Recent submissions

Comment · 10 days ago
They're using Copilot, not locally-hosted AI.
Comment · 11 days ago
Next token prediction is still how pre-training works, but that's a relatively small part of the whole training run nowadays. Most of the time is spent in post-training reinforcement learning scenarios, where models are scored based on an evaluation of their ability to complete a task, not whether any specific token correctly predicts a known next token.

Generally, anyone talking about next token prediction being some limiting factor of LLM capability is a good reason to ignore them, as they haven't updated their understanding of LLMs since 2023 or so.

Comment · 25 days ago
So, the AI wrote a NL proof of Navier-Stokes, then incorrectly auto-formalised it to Lean, but still ended up with a verifiable proof of Navier-Stokes? That seems... strange?
Comment · 1 month ago
He described himself a "violently anti-communist", and he saw nuclear war as an eventual necessity in a civilisational conflict between democracy and totalitarianism. If you view a nuclear war as unavoidable, it's easy to conclude that it's better to get it over with sooner rather than later, since a later war will be even more destructive. Especially since von Neumann was active in the 1940s and 50s, when the west had a slight edge in weapons technology, and before the development of the giant H-bombs. He and a few other pro-nuclear scientists argued there was a brief window where the USA could fight and win a nuclear war against the USSR, and they should take it.

While it's easy to dismiss that view in hindsight, it's worth considering that von Neumann had personally witnessed the rise of the Nazis and had to flee along with many of his friends and family. And he had seen that regime defeated only by military strength of the USA. And while the USSR and USA never did end up in a nuclear war, it really was only by a series of miracles that it was avoided. I think most historians of the 20th century would agree we got very, very lucky.

Comment · 1 month ago
Comment · 1 month ago
Ironically this article itself is a model of "life in 2026" based on examples cherry-picked to support the author's viewpoint. I wonder if he as open to being proved wrong about this exact thesis as he encourages his audience to be?
Comment · 1 month ago
Companies could take your discoveries and sell things based on your work before LLMs ever existed. What's changed?
Comment · 1 month ago
I don't think it was ever ignored that knowledge workers would be the first affected by AI. I remember hearing for a long time that lawyers, doctors, accountants, etc. would all be obsoleted by AI.

I do think many (including me) were surprised that software engineering would be the first kind of knowledge work to be successfully automated. We assumed it would be one of the last, because we'd be the industry using AI to replace everyone else, not the industry using AI to replace ourselves.

Comment · 1 month ago
This is completely standard journalistic practice when reporting a quote on something that is currently contentious or unproven. For example, consider the two hypothetical headlines:

Activists decry police murder of protester

Activists decry police "murder" of protester

The first implies that the police murdering the protestor is an established fact. The second makes it clear that it is the activists who used the term "murder" rather than it being a non-contentious fact.

Comment · 1 month ago
Prompting them yes, suggesting potentially fruitful research directions and so on, but the actual research was conducted by hundreds of agents swapping millions of messages and using billions of output tokens over 88 hours. The result being a huge Lean proof: https://github.com/openai/NavierStokesAndEuler. It's not just possible for humans to manually guide such a process in a meaningful way. They can set the direction and attempt to understand the result, but they solution itself must emerge (or not) from the agent swarm.

So yes, the models do seem to be "solving" the problems themselves, but not necessarily in the way we think of mathematical discoveries happening. Academic mathematics has historically been resource constrained: There are a limited number of top-level mathematicians, and they only have so much time and brain power to spend. So when approaching a problem, they are essentially forced to be as efficient as possible, not just searching for a solution, but for one that can be achieved within their cognitive budget. This induces them to develop novel techniques and abstractions, and it is actually those techniques and abstractions that tend to be the valuable part for further research, not the proof itself.

An agentic swarm is like getting a single skilled mathematician, cloning them a hundred times, then locking them in a room with the single objective of solving a problem. No longer constrained by time or brain power, they can approach it differently, using pre-existing techniques to gradually build their way to a solution. This process might not require a single intuitive leap or new discovery, and the solution will not be simple or elegant, but they will probably get there. It is more like a process of intelligently guided search than invention.

Comment · 2 months ago
The current UK government was also elected by democratic vote, so they have a mandate that postdates the referendum.

You can argue their mandate is invalid due to the first-past-the-post system, but in that case the original decision to hold a referendum, and all subsequent governments that negotiated the terms of the EU exit are also invalid, since they all derived from first-past-the-post elections.

Comment · 2 months ago
Comment · 2 months ago
Cormac McCarthy, Blood Meridian especially. His style won't be to everyone's tastes, but you certainly can't describe it as bland.
Comment · 3 months ago
I'm guessing, given they're relying on private financing, the ability to reuse assets from TP1 is the major reason to make it a sequel instead of a new IP.

Personally I liked TP1 a lot for the most part, but I agree that the ending was a horrible misstep. I'm not adverse to metafiction, and this is Gilbert after all, that's kind of his jam, but the sheer nihilism of it all left a horrible taste in the mouth. Ironically, for someone who cares so deeply about game design, it felt like an ending entirely borne of Gilbert and his fellow designers pleasing themselves, instead of thinking about how it would feel for the player.

That said, I'm still glad there's going to be a sequel. Hopefully it has more of what I liked and less of what I didn't.

Comment · 3 months ago
They are not selling at a loss though. The real issue here is that businesses such as Microsoft do not exist to serve a market or make enough money to survive and pay their employees. They exist to increase the value of their owner's shares. This is predicated on an unsustainable model of continual growth, with the expectation that every market they operate in can produce high margins and endless expansion. But demand is not infinite and persistent high margins are the exception, not the norm.

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