nayroclade
nayroclade on Hacker News
They're using Copilot, not locally-hosted AI.
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.
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?
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.
What Ed-Tech companies? This article isn't talking about Ed-Tech companies. Axel Rauschmayer isn't an Ed-Tech company. He's an individual author who wrote books about JavaScript, the language. He wasn't pushing these "unnecessary solutions", he was helping developers understand JavaScript, exactly the thing you say is necessary. Josh W. Comeau isn't an Ed-Tech company, he's an individual who writes content about new CSS features like Anchor Positioning[1]. What do educators like this have to do with 1+ GB RAM frontends?
[1] https://www.joshwcomeau.com/css/anchor-positioning/
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?
Companies could take your discoveries and sell things based on your work before LLMs ever existed. What's changed?
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.
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.
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.
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.
Cormac McCarthy, Blood Meridian especially. His style won't be to everyone's tastes, but you certainly can't describe it as bland.
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.
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.
That wasn't what this study was investigating.
Some of the other examples you could maybe say are just poor industrial design or bad execution of a potentially workable idea, but the Intel MBP thermal debacle was definitely the most egregious example of Apple blindly pursuing form-over-function. They set a goal for ultra-slim laptop forms that the components they were using simply could never achieve. It would have been obvious from prototyping that temperature was a major problem, but whatever decision making process they had in place at the time overrode it. The best you can say is they seemed to have learned from their mistake.
> It's since november 2025, the so called "inflection point", that I'm still wondering for who coding agents become "really good".
The answer is "for lots of people, but not you".
You're doing a vague impression of being fair and even-handed, arguing for non-polarization, but underlying everything you're saying is an obvious attitude of poralizing superiority: That _your_ personal experience with AI is the real truth. That _your_ codebase is more intricate and more challenging than what other people are doing. That everyone else is being led by a "marketing hype train".
Dependency versions are also locked for npm projects via package-lock.json, and this has been the default behaviour for years. The version ranges specified in package.json don't mean you just pick up the latest whenever you run npm install. Unless you delete package-lock.json or run "npm update", you and everyone else gets the exact same dependency tree each time. So it is just as reproducible as a Maven build in that sense.
The point is that "part" of the appreciation appears here to be
all of the appreciation.
Yes, the context of who created a piece of art will have an affect on how you interpret it. But if the question of who/what created it can literally flip your interpretation between "it's genius" and "it's garbage", then that's the only thing you care about. All the actual characteristics of the thing itself are irrelevant. And if literally the only thing that matters about art is who created it, what exactly is the point of art?
Lol, this is SOP for the British state. There has been a revolving door between the civil service and the private sector for decades. You cannot conceive of how many billions have been wasted on "consultancy" contracts with the big four, IT projects that lasted for years and delivered nothing, etc.
For pre-training, yes. But for post-training you need high-quality labelled datasets for reinforcement learning. So far AI has been most successful in coding, because you can translate the usage into such datasets, and thus produce a virtuous cycle: More usage produces more data, which produces better models, which drives more usage.
The question is whether this same model can successfully be applied in disciplines like medicine, law, engineering, etc.
It's hilarious to me to see the same kind of engineer, who throughout my career have constantly bitched and moaned about team meetings, agile ceremonies, issue trackers, backlogs, slack, emails, design reviews, and anything else that disrupted the hours of coding "flow state" they claimed as their most essential and sacred activity to be protected at all costs, suddenly, and with no hint of shame, start preaching about about the vital importance of collaborative activities and the apparent inconsequence of code and coding, the moment a machine was able to do the latter faster than them. I mean, they're not even wrong, but the nakedly hypocritical attitude of people who, until a year ago, were the most antisocial and least collaborative members of any team they were on is still extraordinary.
It seems like this policy will help them win at contributor poker in the short term, but lose in the end. The next generation of developers will, for better or worse, grow up using AI assistance to write their code, but none of them will ever become a Zig contributor.
I think both got taken by surprise. Last year the talk was that AI was a bubble, demand was soft, pilots projects were failing, etc. Model providers still believed, but thought they had a long ramp up period to build out their own datacenters. Then in late Autumn/Winter, something happened. Model capability reached a threshold and demand exploded, then just kept exploding. Model firms are scrambling to find any compute capacity they can, which means striking any deals problem with hyper scalers. So question is whether model providers can get enough compute without having to effectively sell themselves to hyper scalers.
Bear in mind, in the same survey this article is talking about, nothing and nobody had an overall positive rating amongst those polled. So yeah, AI is unpopular, but it's just one more thing that people hate amongst a broader cultural movement of generalised hate.
I think this touch-only idea would be more viable if we had far better haptic feedback from screens. All the fancy gestures and fluidic UI don't help when your only means of interaction is pushing against an unresponsive pane of glass. Maybe something better just isn't possible, but I'd love to see Apple push things forward in this area.
> Silicon Valley owes a moral debt to the country that made its rise possible
I would agree with that, but its debt is to the people of that country, not their current government. But instead, Palantir conspires to surveil and repress those people at the bidding of an elite, anti-democratic minority.
And would the leaders of Palantir still argue it had a moral debt to serve the government if it was a left-wing one, engaged in a process of wealth redistribution? No, they wouldn't. This supposed moral ideology is a facile sham.
Are you kidding? Check out the index page for this "blog":
https://smarterarticles.co.uk/A new long-form article, published every day, like clockwork, since the 1st of June 2025. All about AI, all attributed to the same author.
Congrats to him on finally getting this slop to the top of HN, I guess. Shame on everybody here for upvoting it.