they don't enjoy. Add on top... instead of earning and acquiring, we shift to taking loans and acquiring... repaying in installments forever making life even heavier. I also see people who retire out of these factories with earned comforts and loved ones around... yet most find it difficult to restructure life to fathom boredom... spending time alone feels lonely and burdensome. It’s a tradeoff, and many die long before mortal death arrives... and one day we are erased... maybe remembered by the world for some time... but our identity fades into this vast cosmos. Is this all there is to life... a set pattern of to-dos? Our education system... seems like another kind of factory... they invite and lure us with promises of a great life ahead... conditioning us for 3-5 years to be part of these work factories. It seems like both factories are conspiring to make us believe that we are no more than human resources. I do find small startups... the small factories... small teams with no hierarchy... where we are not treated as resources. It looks like a great place to be if we are driven... if we are problem-solvers... deep divers... don’t always wait for orders to act... believe in collaboration. Here, we all take responsibility for our work... we feel valued... and many of us truly enjoy the process... trying to build something together... amidst a lot of uncertainty. I see many alive here. Now there is a new entrant—AI, which is evolving at a pace that has started shaking things apart for these old factories that train and treat humans as resources. I see it as a great enabler of discovery and exploration... capable of solving complex problems with human collaboration... but it will also reduce the current factories, and existing human resources will need to adapt quickly and explore a new set of possibilities. I now see micro-factories emerging... just 2-3 people building things with AI... this looks even better, giving rise to solo or micro-entrepreneurship... a small group of creators and innovators building and collaborating with AI agents, ushering in a new era of innovations and discoveries. As I explore life, I keep discovering many such factories (big and small) that society has created for personal and transactional needs... and I am cautious about where I choose to tune in. This is just the beginning of my exploration—I'd love to exchange ideas with others on this journey.

Discovering Human Factories: A Personal Reflection on Modern Work, AI, and Creativity

Authors:
(1) Aviad Rom, The Data Science Institute, Reichman University, Herzliya, Israel;
(2) Kfir Bar, The Data Science Institute, Reichman University, Herzliya, Israel. Table of Links Abstract and Introduction Related Work Methodology Experimental Settings Results Conclusion and Limitations Bibliographical References 6. Conclusion Arabic and Hebrew, both Semitic languages, display inherent structural resemblances and possess shared cognates. In an endeavor to allow a bilingual language model to recognize these cognates, we introduced a novel language model tailored for Arabic and Hebrew, wherein the Arabic text is transliterated into the Hebrew script prior to both pre-training and fine-tuning. We contrast our model by training another language model on the identical dataset but without the transliteration preprocessing step, in order to assess the impact of transliteration. We fine-tuned our model for the machine translation task, yielding promising outcomes. These results suggest that the transliteration step offers tangible benefits to the translation process. Comparing to the translation combination involving other language models, we see comparable results; this is encouraging given that the training data we utilized for pre-training the model is approximately 60% smaller than theirs. As a future avenue of research, we intend to train the model on an expanded dataset and explore scaling its architecture. In this study, our emphasis was on a transformer encoder. We are keen to investigate the effects of implementing transliteration within a decoder architecture, once such a model becomes available for Hebrew. Limitations The transliteration algorithm from Arabic to Hebrew is based a simple deterministic lookup table. However, sometimes the transliteration is not that straight forward, and this simple algorithm generates some odd rendering, which we would like to fix. For example, our algorithm does not place a final-form letter at the end of the Arabic word in Hebrew. Another challenge with transliteration into Hebrew is that for some words a Hebrew writer may choose to omit long vowel characters and the readers will still be able to understand the word. This phenomenon is referred to as “Ktiv Hasser” in Hebrew. Yet, there exists a preference for certain word representations over others. This inconsistency makes it more challenging for aligning the transliterated Arabic words to their cognates in the way they are written. Our transliteration algorithm always renders the Arabic word following the Arabic letters, which may be different than how this word is typically written in Hebrew. Another limitation is the relatively small size of the dataset which we used for pre-training the language model, comparing to other existing language models of the same architecture size. This paper is available on arxiv under CC BY 4.0 DEED license. Authors: (1) Aviad Rom, The Data Science Institute, Reichman University, Herzliya, Israel; (2) Kfir Bar, The Data Science Institute, Reichman University, Herzliya, Israel. Authors: Authors: (1) Aviad Rom, The Data Science Institute, Reichman University, Herzliya, Israel; (2) Kfir Bar, The Data Science Institute, Reichman University, Herzliya, Israel. Table of Links Abstract and Introduction Abstract and Introduction Related Work Related Work Methodology Methodology Experimental Settings Experimental Settings Results Results Conclusion and Limitations Conclusion and Limitations Bibliographical References Bibliographical References 6. Conclusion Arabic and Hebrew, both Semitic languages, display inherent structural resemblances and possess shared cognates. In an endeavor to allow a bilingual language model to recognize these cognates, we introduced a novel language model tailored for Arabic and Hebrew, wherein the Arabic text is transliterated into the Hebrew script prior to both pre-training and fine-tuning. We contrast our model by training another language model on the identical dataset but without the transliteration preprocessing step, in order to assess the impact of transliteration. We fine-tuned our model for the machine translation task, yielding promising outcomes. These results suggest that the transliteration step offers tangible benefits to the translation process. Comparing to the translation combination involving other language models, we see comparable results; this is encouraging given that the training data we utilized for pre-training the model is approximately 60% smaller than theirs. As a future avenue of research, we intend to train the model on an expanded dataset and explore scaling its architecture. In this study, our emphasis was on a transformer encoder. We are keen to investigate the effects of implementing transliteration within a decoder architecture, once such a model becomes available for Hebrew. Limitations The transliteration algorithm from Arabic to Hebrew is based a simple deterministic lookup table. However, sometimes the transliteration is not that straight forward, and this simple algorithm generates some odd rendering, which we would like to fix. For example, our algorithm does not place a final-form letter at the end of the Arabic word in Hebrew. Another challenge with transliteration into Hebrew is that for some words a Hebrew writer may choose to omit long vowel characters and the readers will still be able to understand the word. This phenomenon is referred to as “Ktiv Hasser” in Hebrew. Yet, there exists a preference for certain word representations over others. This inconsistency makes it more challenging for aligning the transliterated Arabic words to their cognates in the way they are written. Our transliteration algorithm always renders the Arabic word following the Arabic letters, which may be different than how this word is typically written in Hebrew. Another limitation is the relatively small size of the dataset which we used for pre-training the language model, comparing to other existing language models of the same architecture size. This paper is available on arxiv under CC BY 4.0 DEED license. This paper is available on arxiv under CC BY 4.0 DEED license. available on arxiv

Reflections on HeArBERT: Transliteration Benefits, Research Horizons, and Limitations

Ethereum's Slump Reflects the Web3 Development Dilemma

Building a two-sided managed pet care platform as first-time founders is not an easy task. Looking back, it's clear that some intuitive decisions brought us to where we are today. After 1.5 years of bootstrapping, we raised $400,000 from a VC fund and an angel syndicate, with follow-on investments totaling $1 million. We now have 30,000 paying customers, 3,000 pet caregivers connected to our platform, and over $5 million in gross revenue since launch. Here's my reflection on the key decisions that brought us to this point. Tip 1: Don't Chase Investors Too Early; Focus on Traction First. A couple of months after our launch, with our first customers on board, we thought raising funds would be a breeze. We prepared a conventional pitch deck and business model and started meeting with angel investors and early-stage VCs. However, we quickly realized it was challenging to convince investors to back two first-time founders with a business earning only $1,500 monthly. With our personal runway nearly exhausted, we had an honest discussion and asked ourselves: Do we want to continue without securing a seed round? The answer was yes. We then asked ourselves how we could survive and improve our chances of fundraising later. We decided to stop wasting time chasing investors and focus on gaining traction. This decision boosted our team's morale. Our success was now in our hands, not dependent on funding. By focusing on traction, we implemented key changes that helped us grow tenfold in one year. I'll discuss these changes in the following tips. Tip 2: Improve Your Unit Economics – Be as Effective as You Can to Survive. One of the challenges we faced in becoming profitable was our low take rate. We launched with favorable terms for pet caregivers: after subsidizing transport expenses, our take rate was 18%. This motivated pet caregivers to serve our first customers, but it wasn't enough to achieve profitability quickly with a bootstrapped approach. I wondered: What if we could earn more from every order? What if we could acquire new pet caregivers on more favorable terms for the company? What if existing pet caregivers accepted changes in the transport subsidy? Changing the amount our service providers earned was daunting, but two adjustments helped us double our take rate to 35%: Introduce a cap on transportation coverage.
Increase our take rate for new pet caregivers joining the platform. Sometimes, we underestimate the value our business provides to users. It's crucial to constantly ask: What if we could earn more on each unit? Tip 3: Try Bootstrap Marketing Instead of Paid Ads. As a startup with a novel concept, you'll likely struggle to win user trust initially. Limited funds for ad testing and the need for quick results often lead to lower conversion rates compared to established competitors. This makes it challenging to achieve positive unit economics from paid channels early on. Our first attempt at SEM didn't yield results, so we explored alternative channels due to budget constraints. Here's what worked for us: 📣 Send Press Releases to the Media Outlets First, we sent press releases to major lifestyle media in our region. Some picked up the story and announced our product launch. Consider researching media outlets relevant to your field and reach out to them. Establishing a public presence for your brand is crucial in the early stages. 🤴 Partner with Industry Experts Next, we partnered with respected influencers in our field. When they mentioned our business to their audience, we gained both warm leads and valuable social proof. These leads were already confident in our product due to the influencers' endorsement. Who are the key voices in your industry? Is there potential to build connections with them? 👩‍💼 Tap into Corporate Networks Our third effective channel was partnerships with enterprises. They promoted our exclusive offers to their employees through internal communications, helping us secure early adopters from their workforce. If your product or service has broad appeal, consider exploring ways to include it in corporate benefits programs. Tip 4: Consider Additional Revenue Streams, Even if They Seem to Diverge From Your Initial Focus. When we launched our pet care platform, we initially only connected pet parents with dog walkers. However, we soon realized that adding dog boarding could provide an additional revenue stream because: Our existing customers were requesting boarding/sitting services.
International competitors already offered this product vertical. While launching a new product might seem risky or unfocused, it's crucial to differentiate between introducing a completely new offering to a new audience versus a complementary product for your existing customer base. In our case, we were fortunate to launch the dog boarding vertical just before the vacation season when people frequently cancel walking services and search for dog sitters. This decision significantly influenced our successful investment round closure. The boarding vertical generated an additional $24,400 in revenue, which, when annualized, added approximately $280,000 to our pre-money valuation during deal discussions in October (having multiple ~9X to yearly gross revenue). Tip 5: Find an Advisor From a Similar Company That's a Few Steps ahead of Yours. After our launch, we were fortunate to bring on board a mentor/advisor who was a co-founder and CEO of a Round A stage company with a similar on-demand business model - a medical tech company providing house call doctor services. Orders are placed via mobile app and chatbot as we do. His guidance was crucial in several key areas: 💰 Fundraising Our advisor tipped us off about a startup competition organized by McKinsey & Company. Among the organizers and jury members were angel investors who had backed his medical company. I believe having him as an advisor significantly boosted our chances during the initial selection stage, where only 12 companies were chosen out of 600+ applicants. The organizers were already familiar with him and understood the on-demand business model, putting us in the right place at the right time. We made it to the finals and, although we didn't clinch the win, we still managed to secure a seed round from an angel syndicate that included jury members from the competition. Consider bringing on board someone with hands-on entrepreneurship experience in a similar market or with a comparable business model. They can provide warm introductions to investors, which can be invaluable. 🎓 Re-use best practices As a first-time founder, especially a young one like myself, you often lack experience in areas like people management, stakeholder relations, and hiring. Sometimes, you might need specific advice on topics like launching paid ads without failing. Having someone who's already gained this experience can significantly reduce mistakes, saving company funds and ultimately increasing your chances of success. The key is to listen and learn. 🆘 Moral Support and Constant Challenging Being an early-stage venture founder means constantly managing your emotions. You might swing from "we're the worst company ever, customers will stop using our app" when you receive a negative Trustpilot rating in the morning, to "we're doing quite well" when you deploy a new feature later that day. Things become even more intense when you attract funds, bring investors on board, start hiring employees, and sometimes need to let go of underperformers - it's quite stressful. Moreover, without a boss, it can be hard to adequately assess your own performance - is it poor or good? Having an advisor can help you handle stress as you can transparently discuss all ups and downs. But they can also provide the feedback you need to improve, which is harder to receive when you're working on your own project without someone senior above you. Conclusion I believe these five strategies were crucial to bootstrapping our growth and securing seed funding. Every startup's journey is unique, but focusing on traction, optimizing operational efficiency, and leveraging experienced mentors can significantly increase your chances of success. I hope my insights prove helpful to entrepreneurs building early-stage products. Building a two-sided managed pet care platform as first-time founders is not an easy task. Looking back, it's clear that some intuitive decisions brought us to where we are today. After 1.5 years of bootstrapping, we raised $400,000 from a VC fund and an angel syndicate, with follow-on investments totaling $1 million. We now have 30,000 paying customers, 3,000 pet caregivers connected to our platform, and over $5 million in gross revenue since launch. Here's my reflection on the key decisions that brought us to this point. Tip 1: Don't Chase Investors Too Early; Focus on Traction First. Tip 1: Don't Chase Investors Too Early; Focus on Traction First. A couple of months after our launch, with our first customers on board, we thought raising funds would be a breeze. We prepared a conventional pitch deck and business model and started meeting with angel investors and early-stage VCs. However, we quickly realized it was challenging to convince investors to back two first-time founders with a business earning only $1,500 monthly. With our personal runway nearly exhausted, we had an honest discussion and asked ourselves: Do we want to continue without securing a seed round? The answer was yes. We then asked ourselves how we could survive and improve our chances of fundraising later. We decided to stop wasting time chasing investors and focus on gaining traction. This decision boosted our team's morale. Our success was now in our hands, not dependent on funding. By focusing on traction, we implemented key changes that helped us grow tenfold in one year. I'll discuss these changes in the following tips. Tip 2: Improve Your Unit Economics – Be as Effective as You Can to Survive. Tip 2: Improve Your Unit Economics – Be as Effective as You Can to Survive. One of the challenges we faced in becoming profitable was our low take rate. We launched with favorable terms for pet caregivers: after subsidizing transport expenses, our take rate was 18%. This motivated pet caregivers to serve our first customers, but it wasn't enough to achieve profitability quickly with a bootstrapped approach. I wondered: What if we could earn more from every order? What if we could acquire new pet caregivers on more favorable terms for the company? What if existing pet caregivers accepted changes in the transport subsidy? Changing the amount our service providers earned was daunting, but two adjustments helped us double our take rate to 35%: Introduce a cap on transportation coverage. Increase our take rate for new pet caregivers joining the platform. Introduce a cap on transportation coverage. Increase our take rate for new pet caregivers joining the platform. Sometimes, we underestimate the value our business provides to users. It's crucial to constantly ask: What if we could earn more on each unit? Tip 3: Try Bootstrap Marketing Instead of Paid Ads. Tip 3: Try Bootstrap Marketing Instead of Paid Ads. As a startup with a novel concept, you'll likely struggle to win user trust initially. Limited funds for ad testing and the need for quick results often lead to lower conversion rates compared to established competitors. This makes it challenging to achieve positive unit economics from paid channels early on. Our first attempt at SEM didn't yield results, so we explored alternative channels due to budget constraints. Here's what worked for us: 📣 Send Press Releases to the Media Outlets Send Press Releases to the Media Outlets First, we sent press releases to major lifestyle media in our region. Some picked up the story and announced our product launch. Consider researching media outlets relevant to your field and reach out to them. Establishing a public presence for your brand is crucial in the early stages. 🤴 Partner with Industry Experts Partner with Industry Experts Next, we partnered with respected influencers in our field. When they mentioned our business to their audience, we gained both warm leads and valuable social proof. These leads were already confident in our product due to the influencers' endorsement. Who are the key voices in your industry? Is there potential to build connections with them? 👩‍💼 Tap into Corporate Networks Tap into Corporate Networks Our third effective channel was partnerships with enterprises. They promoted our exclusive offers to their employees through internal communications, helping us secure early adopters from their workforce. If your product or service has broad appeal, consider exploring ways to include it in corporate benefits programs. Tip 4: Consider Additional Revenue Streams, Even if They Seem to Diverge From Your Initial Focus. Tip 4: Consider Additional Revenue Streams, Even if They Seem to Diverge From Your Initial Focus. When we launched our pet care platform, we initially only connected pet parents with dog walkers. However, we soon realized that adding dog boarding could provide an additional revenue stream because: Our existing customers were requesting boarding/sitting services. International competitors already offered this product vertical. Our existing customers were requesting boarding/sitting services. International competitors already offered this product vertical. While launching a new product might seem risky or unfocused, it's crucial to differentiate between introducing a completely new offering to a new audience versus a complementary product for your existing customer base. In our case, we were fortunate to launch the dog boarding vertical just before the vacation season when people frequently cancel walking services and search for dog sitters. This decision significantly influenced our successful investment round closure. The boarding vertical generated an additional $24,400 in revenue, which, when annualized, added approximately $280,000 to our pre-money valuation during deal discussions in October (having multiple ~9X to yearly gross revenue). Tip 5: Find an Advisor From a Similar Company That's a Few Steps ahead of Yours. Tip 5: Find an Advisor From a Similar Company That's a Few Steps ahead of Yours. After our launch, we were fortunate to bring on board a mentor/advisor who was a co-founder and CEO of a Round A stage company with a similar on-demand business model - a medical tech company providing house call doctor services. Orders are placed via mobile app and chatbot as we do. His guidance was crucial in several key areas: 💰 Fundraising Fundraising Our advisor tipped us off about a startup competition organized by McKinsey & Company. Among the organizers and jury members were angel investors who had backed his medical company. I believe having him as an advisor significantly boosted our chances during the initial selection stage, where only 12 companies were chosen out of 600+ applicants. The organizers were already familiar with him and understood the on-demand business model, putting us in the right place at the right time. We made it to the finals and, although we didn't clinch the win, we still managed to secure a seed round from an angel syndicate that included jury members from the competition. Consider bringing on board someone with hands-on entrepreneurship experience in a similar market or with a comparable business model. They can provide warm introductions to investors, which can be invaluable. 🎓 Re-use best practices Re-use best practices As a first-time founder, especially a young one like myself, you often lack experience in areas like people management, stakeholder relations, and hiring. Sometimes, you might need specific advice on topics like launching paid ads without failing. Having someone who's already gained this experience can significantly reduce mistakes, saving company funds and ultimately increasing your chances of success. The key is to listen and learn. 🆘 Moral Support and Constant Challenging Moral Support and Constant Challenging Being an early-stage venture founder means constantly managing your emotions. You might swing from "we're the worst company ever, customers will stop using our app" when you receive a negative Trustpilot rating in the morning, to "we're doing quite well" when you deploy a new feature later that day. Things become even more intense when you attract funds, bring investors on board, start hiring employees, and sometimes need to let go of underperformers - it's quite stressful. Moreover, without a boss, it can be hard to adequately assess your own performance - is it poor or good? Having an advisor can help you handle stress as you can transparently discuss all ups and downs. But they can also provide the feedback you need to improve, which is harder to receive when you're working on your own project without someone senior above you. Conclusion Conclusion I believe these five strategies were crucial to bootstrapping our growth and securing seed funding. Every startup's journey is unique, but focusing on traction, optimizing operational efficiency, and leveraging experienced mentors can significantly increase your chances of success. I hope my insights prove helpful to entrepreneurs building early-stage products.

Reflection: Top 5 Tips to Bootstrap From $1.5K to $16K Monthly Revenue and Raise $400K

প্রতিফলন: $1.5K থেকে $16K মাসিক আয় এবং $400K বাড়াতে বুটস্ট্র্যাপ করার শীর্ষ 5 টিপস

Rückblick: Die 5 besten Tipps, um von 1.500 auf 16.000 US-Dollar Monatsumsatz zu kommen und 400.000 US-Dollar einzuwerben

Reflexión: Los 5 mejores consejos para impulsar ingresos mensuales de $1,5000 a $16000 y recaudar $400000

Réflexion : les 5 meilleurs conseils pour passer de 1 500 $ à 16 000 $ de revenus mensuels et récolter 400 000 $

चिंतन: $1.5K से $16K मासिक राजस्व तक बूटस्ट्रैप करने और $400K जुटाने के लिए शीर्ष 5 युक्तियाँ

反省: 月間収益を 1,500 ドルから 16,000 ドルに引き上げ、400,000 ドルを調達するための 5 つのヒント

반영: 월 수익을 1500만 달러에서 16000달러로 부트스트랩하고 40만 달러를 모으는 5가지 팁

Reflexão: 5 dicas principais para aumentar a receita mensal de US$ 1,5 mil a US$ 16 mil e arrecadar US$ 400 mil

Для размышления: 5 лучших советов, как увеличить ежемесячный доход от 1,5 до 16 тысяч долларов и привлечь 400 тысяч долларов

Yansıma: Bootstrap ile Aylık Geliri 1,5 Bin Dolardan 16 Bin Dolara Çıkarmak ve 400 Bin Dolar Artırmak İçin En İyi 5 İpucu

Suy ngẫm: 5 mẹo hàng đầu để khởi động từ doanh thu hàng tháng từ 1,5 nghìn đô la đến 16 nghìn đô la và tăng 400 nghìn đô la

反思：将月收入从 1500 美元提高到 1.6 万美元并筹集 40 万美元的 5 大技巧

Celebrating 10 Years of War Robots and Reflecting From A Technical Perspective

যুদ্ধের রোবটদের 10 বছর উদযাপন করা এবং একটি প্রযুক্তিগত দৃষ্টিকোণ থেকে প্রতিফলিত করা

10 Jahre Kriegsroboter und ein Blick aus technischer Perspektive

Celebrando 10 años de robots de guerra y reflexionando desde una perspectiva técnica

Célébration de 10 ans de robots de guerre et réflexion d'un point de vue technique

युद्ध रोबोट के 10 साल का जश्न और तकनीकी परिप्रेक्ष्य से चिंतन

戦争ロボット10周年を祝い、技術的な観点から振り返る

전쟁 로봇 10주년을 기념하고 기술적 관점에서 성찰

Comemorando 10 anos de robôs de guerra e refletindo de uma perspectiva técnica

Празднование 10-летия боевых роботов и размышления с технической точки зрения

Savaş Robotlarının 10. Yılını Kutlamak ve Teknik Açıdan Düşünmek

Kỷ niệm 10 năm robot chiến tranh và suy ngẫm từ góc độ kỹ thuật

庆祝战争机器人十周年并从技术角度进行反思

Recently I wrote an article where I wanted to compare a popular way of creating object instances with DotNet reflection to another. In that article, I put to see which had better performance. The result saw Activator.CreateInstance emerge as winner in one specific case — but another champion emerges: ConstructorInfo. Activator.CreateInstance head-to-head with Type.InvokeMember In this article, I’ll explain how you can get a ConstructorInfo reference using reflection in DotNet. I’ll also expand upon the benchmarks from the previous article, showing you the code and how the results turned out. Understanding ConstructorInfo From DotNet Reflection In DotNet reflection, we get a powerful set of tools for inspecting assemblies, types, and members at runtime. One of the key components of this reflective capability is the class, which belongs to the namespace. This is where all of the goodies are — ConstructorInfo System.Reflection Even the ones shown in this video that can be misused in the wrong hands: https://youtu.be/3Qstc-ND8Oo?embedable=true allows developers to obtain information about the constructors of a class, including their accessibility (public, private, etc.), parameters, and metadata. But one of the best parts, which we’ll be looking at in more detail, is that it enables the instantiation of objects dynamically at runtime without knowing their types at compile time. ConstructorInfo And the best part? We’re going to see that when we compare it to , it’s way faster. these other DotNet reflection mechanisms for making new instances Finding Constructors with Reflection in DotNet – Getting ConstructorInfo In this section, we’ll look at how we can first get instances so that we can leverage them later for object instantiation: ConstructorInfo Get the instances from types ConstructorInfo Find the right constructor … Profit! Something like that, right? Let’s check these code examples out! Get ConstructorInfo for All Public Constructors To retrieve all public constructors of a class, you can use the method without any parameters by using a instance of a particular type. This method returns an array of objects representing each public constructor defined for the class. GetConstructors Type ConstructorInfo Let’s see it in action in this code example: using System;
using System.Reflection;

public class SampleClass
{
    public SampleClass() { }
    public SampleClass(int i) { }
    protected SampleClass(string s) { }
    private SampleClass(int i, string s) { }
}

Type typeInfo = typeof(SampleClass);
ConstructorInfo[] publicConstructors = typeInfo.GetConstructors();

foreach (var constructor in publicConstructors)
{
    Console.WriteLine(constructor.ToString());
} When we’re thinking about dynamically invoking these things, it’s likely going to be the case that we don’t have the reference to the type though. But if we have the name of the type we’re interested in, we can use the following: Type typeOfInterest = Type.GetType("The.Namespace.Of.Your.Type.TheTypeName"); Get ConstructorInfo Including Private and Protected Constructors To get information about all constructors, regardless of their accessibility level, you can use the method with the parameter. This approach allows you to include non-public constructors in the results: GetConstructors BindingFlags ConstructorInfo[] allConstructors = typeInfo.GetConstructors(BindingFlags.Public | BindingFlags.NonPublic | BindingFlags.Instance);

foreach (var constructor in allConstructors)
{
    Console.WriteLine(constructor.ToString());
} Keep in mind that if you watched the video I linked above, this starts to get into the territory of “Should I be doing this?”. Please strongly consider if you need to be accessing non-public things — Someone likely chose that access modifier for a reason. Get ConstructorInfo Matching a Specific Signature If you’re looking for constructors that match a specific parameter signature, you can use (notice that it’s singular). This takes in binding flags like we saw before as well as an array of types that you want to match. GetConstructorInfo Here’s how you could find constructors that take a single parameter: int // Specify the parameter types of the 
// constructor you are looking for
Type[] paramTypes = new Type[] { typeof(int) };

// Use GetConstructor with the appropriate
// BindingFlags and parameter types
var constructor = typeInfo.GetConstructor(
    BindingFlags.Public | BindingFlags.Instance,
    paramTypes);

if (constructor != null)
{
    Console.WriteLine(constructor);
}
else
{
    Console.WriteLine("No matching constructor found!");
} Note that this method will return null when there’s no match, so ensure you got what you were looking for! Creating Object Instances Using ConstructorInfo Once we have a instance, we can start making object instances. This is what we’ll be benchmarking in the upcoming sections! ConstructorInfo In these examples, assume that we already have a instance called constructorInfo. We’d be getting this instance in any of the ways documented earlier in the article: ConstructorInfo object instance = constructorInfo.Invoke(null); The code above shows instantiating an object with a parameterless constructor. We pass in null for the list of arguments that would need to be provided — because there are none. Take note that the type we get back is an . If we have access to the type at compile, we could cast this instance to that type… But if we have access to the instance at compile time there are probably very few good reasons why you would be doing this in the first place. If you don’t believe me, wait until you see the benchmark results. object If we want to instantiate using a constructor that takes parameters it would look like the following: object instance = constructorInfo.Invoke(new object[] { 42 }); This code example shows a constructor with a single integer parameter defined being invoked with 42 as the single integer argument. ConstructorInfo Performance Benchmarks The moment you’ve all been waiting for! You might enjoy watching the video demonstrating these DotNet reflection benchmarks here: https://youtu.be/Djq7eMI_L-4?embedable=true BenchmarkDotNet Setup for Reflection Performance Much like the previous article, I’ve just added a couple of additional scenarios for the scenarios. I wanted to mention that I added TWO scenarios for each class, and that’s because I wanted to demonstrate the performance if you had to go instantiate AND find the back-to-back. I felt like this variation compared to already having the would be interesting to take note of. ConstructorInfo ConstructorInfo ConstructorInfo Here is the full code: //
// This code was written for the following Dev Leader content:
// https://www.devleader.ca/2024/03/14/activator-createinstance-vs-type-invokemember-a-clear-winner/
// https://www.devleader.ca/2024/03/17/constructorinfo-how-to-make-reflection-in-dotnet-faster-for-instantiation/
// https://youtu.be/Djq7eMI_L-4 
//
using BenchmarkDotNet.Attributes;
using BenchmarkDotNet.Running;

using System.Reflection;

BenchmarkRunner.Run(Assembly.GetExecutingAssembly());
//BenchmarkSwitcher.FromAssembly(Assembly.GetExecutingAssembly()).RunAllJoined();

public class ParameterlessClass
{
}

public class ClassicStringParameterClass
{
    private readonly string _value;

    public ClassicStringParameterClass(string value)
    {
        _value = value;
    }
}

public class PrimaryConstructorStringParameterClass(
    string _value)
{
}

[ShortRunJob]
public class ParameterlessClassBenchmarks
{
    private Type? _type;
    private ConstructorInfo? _constructorInfo;

    [GlobalSetup]
    public void GlobalSetup()
    {
        _type = typeof(ParameterlessClass);
        _constructorInfo = _type.GetConstructor(Type.EmptyTypes);
    }

    [Benchmark]
    public void Constructor()
    {
        var instance = new ParameterlessClass();
    }

    [Benchmark(Baseline = true)]
    public void Activator_Create_Instance()
    {
        var instance = Activator.CreateInstance(_type!);
    }

    [Benchmark]
    public void Type_Invoke_Member()
    {
        var instance = _type!.InvokeMember(
            null,
            BindingFlags.CreateInstance,
            null,
            null,
            null);
    }

    [Benchmark]
    public void Constructor_Info_Invoke()
    {
        var instance = _constructorInfo!.Invoke(null);
    }

    [Benchmark]
    public void Find_Constructor_Info_Then_Invoke()
    {
        var constructorInfo = _type.GetConstructor(Type.EmptyTypes);
        var instance = constructorInfo!.Invoke(null);
    }
}

[ShortRunJob]
public class ClassicStringParameterClassBenchmarks
{
    private Type? _type;
    private ConstructorInfo? _constructorInfo;

    [GlobalSetup]
    public void GlobalSetup()
    {
        _type = typeof(ClassicStringParameterClass);
        _constructorInfo = _type.GetConstructor([typeof(string)]);
    }

    [Benchmark]
    public void Constructor()
    {
        var instance = new ClassicStringParameterClass("Hello World!");
    }

    [Benchmark(Baseline = true)]
    public void Activator_Create_Instance()
    {
        var instance = Activator.CreateInstance(
            _type!,
            new[]
            {
                "Hello World!",
            });
    }

    [Benchmark]
    public void Type_Invoke_Member()
    {
        var instance = _type!
            .InvokeMember(
                null,
                BindingFlags.CreateInstance,
                null,
                null,
                new[]
                {
                    "Hello World!",
                });
    }

    [Benchmark]
    public void Constructor_Info_Invoke()
    {
        var instance = _constructorInfo!.Invoke(new[]
        {
            "Hello World!",
        });
    }

    [Benchmark]
    public void Find_Constructor_Info_Then_Invoke()
    {
        var constructorInfo = _type.GetConstructor([typeof(string)]);
        var instance = constructorInfo!.Invoke(new[]
        {
            "Hello World!",
        });
    }
}

[ShortRunJob]
public class PrimaryConstructorStringParameterClassBenchmarks
{
    private Type? _type;
    private ConstructorInfo? _constructorInfo;

    [GlobalSetup]
    public void GlobalSetup()
    {
        _type = typeof(PrimaryConstructorStringParameterClass);
        _constructorInfo = _type.GetConstructor([typeof(string)]);
    }

    [Benchmark]
    public void Constructor()
    {
        var instance = new PrimaryConstructorStringParameterClass("Hello World!");
    }

    [Benchmark(Baseline = true)]
    public void Activator_Create_Instance()
    {
        var instance = Activator.CreateInstance(
            _type!,
            new[]
            {
                "Hello World!",
            });
    }

    [Benchmark]
    public void Type_Invoke_Member()
    {
        var instance = _type!
            .InvokeMember(
                null,
                BindingFlags.CreateInstance,
                null,
                null,
                new[]
                {
                    "Hello World!",
                });
    }

    [Benchmark]
    public void Constructor_Info_Invoke()
    {
        var instance = _constructorInfo!.Invoke(new[]
        {
            "Hello World!",
        });
    }

    [Benchmark]
    public void Find_Constructor_Info_Then_Invoke()
    {
        var constructorInfo = _type.GetConstructor([typeof(string)]);
        var instance = constructorInfo!.Invoke(new[]
        {
            "Hello World!",
        });
    }
} ConstructorInfo Benchmark Results from BenchmarkDotNet The first set of results will be for the parameterless constructor: In the results above, we already knew that without using reflection, we get the best speed. No brainer here. BenchmarkDotNet says it’s so fast it can’t even measure it properly. But we’ll notice that is technically a smidge faster here than using , even if we already had the instance ahead of time. The results are very close, and I have seen this swing the other way. So overall, these two are very comparable in this situation. Activator.CreateInstance ConstructorInfo What happens if we need to use parameters though? The BenchmarkDotNet results above show that a classic style constructor taking in a single string parameter, is an order of magnitude faster than the other DotNet reflection options. Even if we need to look up the instance first, it’s still almost twice as fast as the other options! ConstructorInfo And of course, I wanted to see if primary constructors were any different in behavior: Based on the results above though, they’re right on par! Wrapping Up ConstructorInfo and Reflection in DotNet As we can see from the BenchmarkDotNet results, leveraging can be very performant! Only in the case where we’re dealing with a public parameterless constructor did it seem to be right on par with . Technically in this run it showed that it was a touch slower, but I’ve run these before and seen the opposite case too. Overall, you’ll want to consider if it makes sense for you to leverage this approach for creating object instances — but certainly don’t opt for reflection if you can easily just call ! ConstructorInfo Activator.CreateInstance new() If you found this useful and you’re looking for more learning opportunities, consider and check out my ! subscribing to my free weekly software engineering newsletter free videos on YouTube

Faster Instantiation With DotNet Reflection Using ConstructorInfo

Reflection in is a powerful feature that allows you to inspect and manipulate code at runtime. If that sounds like some fancy programming magic, it’s because it basically is. And you know what they say — with great power, comes great responsibility. C# Reflection in C# provides us with the ability to examine types, and their members, and invoke methods dynamically, opening up a world of possibilities for creative programs. In this article, I’ll provide you with 4 simple code examples illustrating how reflection works in C#. Example 1: Retrieving Type Information Using Reflection in C# Reflection in C# allows us to examine and manipulate types at runtime. It gives us the ability to retrieve information about classes, interfaces, methods, properties, and more. Understanding how to retrieve types using reflection is important for more complex and creative applications in C#. To retrieve types using reflection, we can use the class from the namespace. The class provides various methods and properties to work with types dynamically. Here’s an example code snippet that demonstrates how to retrieve types using reflection: Type System Type using System;

public class Program
{
    public static void Main()
    {
        // Get the type of a class
        Type carType = typeof(Car);
        Console.WriteLine($"Type Name: {carType.Name}");

        // Get all public methods of a class
        MethodInfo[] methods = carType.GetMethods();
        Console.WriteLine("Methods:");
        foreach (MethodInfo method in methods)
        {
            Console.WriteLine($"- {method.Name}");
        }

        // Get all properties of a class
        PropertyInfo[] properties = carType.GetProperties();
        Console.WriteLine("Properties:");
        foreach (PropertyInfo property in properties)
        {
            Console.WriteLine($"- {property.Name}");
        }
    }
}

public class Car
{
    public string Make { get; set; }
    public string Model { get; set; }

    public void StartEngine()
    {
        Console.WriteLine("Engine started");
    }

    public void StopEngine()
    {
        Console.WriteLine("Engine stopped");
    }
} In the above code, we first use the of the class. Then, we can . In this example, we retrieve the type’s name, all public methods, and all properties. Running this code will output the following: typeof operator to get the type Car access various information about the type Type Name: Car
Methods:
- StartEngine
- StopEngine
Properties:
- Make
- Model Retrieving types using reflection can be useful in a variety of scenarios. For example, you might want to dynamically load and instantiate classes based on user input or configuration data. Reflection also enables you to inspect the structure and behavior of code at runtime, and this opens up some doors when you need to make decisions based on information that you don’t have at compile time. See how this works in this video tutorial: https://youtu.be/7xWaSuPn2I8?embedable=true Example 2: Accessing Non-Public Members Using Reflection in C# We previously saw how we could access things like public methods and properties that are available on types. As mentioned, this can have many helpful use cases but it doesn’t *quite* feel like the scary stories we might have heard about reflection. Let’s change that up a bit. While reflection in C# allows us to look up this information, we can also look up non-public information about types. That’s right. All of that effort that someone put in place to use private/protected and hide details from us on the outside? Gone. We can see everything we want! Muahaha! Oh, right — with great power comes great responsibility. No more evil laughter. Here’s an example code snippet that demonstrates how to access non-public members using reflection: using System;
using System.Reflection;

public class Person
{
    private string _name;

    privateint Age { get; set; }

    private void SayHello()
    {
        Console.WriteLine("Hello!");
    }
}

public class Program
{
    public static void Main()
    {
        Type personType = typeof(Person);

        // Accessing a field using reflection
        FieldInfo nameField = personType.GetField(
            "_name",
            BindingFlags.NonPublic | BindingFlags.Instance);
        Console.WriteLine($"Field Name: {nameField.Name}");

        // Accessing a private property using reflection
        PropertyInfo ageProperty = personType.GetProperty(
            "Age"
            BindingFlags.NonPublic | BindingFlags.Instance);
        Console.WriteLine($"Property Name: {ageProperty.Name}");

        // Accessing a private method using reflection
        MethodInfo sayHelloMethod = personType.GetMethod(
            "SayHello",
            BindingFlags.NonPublic | BindingFlags.Instance);
        Console.WriteLine($"Method Name: {sayHelloMethod.Name}");
    }
} In the above code, we define a class with a , a private property , and a private method . In the method, we obtain the object for the class using . Using reflection, we can access the field, property, and method by specifying their names and using the , , and methods of the type, respectively, to retrieve the corresponding members. Person private field name Age SayHello Main Type Person typeof(Person) GetField GetProperty GetMethod Type But the super important part here? The enum. We can ask, for instance, non-public members. We combine these two categories of members together , which you can : BindingFlags using flag enums learn more about here in this video https://www.youtube.com/watch?v=_yUOrzTCpGU&embedable=true Example 3: Modifying Objects Using Reflection Reflection in C# not only allows us to inspect and retrieve information about objects, but it also gives us the power to modify their data and behavior dynamically at runtime. This means that we can, at runtime, get a member by name (and other conditions) and then make modifications — effectively bypassing a lot of the compile-time checks we normally get. And… we can combine that with the non-public access we just saw! Keep that maniacal evil laughter under control… To illustrate how modifying objects using reflection works, let’s consider a scenario where we have a simple class with properties representing their name and age: Person public class Person
{
    public string Name { get; set; }
    
    // NOTE: this probably makes no sense to ever
    // just have a private property like this here
    // but it's just for demonstration
    private int Age { get; set; }

    public void PrintInfo()
    {
        Console.WriteLine($"{Name} - {Age} years old");
    }
} Now, let’s say we want to change the age of a object dynamically based on some condition. With reflection, we can achieve this by accessing and modifying the property at runtime. Person Age // Create a new instance of the Person class
Person person = new Person()
{
    Name = "Dev Leader",
};

// Get the Type object for the Person class
Type personType = typeof(Person);

// Get the PropertyInfo object for the Age property
PropertyInfo ageProperty = personType.GetProperty(
    "Age",
    BindingFlags.NonPublic | BindingFlags.Instance);

// Set the value of the Age property to 35
ageProperty.SetValue(person, 35);

// Prints "Dev Leader - 35 years old")
person.PrintInfo(); In this code example, we first create an instance of the class. Then, using reflection, we obtain the object for the class. From the object, we retrieve the object for the property, which is private and not accessible to us traditionally from the outside. Finally, we use the method of the object to modify the property of the object to 35. When we ask the instance to print its info, we see the updated value! Person Type Person Type PropertyInfo Age SetValue PropertyInfo Age person While being able to modify objects dynamically can be incredibly powerful, it also comes with some risks and considerations. Modifying objects using reflection can introduce complexity and potential pitfalls (read that as: “will likely break things”), such as breaking encapsulation and violating the intended behavior of the object. It’s important to exercise caution and ensure that the modifications made using reflection align with the design and requirements of the system — this *probably* shouldn’t be your first course of action for many things. Learn more about private access and modification in this video tutorial: https://youtu.be/3Qstc-ND8Oo?embedable=true Example 4: Creating Objects Using Reflection Reflection in C# allows us to dynamically. This means that we can create objects of a certain class without knowing the class name at compile-time. This flexibility can be particularly useful in scenarios where we need to dynamically instantiate objects based on runtime data or configuration. create instances of types To create an object dynamically using reflection, we need to follow a few steps: We need to obtain a Type object that represents the class we want to create an instance of. We can do this by using the method and passing the fully qualified name of the class as a string. Type.GetType() We can use the method to create an instance of the class. This method takes the Type object as a parameter and returns a new instance of the class. We can then cast this instance to the desired type and use it as needed. Activator.CreateInstance() Let’s take a look at an example: string className = "MyNamespace.MyClass";
Type classType = Type.GetType(className);
object instance = Activator.CreateInstance(classType);
MyClass myObject = (MyClass)instance; In the code above, we start by defining the fully qualified name of the class we want to create an instance of ( ). We then obtain the Type object by calling and passing the class name as a string. Next, we use to create a new instance of the class and cast it to the desired type ( in this case). MyNamespace.MyClass Type.GetType() Activator.CreateInstance() MyClass Creating objects dynamically using reflection can be useful in various scenarios, including: . By using reflection, we can dynamically create instances of the plugin classes based on configuration or user input. A plugin system where we want to load different plugins at runtime Dynamic object creation when working with deserialization. For example, if we receive JSON or XML data and need to map it to different classes based on the data content, reflection in C# can help us create the appropriate objects dynamically. Remember to handle exceptions and ensure proper error-checking when working with reflection and dynamically creating objects! It’s easy to forget that reflection opens some funky doors that we really need to be careful with. Showcase of Reflection in C# Reflection in C# is a powerful tool that every C# developer should get familiar with because even if you don’t need to use it regularly, it’s helpful to understand. Reflection allows us to examine and manipulate objects at runtime, providing us with great flexibility and control over code in some creative situations — like plugin loading! By leveraging reflection, we can dynamically load types, query and invoke methods, access properties, and even create new objects. Throughout this article, we explored four code examples that showcased how you can leverage reflection in C#. We discussed how to iterate through members, inspect things that aren’t publicly available, retrieve and set property values dynamically, and dynamically create instances of objects. If you found this useful and you’re looking for more learning opportunities, consider and check out my ! subscribing to my free weekly software engineering newsletter free videos on YouTube Also published . here

4 Simple But Powerful Code Examples of Reflection in C#

Context This article is meant to be a sober reflection on the data lakehouse table format conversation I have had as a participant over the last two years. I've written the following articles over the years on the subject: Table Format Comparison Table Format Comparison: Partitioning Table Format Comparison: Governance Architecture of the Lakehouse Table Formats Apache Iceberg 101 I am writing this article in response to these two pieces: Jacques Nadeau: Overview of state of table formats Kyle Weller: Don’t Worry About Data Lakehouse Features, Trust in Google Search… I work for , who is a contributor to Apache Iceberg and has robust support for Apache Iceberg Data Lakehouses (DDL, DML, Cataloging, Table Optimization) and also can read Delta Lake tables. DISCLOSURE: Dremio, the Data Lakehouse Platform Introduction Choosing the right open-source table format for your data lakehouse is more top of mind than ever as people explore implementing data lakehouses and data lakehouse platforms. With three prominent options in Apache Iceberg, Apache Hudi, and Delta Lake, all vying to be the heart of your lakehouse, it's easy to get lost in the noise of feature sets and performance benchmarks. This blog aims to cut through the fear, uncertainty, and doubt (FUD) surrounding table formats, providing a clear path to understanding what really matters in your selection process. Short Version for Quick Readers All major table formats are mature projects that are constantly improving performance and feature sets. The existence of multiple formats is a boon to the industry, as it fosters a competitive environment that drives improvements across the board. However, when it comes down to choosing a format, it's not just about features and performance. The critical decision should be based on the ecosystem of tools you plan to use and how well they integrate with the format. By focusing on your use cases and testing with your actual workloads, you'll find the table format that best meets your needs. My Journey with Table Formats and Lakehouses Over the last two years, I've immersed myself in the world of table formats and lakehouses, a journey that I plan to continue for the foreseeable future. My entry into this conversation began with an article comparing different table formats. That piece, which became one of my most-viewed writings, initially focused on the various features of these formats. However, as I've updated the article over time, I've noticed the narrowing differences between them, leading to a significant realization. Ecosystem Over Features What truly matters is not the array of features a format possesses but the ecosystem that supports these features and their usability. After all, what's the point of advanced functionality if it's not utilized effectively or is too complex to integrate? The real value lies in how these features are implemented within the ecosystem and how seamlessly they can be adopted into your workflows. Key Takeaways The first major takeaway from my experience is the paramount importance of the ecosystem and usability over the raw feature set. A table format might boast an impressive list of capabilities, but if those features are not accessible or practical for your team's use, their value diminishes. Thus, when evaluating table formats, consider the supporting tools, documentation, community, and ease of integration into your existing systems. Ecosystem and Usability Over Features Performance Considerations: Beyond Benchmarks When delving into the world of table formats, it's easy to get caught up in the numbers game of performance benchmarks. While these metrics offer a snapshot of efficiency under ideal conditions, they seldom provide the full picture needed for informed decision-making. The Limitations of Benchmarks Benchmarks, particularly those in Apache Spark environments, have their place in performance evaluation. However, they often reflect a momentary advantage, influenced by specific configurations and data sets that may not align with everyday usage. The reality is that the performance of a table format is not static; it evolves with each update to its libraries, the processing too, and as users configure the table and tools to suit their unique workloads. True performance evaluation requires a broader lens, one that considers how a table format behaves with the suite of tools you rely on and the nature of your data. Making Informed Choices Choosing a table format based on performance means looking beyond Spark-centric benchmarks. It involves testing how each format manages your specific data types and use cases across the tools and technologies that form the backbone of your data infrastructure. Only by assessing performance in this holistic manner can you ensure that your chosen table format aligns with your operational realities and performance expectations. Understanding the Metric of Open Source Contributors A critical aspect I'd like to clarify from my original blog post is the rationale behind using the number of open-source contributors as a key metric. This choice might have raised some eyebrows, especially considering the complex structure of repository management across many table formats. These projects often distribute their development efforts across multiple repositories, separating the core project—typically written in Java—from implementations in other programming languages like Python, Go, and Rust. Why Focus on Core Contributors? The decision to concentrate on contributors to the core format was deliberate. The core repository is where the most significant decisions regarding the format's evolution are made. It's the heart of the project, determining not just current functionalities but also setting the direction for future developments. The distribution of influence over these decisions is crucial. It reveals whether the evolution of the format is being guided by a diverse group of stakeholders or if it's under the control of a few, potentially leading to a bias in development priorities. The Impact on the Ecosystem While there are undoubtedly many talented contributors working across the various language-specific repositories, their work often focuses on mirroring the functionality established in the core. Although valuable, this does not typically drive the project's overall direction. The core repository's contributor diversity is, therefore, a more accurate indicator of the project's health and its alignment with the broader community's needs. The Importance of Competitive Diversity From a consumer's perspective, the diversity of contributors to the core repository is more than a technicality; it's a safeguard against vendor lock-in, budget inflation, and the potential stagnation of innovation in a controlled market. A table format steered by a community with varied interests ensures that no single entity can dominate the project's direction to the detriment of the community. This competitive diversity fosters an environment where vendors can innovate on equal footing, driving technological advancements and more favorable pricing for end-users. The Value of Contributor Diversity In aiming for a competitive market, the significance of an open format governed by a broad coalition cannot be overstated. The diversity of core repo contributors matters because it ensures that the format remains open, adaptable, and free from monopolistic control. By prioritizing formats with a wide array of contributors, we champion the principles of open innovation and collective progress that are foundational to the open source ethos. Conclusion It's clear that the table format conversation transcends mere technical specifications and performance metrics. The past two years have illuminated the paramount importance of ecosystem compatibility, the tangible benefits of a broad, diverse community of open-source contributors, and the nuanced understanding required to evaluate performance in real-world scenarios. As we navigate the choices between Apache Iceberg, Apache Hudi, and Delta Lake, it becomes evident that the true value lies in fostering an open, competitive market that drives innovation, ensures flexibility, and avoids vendor lock-in. By prioritizing formats that align with our technological ecosystems, supported by a vibrant community, and delivering performance on our workloads with our desired tooling, we can build data infrastructures that are not only robust and efficient but also adaptable and forward-looking. Try the Dremio Lakehouse Platform Today Build a Prototype Data Lakehouse on Your Laptop with This Tutoria Also published . here

Data Lakehouse Table Formats: Considerations, Reflection, and Perspective

This year has been important in so many ways. I’ve been publishing more content than ever. I had a part-time personal assistant. Got access to many wonderful opportunities. I raised my net worth by 60%. I’ve built a great team and moved the product forward at the cybersec SaaS I work at. I almost finished my master’s in management (thesis postponed to the next year). I designed and furnished my first (and hopefully last) apartment. Hell, I even started using separate products for hair and body. And there was a lot of personal change as well. Join me in this short recap if you want to learn where a path like mine can lead you. I’ll share mostly blog and online presence-related details with some professional (engineering), financial, and private information sprinkled on top. Happy to tell more to those interested. Why am I here? I like sharing knowledge, writing, and helping people. I believe that publishing is a vital part of being a professional. Being here, rushing some content out even though it’s not perfect, being vulnerable - that’s a great way to get to know more people and open one’s mind to new points of view. I think one person - Austin Kleon - put this in words much better than me. Check out his short book, and you’ll know everything. is about why generosity trumps genius. It's about getting , about using the network instead of wasting time "networking." It's not self-promotion, it's self-discovery--let others into your process, then let them steal from you. Show Your Work! findable I had a blast putting effort into this blog and other projects this year. Some people enjoyed it as well, as seen in stats from various platforms. Stats Here’s the most interesting numbers i dug out! My blog was visited a total of 43 thousand times: I also got an additional 23k visits to my articles republished on Hackernoon. My LinkedIn content generated 65k impressions, similar to views on the blog. I’ve been posting quite irregularly, as seen in the graph below. Near the end of the year, I started listening to the numbers, resulting in more engagement than ever. Posts mentioning others and with my photos are noticeably more popular. Other numbers: My newsletter got 50 subscribers (up from 24 in July). On Twitter, my posts generated ~300k impressions. I spoke at eight conferences. I was a guest in 5 podcast episodes. I have published 12 blog articles. Best content If you missed some of my articles, here’s a chance to catch up. It’s clear that my most popular content was not opinions, summaries, or anything related to my publishing online. Most viewed articles were software engineering tutorials. A lot of traffic came from Google search, where I ranked quite high for some keywords. I also think I figured out a good way to create thumbnails. 11k views: Extracting and Generating JSON Data with GPTs, LangChain, and Node.js 9K views: How I Effortlessly Create PowerPoint Presentations with ChatGPT and MARP (as a Software Engineer) 2K views: Fine-tuning OpenAI GPT 3.5: Practical example with Python Tip for me for the next year: write more engineering tutorials. Other projects simple message from me here: don’t build a house or buy a new unfinished apartment if you’re not into it. I had to learn interior design from the ground up. Get to know materials, design solutions, too many new technical terms. It interesting, it can be fun, but it is a lot of work. Even though I’m very happy with the outcome, I think I could have spent my time better. Real estate investing / buying a new apartment: really is kicked off 2, shipped none. Excuses? Master thesis and moving apartments. Picking them up again in 2024. One was MeetingFusion: , the other is still unpublished. MF got several sign-ups on the waiting list. Side projects/startups: https://meetingfusion.com : Struggling, will post an update soon. My old AI Startup, Sentimatic : I’ve been able to provide some small-scale but well-paid software engineering services on the side. Consulting : applied for government funding and spent a lot of time. My assistant spent 175 hours on it! The application was of a master’s thesis size. Funding for new AI project Opportunities Writing here gave me more opportunities than ever before. Apart from everything mentioned above, here are some highlights. I’ve been invited a few times to run a workshop about topics I write about by several engineering companies. All my offers were rejected due to the price. I am okay with this, as I only considered it if I was able to provide the absolute best quality of the workshop. I’ve got more interesting job offers than ever. I did not proceed with any, as I’m committed to my current work at Netacea. I’ve been asked to develop a Vue.JS course for a popular course platform. The contract signing is in progress, so hopefully, next year, some people will be able to learn something new using the course. I’ve been invited to many more conferences than I spoke at. Had to choose where to spend my time. Money My work around this blog and anything professional that is not related to Netacea (the cybersec startup I’ve mentioned) only me money. cost Apart from this money pit, I am quite okay at managing my finances, saving it, and investing. I’m also fluent in tax codes. I don’t let money go to waste. I am following the stock market to a limited extent as well. All of this pays dividends and helps me feel more secure in life. I recommend everyone to have basic financial fluency. I won’t get into much detail and exact numbers, but I’ll share some stats to give you some insight into how I think about money and investing. I can share some guidelines for engineers in a separate article. Let me know. My net worth (assets less liabilities) is allocated between cash, real estate, and stocks. I am definitely real estate heavy but I have access to really good advice. Going forward, I’d prefer to have my net worth allocated in some business I run or contribute to in the form of work or investment. I am tracking my savings and investments as a whole by doing a monthly net worth evaluation (it’s a quick exercise at this point). I’ve been doing it since April 2019 and have been able to maintain a good pace of growth, albeit with some ups and downs. Don’t get all excited; the starting point was fairly low! My short advice for friends: use retirement tax-advantaged accounts buy the simplest stock market investments - index funds, S&P500, whole US stock market get a mortgage; it’s a low-interest rate leveraged capital, and overall properties keep up with inflation rates have a safety net with some small cash (as in a bank) pile to bail you out in emergencies Plans My plans regarding this blog and my online presence are still in the making. I want to aim for something that will keep giving me satisfaction while being relevant and impactful. Here are the goals I am thinking about: Launch and grow a newsletter up to at least 1000 subscribers. Shipping one successful SaaS tool on my own. And then grow or sell it. Grow my global (online) and local (at Netacea) influence as an engineering leader. Write one blog post per week. Publish video content and get a reasonable following. Regardless of the details of these, you’ll likely see much more from me next year! Stay tuned. Summary So yeah, a lot happened, and I want it to continue to happen. This year has been another great period of my life which I’m truly grateful for. As for this blog, I want to keep writing and being a part of the global community. After years of learning and working, I finally think like I have something to say. For me, writing has always been this elusive thing that I never quite got to do. I stopped hiding behind perfectionism and started sharing. And many people found it useful, which just makes me happy. I keep learning but this time, I make some of my private notes public. This year, I’ve learned a lot, made mistakes, and made new friends. The future looks exciting. See you there. Have the most wonderful year of your life. Don't forget to follow me on Twitter and subscribe to my blog’s for more tips and insights! @ horosin_ newsletter If you don't have Twitter, you can also follow me on . LinkedIn Also published . here

Reflecting On My 2023: A Year of Growth, Opportunities, and Financial Insights

Introduction This is my consistent coding for the past year 👨🏻‍💻 https://twitter.com/Dhanush_Nehru/status/1741475660978397453?embedable=true Additionally, I discovered that I was one among 0.4% of consistent coders on Leetcode 🧠 https://twitter.com/Dhanush_Nehru/status/1735666289027227690?embedable=true Mastering Consistency How was I so consistent? Here’s how I did it, I just enjoy coding and problem solving, so I thought of doing something better than my 100 Days Of Code Challenge, so I chose to do a 365 Day of Leetcode Challenge. “Choose a job you love, and you will never have to work a day in your life.” — Confucius . I love to solve problems, and my interest and passion for problem-solving made it a habit to face a new problem and solve it without any motivation. “Every man is divine and strong in his real nature. What are weak and evil are his habits, his desires, and thoughts, but not himself.” — Swami Vivekananda. Similar to how we do our daily tasks, problem-solving has become a habit for me without much pressure or inspiration. “First we make our habits, and then our habits make us.” — John Dryden. Similar to how you go to the gym and exercise and maintain your health, it is necessary to train your brain as well as the ability to code. “Programming is a journey, not a destination. The code you write today is not the code you will write tomorrow.” — Unknown. Consistency is an art. It was hard for me to be consistent a few years back, so in order to master consistency as a goal, I did this challenge. It’s not what we do once in a while that shapes our lives. It’s what we do consistently.” — Tony Robbins . Mistakes to Avoid Here are a few mistakes that you can avoid while doing leetcode, We generally force ourselves to get the solution anyway, and once we see the solution, we feel bad about ourselves, and all the negative self-talk comes into play. But, most people do not understand that you must know the basics first before solving that particular problem. How can you expect yourself to play chess well if you don’t know how the coins move? Clear your fundamentals/syntax of whatever programming language, then push yourself to solve the problem. Build your foundation first: You should start valuing your efforts rather than getting the solution. Problem-solving skills are developed in those 30 minutes of fighting with the problem to get the solution. Sometimes, when you are not able to get the solution on the initial days, it is okay to look into the solutions by others, but it should not be a regular practice. Getting to the solution is not everything: Pick up a pen and paper, try to think of all the possible solutions, and focus on building up the solution. Start with the smallest example, try to come up with a solution, and then optimize it with edge case scenarios, etc. Don’t code in your head: There are more than 2000+ problems on Leetcode, and you don’t need to solve all of them. I just coded it as a matter of consistency. However, you need not solve every single problem every day if you want to improve your problem-solving. Concepts are limited. Problems are infinite: Even if I could solve the problem on my own, I always go to the comment section and quickly scan over superior solutions. You may not be aware of how many more effective approaches and viewpoints there are to solving the same issue. Also, I have done many open sources, so it has helped me to view others co’ code in a better way. Read other’s code: Establish a timer for each task; the breakdown is as follows: easy tasks take around 15 minutes, medium tasks take about 30 minutes, and hard tasks take about 45 minutes. Try not to enjoy the moment of finding the answer right away. Always time yourself: No matter how many questions you solve in the contest, show up every time. Once you show up, you have completed the hardest part. Don’t care about ratings: After the contest try to solve the questions without any time limit, if you don’t get it then check other’s solutions understand what they have done, read about that particular topic, and solve it back again using the specific knowledge. Up-solve the contest questions again: I have answered many more questions about my journey in the video below. Do watch, like, to show your support 🙏🏻 subscribe to my channel “The important thing is not to stop questioning. Curiosity has its own reason for existing.” — Albert Einstein. https://www.youtube.com/watch?v=J-hDaEU8smE&embedable=true In the end, it doesn’t matter how smart or dumb or lucky you are, if you are consistent enough you can outwork all the people you think are talented or smarter than you. Also, life is not something that happens on weekends. It is something that happens every single day. A Big Thank You 🙏🏻 If you’ve made it this far, thank you! If you love this post, please give a like as a sort of encouragement and also share this post on social media, which would benefit others. Connect ⬇️ / / / / Twitter Instagram Github Youtube Newsletter Also published . here

Reflecting on My Year of Consistent Leetcode Practice and Mistakes to Avoid

Image by Geralt on Pixabay The trading realm is evolving unprecedentedly, with at the helm of this transformation. The ubiquitous integration of AI in trading is hard to ignore, given that the global AI market is projected to reach a staggering . This growth underscores the increasing importance of AI technologies and the new opportunities and challenges they introduce. AI $407 billion by 2027 As we navigate the pros and cons of AI in trading, it's essential to understand that it's a double-edged sword. On the one hand, AI presents groundbreaking efficiencies and potential profits, but on the other hand, it brings significant cybersecurity concerns in finance. This article offers a balanced, insightful examination of these contrasting aspects. Understanding AI in Trading AI trading strategies represent an innovative leap in the financial sector, blending high-tech algorithms with data analysis to maximize profitability. This enticing fusion of tech and finance paves the way for unprecedented market insights and investment opportunities. Let's delve into AI trading strategies, illuminating the past, present, and potential future. Definition and scope of AI in trading Trading using AI refers to the use of complex algorithms to make trading decisions. These systems analyze vast amounts of data and execute trades at lightning speeds. Automated trading systems have revolutionized modern finance, enabling high-frequency trading and reducing the likelihood of human errors. They offer the potential for greater efficiency and profitability, but their use also raises essential ethical and security questions. Historical context and the evolution of AI in finance The genesis of AI in finance began in the 1980s with rudimentary algorithmic trading. With advancements in technology, AI swiftly progressed. From simple predictive models, it evolved into complex neural networks by the 1990s. The advent of machine learning in the 2000s further propelled AI's capabilities. Today, are integral to finance, encapsulating trading, risk management, and financial planning. sophisticated AI trading strategies Pros and Cons of AI in Trading AI presents a fascinating blend of benefits and challenges. Its impact on the trading industry is transformative, reshaping the landscape in unprecedented ways. Let's uncover AI's intricate pros and cons in trading technology, shedding light on its potential to revolutionize trading as we know it. Pros of AI in trading Here are the pros of using AI trading strategies: Enhanced marketing efficiency AI trading strategies streamline and expedite the trading marketing process. They decipher complex market data, identify patterns, and accurately predict trends. This leads to informed decisions and targeted marketing strategies. Further, automated trading systems reduce costs and increase response times, boosting overall marketing efficiency. Superior data processing and analysis AI in trading revolutionizes , making financial decisions faster and more efficient. Automated trading systems can handle vast amounts of market data in real-time. data processing and analysis They identify subtle patterns and trends that humans could miss. These systems excel at predictive analysis, providing traders with insightful forecasts. This superior analysis capability translates to more precise, data-driven trading decisions, enhancing profitability. Automated decision-making and speed AI-powered trading systems ensure speedy and automated decision-making. They analyze and act on market data at an unrivaled pace, offering a competitive edge. This lightning-fast decision-making ability eliminates the lag associated with human intervention. It enables traders to capitalize on fleeting trading opportunities, which are commonplace in volatile markets. By eliminating human error and emotional trading decisions, AI ensures more strategic, efficient, and profitable trading. Cons of AI in trading Here are the cons of AI in trading: Ethical considerations and biases AI trading systems can inadvertently perpetuate biases, skewing trading decisions based on flawed algorithms or biased data. Ethical considerations arise when these systems prioritize profitability over fairness or transparency. Furthermore, such biases could lead to discriminatory trading practices, amplifying market disparities. This highlights the need for rigorous bias and ethics checks in AI trading strategies. Risk of over-reliance and loss of human oversight An over-reliance on AI in trading could result in a lack of human oversight. This absence of human judgment might exacerbate market risks. AI systems, while efficient, lack the intuition and adaptability inherent in human traders. This makes them susceptible to unexpected market changes. Moreover, an over-reliance could lead to complacency, with traders not fully understanding the underlying trading strategies. A balanced approach between AI and human oversight is crucial for sustainable and responsible trading. Cybersecurity threats and data privacy concerns While highly efficient, AI trading platforms expose financial markets to an increased risk of cyber-attacks. Cybercriminals can exploit weak security measures to manipulate trading algorithms and compromise sensitive data. Additionally, data privacy concerns arise as AI systems process large quantities of personal and financial information. Therefore, implementing in finance is paramount in AI trading to protect the integrity of trading strategies and the privacy of trader's data. robust cybersecurity The Impact of AI on Trading Strategies and Performance AI has revolutionized trading strategies with its accuracy and speed, fostering a new era of automated trading systems. These sophisticated systems are transforming traditional trading, offering innovative strategies and improved performance. Innovative trading strategies enabled by AI harness the power of artificial intelligence to analyze vast data sets, identify trading opportunities, and execute trades at lightning-fast speeds. These strategies can learn from market patterns and trends and adapt their tactics accordingly. AI trading strategies AI's ability to process high volumes of data and make real-time data-driven decisions significantly enhances trading operations' efficiency and profitability. Incorporating AI in trading strategies has ushered in a new era of precision, speed, and effectiveness in financial markets. Performance Analytics Automated trading systems provide robust performance analytics, furnishing traders with critical insights. These systems analyze market data, assessing trade performance with pinpoint precision. The analytics highlight effective strategies and potential areas for improvement. This data-driven method leads to more informed decision-making and improved trading outcomes. Risk management in AI trading AI significantly bolsters risk management in trading. It delivers predictive analytics, enabling traders to foresee potential market downturns and adjust strategies proactively. Enhanced cybersecurity measures in AI trading systems also ensure data integrity and privacy. Due to AI's ability to detect anomalies, cybersecurity threats are identified and mitigated promptly, safeguarding financial transactions and confidential data. AI's role in cybersecurity in finance is crucial, ensuring safe and secure trading operations. AI's Impact on Employment in the Trading Sector AI's integration into the trading sector isn't just transforming strategies—it's revolutionizing the job landscape. As we delve into its impact on employment, we'll explore the delicate balance between job displacement and creation. We'll also discuss the changing skill requirements in this rapidly evolving industry. This exploration will shed light on the increasingly vital role of human expertise amidst the rise of machines. Job displacement vs. job creation AI has led to job displacement in the trading sector. Due to automated trading systems, traditional roles, such as floor traders and stock analysts, are becoming redundant. These systems can execute trades faster and more accurately than human traders, enhancing efficiency and performance. Moreover, AI can analyze vast amounts of financial data in real-time, eliminating the need for human analysis. On the flip side, AI has also stimulated job creation. are emerging. For instance, AI trading strategists analyze AI trading outcomes and refine AI algorithms. There's also a surge in demand for AI compliance officers who ensure AI trading systems adhere to regulatory standards. New roles that require expertise in AI and machine learning AI developers and cybersecurity specialists are also in high demand to build and protect these systems. This indicates that while AI may replace specific jobs, it's also creating new roles for those with specialized skills. Changing skill requirements The shift towards AI trading mandates traders to adapt their skill sets. A strong understanding of AI algorithms, data analysis, and financial modeling becomes crucial. Expertise in programming languages like Python that aid in developing AI strategies is beneficial. Lastly, skills in risk management, understanding AI ethical considerations, and regulatory compliance are indispensable in this increasingly AI-driven trading environment. The Human Element in AI Trading While AI has disrupted trading with its speed, efficiency, and data-crunching prowess, human insight remains essential. This intersection of AI and human expertise creates a dynamic, transformative landscape in trading. The nuanced balance between these two elements unfolds as we delve further, revealing their collective impact on AI trading strategies. Let's explore the enduring relevance of the human element in this AI-dominant environment. Importance of human intuition and management Human intuition in trading continues to hold ground amidst advanced automated trading systems. Experienced traders, with their intuitive understanding, can discern patterns in market behavior that AI might overlook. Furthermore, they can make adaptive decisions based on fluctuating market contexts, something that AI systems may struggle with given the limited predefined parametrics. Therefore, while automated trading systems provide significant benefits, human oversight often brings balance, propelling successful trading strategies. Balancing AI and human decision-making Striking a balance between AI and human decision-making in trading has its unique set of challenges. AI tools excel in processing vast data, making quick decisions, and reducing human errors. On the other hand, they lack the intuitive understanding humans have of market subtleties. Humans excel at making flexible judgments based on experience and context. However, they can be slow and prone to errors. The ideal scenario is a symbiosis—AI offering efficiency and speed, humans providing oversight, nuance, and intuition. Training for tomorrow's AI-enhanced workforce Preparing for an AI-enhanced workforce entails comprehensive training and upskilling initiatives. Companies must foster a continuous learning culture, encouraging employees to embrace AI tools. Training should focus on understanding AI's capabilities, application in their respective roles, and ethical considerations. This readiness will help businesses adapt swiftly to AI's influence, particularly in dynamic sectors like marketing, where data-driven strategies are gaining prominence. Exploring Cybersecurity in Finance Evolving technology comes with increased cybersecurity risks, particularly in finance. While financial institutions harness AI's immense power, they must simultaneously address cybersecurity concerns. The following sections dive deeper into this critical interplay, highlighting the importance of robust security measures in our increasingly digital world. Emerging threats in AI systems AI systems in finance are facing emerging cybersecurity threats. Hackers are exploiting AI's intricate algorithms to launch sophisticated attacks. These threats can compromise data integrity, disrupt trading operations, and tarnish a company's reputation. Additionally, deepfakes, powered by AI, pose a significant identity verification challenge. Consequently, the industry must invest heavily in advanced cybersecurity measures to counter these risks. Strategies for securing AI in trading Here are practical yet helpful strategies to secure your trading journey: Employing multi-factor authentication is crucial to secure AI in trading. This strategy enhances access control, reducing unauthorized entry. Regular audits can help detect anomalies early. Encrypted communication protocols bolster data security during transmission. Continuously updating AI algorithms increases resilience against emerging cyber threats. Privacy Concerns in AI-Driven Trading Privacy concerns occupy a pivotal role in the rapidly evolving realm of AI-driven trading. As financial institutions leverage AI's prowess, they grapple with an unseen adversary—privacy breaches. These intrusions are detrimental to their reputation and potentially risk their financial stability. Now, let's explore this further and see how the finance sector can navigate this precarious cyber landscape. Data collection and usage In AI-driven trading, vast amounts of data are collected relentlessly. This data, encompassing personal details and transaction histories, fuels the predictive capabilities of AI models. However, such extensive data collection can infringe upon your privacy, as sensitive information could fall into the wrong hands. Moreover, concerns about how this data is stored, processed, and shared persist, warranting stringent data governance protocols. The delicate balance between leveraging data for AI and maintaining privacy is a pressing issue in today's digitalized trading world. Legal implications of privacy breaches When privacy breaches occur, the legal fallout can be severe. Financial institutions may face hefty penalties if found to be non-compliant with data protection laws. Additionally, they may suffer substantial reputational damage. Clients could lose trust and opt for other service providers, leading to a loss of business. Therefore, financial entities must adhere strictly to laws and regulations, taking a proactive stance in ensuring the safety and confidentiality of user data. User consent and data rights Consent and data rights form the bedrock of ethical AI trading. Users must knowingly give consent, understanding the extent of data use. Explicitly stating data rights upholds transparency and builds trust. Informed consent is fundamental to adhere to cybersecurity norms. It fuels the relationship between the finance sector and clients, anchoring it in trust. Redefining Markets With AI: Balancing Risks and Rewards AI is redefining trading markets and unlocking potential while introducing new risks. Emphasizing data privacy and cybersecurity while exploiting AI's capabilities can strike a balance. The benefits are significant: AI can identify trading patterns, automate transactions, and improve decision-making. However, the risks, including data breaches and privacy infringements, are concerning and demand attention. In conclusion, as AI revolutionizes trading markets, it will be crucial to balance its rewards and risks. The future holds promise if we navigate responsibly, ushering in an efficient and secure trading era.

Reflecting on the Pros and Cons of AI in Trading: From Ethics to Cybersecurity Issues

During Miami Art Week 2023, the annual culmination of celebration and showcase of contemporary art and technology, Shiseido, a legacy brand in the skincare industry, unveils its latest digital art endeavor, " ." It is an exploration into the realm of generative art and represents a significant advancement in Shiseido’s ongoing journey to blend beauty with cutting-edge technology. "Future Reflections" stands out as a testament to Shiseido's commitment to continuous innovation, drawing on its extensive 150-year Japanese heritage and the sophisticated ingredients of its acclaimed collection. Shiseido ventures beyond traditional beauty, crafting a unique digital narrative that marries the meticulous world of skincare with the boundless potential of modern digital artistry. Future Reflections Future Solution LX Details of the Collection Launch Date: December 7, 2023 at 7:00am ET Available: Future Reflections Collection Process: Enthusiasts can collect pieces from the “Future Reflections” Shiseido leverages the capabilities of the , a leading generative art technology platform.Art Blocks Engine is highly regarded for its ability to enable artists and creators to generate unique, algorithm-driven artworks, ensuring each piece is one-of-a-kind. This technology is pivotal in the world of digital art, as it leverages algorithms to transform artists' visions into dynamic, ever-evolving creations. By adopting this innovative platform, Shiseido is not merely stepping into the realm of digital art; it is embracing a technology that represents the full depth of artistic expression. This partnership with Art Blocks Engine is a powerful statement from Shiseido, blending the precision and science of skincare with the fluidity and unpredictability of generative art. It underscores the brand's commitment to being at the forefront of technological advancement, pushing the boundaries of how beauty and art intersect in the digital age. Art Blocks Engine "Future Reflections" comprises 1,872 unique generative artworks, reflecting the brand’s founding year.The collection is a reimagination of the convergence of science, technology, and beauty, providing unique value to collectors. Brought to life by esteemed artists, including Hannah Yan, Jen Stark, Kaoru Tanaka, and Robert Hodgin, each artist brings a unique perspective and style, utilizing the Art Blocks Engine to create artworks that resonate with Shiseido's ethos. Their collective work is a vibrant testament to the synergy between artistic vision and technological innovation. Yan's intricate patterns, Stark's bold color palettes, Tanaka's subtle elegance, and Hodgin's dynamic interpretations all converge to reflect the diverse and rich tapestry of Shiseido's heritage. This collaboration not only highlights the artists' individual talents but also exemplifies Shiseido's commitment to fostering artistic creativity in harmony with its legacy in beauty and skincare. Artist Highlight Stark, in particular, brings to the collection a vivid intersection of art and technology. Renowned for her captivating visual language that explores organic growth patterns and sacred geometries, Stark's works are a kaleidoscope of color and motion. In "Future Reflections," she brings her signature style of mimetic topographies and fractal designs, creating pieces that are both visually seductive and perceptually engaging. Stark's artistry extends beyond traditional mediums, encompassing interactive projections and distinctive NFTs, which aligns seamlessly with the digital nature of "Future Reflections." Her artworks for the collection are expected to be atmospheric and minimal, yet deeply rooted in naturalist themes, offering viewers an immersive experience into an echoic world of nature-inspired patterns and designs. Stark’s ability to blend the vibrational phases of color and form into a transcendent, curative experience for the viewer aligns perfectly with Shiseido's ethos of beauty and innovation. As a trailblazer in the digital art space, having been recognized as one of the top NFT creatives by Fortune, Stark’s involvement in "Future Reflections" greatly enriches the collection. Shiseido’s Legacy of Innovation Tracing back to its roots over a century and a half ago, Shiseido has consistently been a beacon of innovation and artistic expression. Founded by a visionary Japanese photographer, the brand has woven a rich tapestry of art throughout its history, from establishing a renowned museum in Tokyo to nurturing and collaborating with a host of creative talents. "Future Reflections'' stands as the latest chapter in this storied journey, showcasing the brand's unwavering commitment to pushing boundaries and embracing the new wave of digital artistry. The Convergence of Creativity and Science At the heart of "Future Reflections" lies a celebration of the intricate dance between the generative, code-based art and the meticulous science behind beauty innovation. This collection is a vivid demonstration of Shiseido's philosophy – that true beauty is born at the intersection of art and science. Each piece in the collection is a digital canvas, reflecting the brand's ethos and the transformative qualities of its Future Solution LX line. Web3, Art, and Accessibility "Future Reflections" is accessible to art enthusiasts at no cost. This strategic approach not only democratizes the ownership of digital art but also introduces an element of surprise and delight. Random works within the collection offer exclusive perks, including some of Shiseido’s most sought-after Future Solution LX products, thus seamlessly blending the world of beauty with the allure of digital art. As "Future Reflections" debuts at Miami Art Week, specifically showcased at the NFT Now’s “The Gateway” event, it signifies a pivotal moment for Shiseido in the rapidly evolving digital landscape. This unveiling at such a prominent digital art and NFT-focused event not only marks a significant milestone for Shiseido but also potentially sets a new precedent for the beauty industry as a whole. The collection's presence at "The Gateway," known for spotlighting innovative digital art and Web3 technologies, underscores the blend of art, beauty, and technology, showcasing how Shiseido is leading the way in integrating these realms.

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