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Writes Strange Loop Canon, on the intersection of technology, economics and business — "building models of the world to understand these problem areas and to define them better".

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  Interacting AI agents or algorithms risk pushing each other into a Black-Monday-style cascading failure.

  Their words

  I have said for many years now that the thing I'm worried about with the models is a Black Monday type scenario, where many algorithms work with each other and get us into weird basins of actions.

  How to control an agent swarmstrangeloopcanon.com

Founder of Platformer, a newsletter on tech platforms and the people they affect, and co-host of the Hard Fork podcast at the New York Times.

• Our readingkorrents.com

  Social media platforms across the industry rely on similar video formats, recommendation algorithms, and push notifications to keep users engaged as long as possible.

  Their words

  It's true that Meta's rivals do largely employ the same cocktail of video formats, recommendation algorithms, and push notifications to continuously derail their users' attention.

  platformer.news

Programmer and teacher; writes on software, learning and the web, and makes the Coding Blocks video course.

• Lovedrcmnd.app

  Introduction to Algorithms

  Their words

  Spent endless hours digging through The Book. It’s very well written and organized and was a tremendous help in my CS studies.

  rakhim.org

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  Algorithms to Live By

  Their words

  One of the few books that successfully brings CS into everyday life. We need more books like this. An audiobook is also available, but this one is better on paper.

  rakhim.org

Sequoia Professor of Computer Science at Stanford, co-director of the Stanford Institute for Human-Centered AI, and co-founder and CEO of World Labs.

• Our readingkorrents.com

  AI's bottleneck was never its algorithms but how little data they were fed, which is why the field needed ImageNet rather than another model.

  Their words

  So we conjectured that the lack of data was a huge part of the reason that's the lack of progress in AI. So we took a departure from everybody else who are really focusing only on algorithm and said that we need data. we need data to drive these algorithms.

  youtube.com

Co-CEO of Waymo and a founding member of Google's self-driving car project, which he joined in 2009.

• Our readingkorrents.com

  Models leak and algorithms get copied, but hundreds of millions of audited autonomous miles cannot be replicated — earned trust is the real moat.

  Their words

  Your your models can be leaked, algorithms can be replicated, but hundreds of millions of miles of fully autonomous operations in the real world, backed by evidence-grade evaluation and publicly audited proof, that is much, much more difficult to replicate.

  youtube.com

Chief Scientist at Google DeepMind and Google Research, at Google since 1999, where he co-created MapReduce, Bigtable, TensorFlow and the TPU.

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  Today's models see a thousand times more data than an eighteen-year-old and are no better for it, so far more data-efficient algorithms must be possible.

  Their words

  If you think about our large scale models today, they probably see a thousand times as much data as a human does by the age of 18. Yet, the human by the age of 18 is better in a lot of things and, you know, on par uh with those frontier models that have seen way more data. So could you come up with much more data efficient systems that can learn continuously learn from their own actions?

  Jeff Dean: The 1% Rule for Building in AIyoutube.com

Staff writer at The New Yorker, where he writes the Infinite Scroll column, and author of Filterworld and The Longing for Less.

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  AI models default to generic, lowest-common-denominator output unless a user actively pushes back against them.

  Their words

  If the user doesn't actively push back against the AI model, then they get the generic output, the lowest common acceptable denominator of aesthetics and taste.

  The generic style of AI web designkylechayka.substack.com

AI researcher at OpenAI; built the poker systems Libratus and Pluribus and the Diplomacy agent Cicero, and works on reasoning models.

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  A model can make an existing algorithm a hundred times faster and still cannot invent a better one, however long you give it.

  Their words

  And then I was like, okay, can you come up with an algorithm that is better than the algorithms that I came up with or that anybody else came up with and go ahead and like look at all the published work and synthesize that and then try to come up with something novel and it it's not able to do it. And I can give it a lot of time and it's it's still not able to do it.

  youtube.com

Makes NeetCode, the structured practice list and video walkthroughs people use to prepare for coding interviews; a former Google engineer.

From one piece Tech interviews with NeetCode 2 beliefs, in the piece's order there

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  The data-structures-and-algorithms interview never tested a skill that transfers to the job; what it tested was whether somebody can think.

  Their words

  And DSA interviews were never the best for that. Well, thinking, sure. But in terms of like does that skill translate to what you're doing on the job? It never really translated to that. It was more about evaluating like does somebody think?

  Tech interviews with NeetCodeyoutube.com

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  The right way to hire is not four rounds of data structures and algorithms but work like the job, plus asking a candidate why they made each choice.

  Their words

  I'm not going to spend four interviews going through and asking somebody data structures and algorithm stuff. I just have them do work that might be similar to something I'd give them on the job or even just have a conversation with them. See how they think. Like can they think through trade-offs? I don't even care about what answer they give me to a problem. I care about like what's like why did they say that?

  Tech interviews with NeetCodeyoutube.com

Machine learning engineer and consultant focused on RAG and retrieval systems. He writes about applied AI engineering at jxnl.co and is the author of the instructor library.

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  A recurring AI workflow improves more through ongoing user feedback than by being fully specified upfront.

  Their words

  This is why I like the thread version more than a generic scheduled report. The brief improves as you complain about it.

  jxnl.co

Co-founder of NVIDIA and, as of 2026, its chief executive; the company designs the GPUs most large AI models are trained on.

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  Most advances in AI have come from algorithms rather than raw hardware, which makes China's army of AI researchers its fundamental advantage.

  China

  Their words

  We have got to acknowledge that most of the advanc advances in AI came out of algorithm advances not just the raw hardware. Now if most advances came from algorithms and computer science and programming tell me that their army of AI researchers is not their fundamental advantage.

  Jensen Huang – Will Nvidia’s moat persist?youtube.com

Writer and technology executive; blogs at anildash.com, was CEO of Glitch, and helped build Movable Type and ThinkUp.

• Our readingkorrents.com

  The web is being flooded with coherent, generic, generated text that buries the writing worth reading.

  Their words

  As publishers see the danger from AI bots expand, they retreat to putting more and more content behind either password protection or payment walls or both, leaving the only publicly-accessible content to be AI-generated slop; open resources like research work, scientific analysis, and fair use of content all suffer as a result of people responding to the bad actors, since legitimate uses of open content are no longer possible.

  Endgame for the Open Webanildash.com

Professor of economics at George Mason University and Bartley J. Madden Chair at the Mercatus Center. Co-writes the blog Marginal Revolution and co-authors the textbook Modern Principles of Economics with Tyler Cowen.

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  Feast-or-famine corner outcomes, not modest proportional belt-tightening, are the generic result of price controls.

  Their words

  This paper shows that feast or famine, not modest belt-tightening, is the generic outcome of price controls.

  arxiv.org

Software developer and entrepreneur; co-founder of Heroku, author of The Twelve-Factor App, and a researcher at Ink & Switch.

• Our readingkorrents.com

  What a message-recipient considers important is too idiosyncratic to be captured by generic heuristics like "all receipts go to FYI."

  Their words

  It's a good example of how user preferences are much more subtle than broad heuristics like "all receipts go to FYI."

  Email triage with an embedding-based classifieradamwiggins.com

Software engineer and a long-time technical lead of the Go programming language; author of plan9port and of the research.swtch.com essays.

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  Floating-point printing and parsing algorithms are converging toward an optimal solution.

  Their words

  Given the simplicity and speed of the algorithms in this post and the increasingly small deltas between successive algorithms, perhaps we are nearing an optimal solution.

  research.swtch.com

Software developer and entrepreneur; co-founder of Heroku, author of The Twelve-Factor App, and a researcher at Ink & Switch.

• Our readingkorrents.com

  Social media recommendation algorithms are only partially designed to serve the people using them.

  Their words

  The weak point of social media algorithms for end users is that they are only partially designed to serve us.

  Personal information firehoseadamwiggins.com

Researcher and science writer. Co-founder and editor at Works in Progress magazine, formerly a researcher at Our World in Data, and author of the Scientific Discovery newsletter on science, global health and medical innovation.

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  The Code Breaker

  Their words

  I mistakenly expected this to be a somewhat shallow, generic popular science book, but it was a very thorough account of how CRISPR gene editing emerged from decades of obscure basic research into bacterial immune systems.

  scientificdiscovery.dev

Software engineer at PlanetScale and creator of the vim-go plugin. Writes at arslan.io about Go, tooling, industrial design and books.

• Mixed onrcmnd.app

  The Inner Game of Tennis

  Their words

  I'm mixed on this book. It doesn't really offer actionable exercises, and the Self 1 and Self 2 framing didn't fully convince me.

  arslan.io

Novelist and critic, author of The Body Scout and Metallic Realms; writes the newsletter Counter Craft on fiction craft and the publishing industry.

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  Exercises in Style

  Their words

  Oulipo's co-founder Raymond Queneau has a book to include here called Exercises in Style (trans. by Barbara Wright), which retells an intentionally banal story 99 times.

  countercraft.substack.com

Reinforcement-learning researcher; co-wrote the field's standard textbook, wrote The Bitter Lesson, and shared the 2024 Turing Award.

• Our readingkorrents.com

  Gradient descent finds a solution to the problems a model has seen; nothing in the algorithm makes it pick the one that generalises well.

  Their words

  Well, there's nothing in them which will cause it to generalize. Well, the gradient descent will cause them to find a solution to the problems they've seen. And if there's only one way to solve them, you know, they they'll do it. But there are many ways to solve it. Some which generalize well, some which generalize poorly. There's nothing in them in the algorithms that will cause them to generalize well.

  youtube.com

Member of technical staff at Anthropic. He has led ML/AI teams at Amazon, Alibaba and Lazada, and writes about LLMs, recommender systems and engineering at eugeneyan.com.

• Our readingkorrents.com

  Language models lack catalog-specific knowledge, so their recommendations tend to be generic and biased toward popular items.

  Their words

  language models have world knowledge and can eloquently talk about products, but are unaware of our catalog. Also, their recommendations are generic and suffer from popularity bias.

  eugeneyan.com

Cognitive scientist and long-standing critic of deep learning's claims; writes Marcus on AI and wrote Rebooting AI.

• Our readingkorrents.com

  A language model is no substitute for a well-specified conventional algorithm, so it cannot simply be dropped into a complex problem and trusted.

  AGILLMs

  Their words

  What the Apple paper shows, most fundamentally, regardless of how you define AGI, is that LLMs are no substitute for good well-specified conventional algorithms.

  A knockout blow for LLMs?garymarcus.substack.com

American open-source program lead working on WordPress; a WordPress core contributor and release lead who writes at jeffpaul.com.

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  Generic Office Chair with Upgraded Roller Blade Wheels

  Their words

  Generic Office Chair with Upgraded Roller Blade Wheels — makes rolling around the office much easier.

  jeffpaul.com

Writes The Pragmatic Engineer, the software-engineering newsletter, and wrote The Software Engineer's Guidebook. Formerly an engineering manager at Uber, and at Microsoft/Skype and Skyscanner before that.

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  Cracking the Coding Interview

  Their words

  a classic to prepare for the data structures and algorithms interviews.

  blog.pragmaticengineer.com

Interface designer and researcher, known for the talks Inventing on Principle and Media for Thinking the Unthinkable and for essays on dynamic representations of ideas. Founder of Dynamicland, where he is building a communal computer.

• Lovedrcmnd.app

  Hacker's Delight

  Their words

  A treasure of bit-manipulation algorithms.

  worrydream.com

Software engineer, Wikipedia editor and crypto critic; writes Citation Needed and runs Web3 is Going Just Great.

• Our readingkorrents.com

  The web is being flooded with coherent, generic, generated text that buries the writing worth reading.

  Their words

  What is out there is buried among ever-growing piles of useless content farm material or, increasingly, AI-generated garbage.

  Fighting for our webcitationneeded.news

Medicinal chemist; has written In the Pipeline, the drug-discovery blog, since 2002, and the “Things I Won’t Work With” posts about chemicals that try to kill you.

• Our readingkorrents.com

  How much machine learning can help a biological problem is set by the quality of the data around that problem, not by the algorithms.

  Their words

  I predict (with confidence bordering on arrogance) that whatever machine-learning progress can be made will correlate extremely closely with the quality of the data around any given problem

  AI and Biologyweb.archive.org

Music critic and historian; author of The History of Jazz and Music: A Subversive History. Writes the newsletter The Honest Broker on music and culture.

• Our readingkorrents.com

  Anything that might take a reader off the platform, including a news story or an outside link, is punished by the algorithm.

  Their words

  Anything that might persuade you to leave the platform—a news story, or any outside link—is brutally punished by their algorithms.

  The State of the Culture, 2024honest-broker.com

Programmer; founded comma.ai and tinygrad, and was the first to unlock the iPhone.

From one piece George Hotz: Tiny Corp, Twitter, AI Safety, Self-Driving, GPT, AGI & God | Lex Fridman Podcast #387 2 beliefs, in the piece's order there

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  Anyone who cannot write a full software stack for NVIDIA's generic GPUs has no chance of writing one for their own, more specialised, AI chip.

  Their words

  It’s always harder to write software for more specialized hardware. A GPU is pretty generic. If you can’t write an in Nvidia stack, there’s no way you can write a stack for your chip. My approach with Tinygrad is first write a performant NVIDIA stack.

  youtube.com

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  Recommendation algorithms are not sinister; they simply predict engagement, and what humans engage with most is outrage.

  Their words

  It just predicts what you are likely to re-Tweet and like, and linger on. That’s what all these algorithms do. It’s what Tik-Tok does, it’s what all these recommendation engines do. And it turns out that the thing that you are most likely to interact with is outrage. And that’s a quirk of the human condition.

  youtube.com

Writes jvns.ca, turning "hard and scary" topics — networking, debugging, Linux internals — into plain explanations and hand-drawn comics. Publishes Wizard Zines, illustrated programming zines. Software developer based in Montreal.

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  Cryptopals

  Their words

  Cryptopals – a set of exercises to learn cryptography by breaking it. Very fun.

  jvns.ca

Musician and writer; answers readers' questions weekly at The Red Hand Files, and fronts Nick Cave and the Bad Seeds.

• Our readingkorrents.com

  Songs come out of suffering, and a system that has endured nothing has nothing to make one from.

  Their words

  Songs arise out of suffering, by which I mean they are predicated upon the complex, internal human struggle of creation and, well, as far as I know, algorithms don’t feel. Data doesn’t suffer.

  theredhandfiles.com

Design engineer and illustrator; makes visual essays on programming, anthropology and what language models do to the way people write.

• Our readingkorrents.com

  The web is being flooded with coherent, generic, generated text that buries the writing worth reading.

  Their words

  These new models are poised to flood the web with generic, generated content.

  The Dark Forest and Generative AImaggieappleton.com

Co-founder of the Machine Intelligence Research Institute and the writer who started the modern argument that a sufficiently capable AI would by default kill everyone. Has argued the case since the early 2000s, latterly with the conclusion that it is being lost.

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  You cannot build an AI that has only the capabilities you want, because the algorithms that solve the problems you want generalize to the ones you do not.

  Their words

  The best and easiest-found-by-optimization algorithms for solving problems we want an AI to solve, readily generalize to problems we’d rather the AI not solve; you can’t build a system that only has the capability to drive red cars and not blue cars, because all red-car-driving algorithms generalize to the capability to drive blue cars.

  AGI Ruin: A List of Lethalitiesintelligence.org

Mathematician and maker of the 3Blue1Brown YouTube channel, which explains mathematics through animation. Creator of the open-source Manim animation library and founder of the Summer of Math Exposition.

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  Information Theory, Inference and Learning Algorithms

  Their words

  Information theory has a way of shaping the way you view many things in math, computer science, physics, and beyond. It's one of those fields that takes ideas that you wouldn't think of as being quantifiable or rigorous and makes them so.

  3blue1brown.com