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American historian of Central and Eastern Europe and the Holocaust; author of Bloodlands, On Tyranny and On Freedom, and writer of the newsletter 'Thinking about...'.

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  It is entirely possible to be both morally wrong and geopolitically weak at the same time.

  Their words

  As Trump proves again and again, it is entirely possible to be both morally wrong and geopolitically weak.

  Our Trade War Against Ourselvessnyder.substack.com

Programmer; makes Handmade Hero and teaches Performance-Aware Programming, and argues loudly about how software got slow.

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  The absence of a visible productivity jump from AI proves nothing, because a real ten percent uplift across the board would be impressive and almost invisible from outside.

  Their words

  Then there's another possibility which is that it actually already has worked but just the productivity boost isn't as big as would be obvious if people got 10% more productive. That would still be pretty impressive because it's hard to get a 10% across the board uplift.

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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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  Translating software from one programming language to another is where coding agents already excel, because the existing code is a perfect specification.

  coding agents

  Their words

  Um, and to give you an example of a a a use of a coding agent that works extremely well is you can ask today's models to translate software from one computer language to another very effectively because in that case you actually have a incredibly detailed specification.

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

British open-standards and open-source technologist, formerly of the UK Government Digital Service and the W3C Advisory Committee. Blogs at shkspr.mobi, where he posts a book review most weeks.

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  A City on Mars

  Their words

  They excel at making the dull delightful. There are a lot of big and serious facts to get through, but they have a gift for communicating them simply and eloquently. I just wish they'd've come to a different conclusion.

  shkspr.mobi

Software design writer and chief scientist at Thoughtworks; wrote Refactoring and Patterns of Enterprise Application Architecture.

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  Using an AI tool well is something you have to learn, exactly as it was with object orientation; a bad first impression proves nothing.

  Their words

  one of the things that I took from that was to use this tool well, you have to learn how to use it well, which was also something very true of object orientation.

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Mathematician at UCLA, working mainly in harmonic analysis and partial differential equations. Writes What's new, a long-running blog on their research, open problems and expository notes.

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  AI excels at breadth and human experts at depth, which makes them complementary and makes today's depth-focused way of doing science the wrong shape.

  Their words

  Yeah, so they excel at breadth and humans excel at depth. Um like human experts at least. Yeah, so um I think they're very complementary. Um but our current uh way of doing math and science is focused on depth because that that's where the human uh expertise cuz humans can't do breadth.

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Co-founder and co-chairman of Oaktree Capital Management; author of the Oaktree memos.

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  There is no way to capture a new technology’s upside without being exposed to the losses if the enthusiasm proves excessive.

  Their words

  There can be no way to participate fully in the potential benefits from the new technology without being exposed to the losses that will arise if the enthusiasm and thus investors’ behavior prove to have been excessive.

  Is It a Bubble?oaktreecapital.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.

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  Traditional recommender systems predict user behavior well but cannot be steered via natural language or explain their own reasoning.

  Their words

  They excel at predicting what a user will click or buy next, but can't be steered via natural language or reason on their choices.

  eugeneyan.com

Economics professor at George Mason University and author of The Myth of the Rational Voter, Selfish Reasons to Have More Kids, The Case Against Education and Open Borders. Writes Bet On It.

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  Bad admissions tests survive on herding: no programme wants to be the one asking for a different exam, even a far better one.

  Their words

  So a lot of the problem is mere herding: If every other top engineering program is using the GRE, it’s too weird to require a different test even if the alternative test is a far superior selection mechanism.

  What's Really Wrong With Standardized Testsbetonit.ai

Creator of the Keras deep-learning library and the ARC-AGI benchmark.

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  Scaling the 2019-2023 recipe — same architecture, bigger model, more data — is not enough; further progress depends on new architectural ideas.

  OpenAI

  Their words

  o3's improvement over the GPT series proves that architecture is everything. You couldn't throw more compute at GPT-4 and get these results. Simply scaling up the things we were doing from 2019 to 2023 -- take the same architecture, train a bigger version on more data -- is not enough.

  OpenAI o3 Breakthrough High Score on ARC-AGI-Pubarcprize.org

Writer on a lost civilisation of the Ice Age; wrote Fingerprints of the Gods and presented Ancient Apocalypse. Archaeologists reject the claims, which he disputes at length.

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  That there is no soul is an assumption of science rather than a finding: no experiment has ever shown that the light simply blinks out.

  Their words

  The general view of science, I think, is that we’re accidents of evolution. When we die, the light blinks out. There’s no more of us. There’s no such thing as the soul. But that’s not a proven point. There’s no experiment that proves that’s the case.

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Dutch bootstrapper who builds and runs their internet startups alone — Nomads.com, Remote OK, Hoodmaps, Photo AI and Interior AI — and has written about it at levels.io since 2013. Posts as @levelsio.

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  An idea is only validated when people take out their credit cards and pay for it; signing up proves nothing.

  Their words

  And I check if there’s demand and if people actually sign up and not just sign up, but if people actually pay money. They need to take out their credit cards, pay me money, and then I can see if the idea is validated.

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Co-founder and CEO of Perplexity, an AI answer engine; previously a research scientist at OpenAI and a PhD student at UC Berkeley.

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  Spending most of the compute memorising the world in pre-training is brute force; what we want is a model that reasons the way a student sits an open-book exam.

  Their words

  I think there’s an interesting thought experiment here that, we’ve been spending a lot of compute in the pre-training to acquire general common sense, but that seems brute force and inefficient. What you want is a system that can learn like an open book exam.

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