sobiolite

Do you review and understand every byte of machine code being generated by your compiler? Do you understand all the implications of how it could interact with the underlying hardware, pipelining and prediction, etc?

Maybe you do, but most of our industry doesn't and hasn't for decades. Isn't this just the next step up the ladder of abstraction?

In the old days? Reading the www-style W3C mailing list was the best way to learn about proposed features and people like Dave Hyatt, David Baron, Anne van Kesteren, Eric Mayer, Paul Irish and many more I've forgotten about used to blog about upcoming things. Sites like A List Apart and Smashing Magazine were also good resources for articles about established features and interesting techniques.

Good luck, I guess, but in 2026 "CSS Tricks" seems about as relevant as "PostScript Tricks" or "Office Open XML Tricks". Human manipulation of CSS is going to be, at best, a hobby for a few dedicated tinkerers. And I say that as someone who invested a significant amount of the last 20 years getting good at CSS.

A lot depends on what the models were specifically trained for using reinforcement learning. Modern models are generally OK and everything, but they're only really good at the things they have extensive RL for.

New Constructs takes a similar position on all mega IPOs. Sometimes they're right, but sometimes they're wrong. For example, they insisted Uber's IPO valuation was too high due to unsustainable losses, hidden liabilities, etc. Initially they were proved right when the post-IPO stock price plummeted, but in the long term Uber has performed well, become very profitable, and now trades well above its IPO valuation.

I'm expecting a similar story to play out with Anthropic: The stock price will come down significantly after the IPO, resulting in lots of headlines about the AI bubble bursting. But in the long term it'll climb up again and investors who stick around will do very well.

I feel like if you need to make a public blog post about how you're done with the internet, you're not done with the internet.

I don't really understand the IP protection angle here: These browser ports are no more or less illegal that hosting a RAM file for use on an emulator, or pirated software in general. And sites hosting them are no harder or easier to shut down than existing piracy sites.

What's more interesting is the new ability to easily create ports of old games that let you play old games legally: Bringing your copy of the original's data files and playing on a modernised engine with high-resolution, unlocked FPS, bugfixes, etc. In the past couple of months, I've seen a bunch of vibe-coded ports of DOS games for which the source code was lost.

Computers can make decisions: Almost everyone reading this will have a implemented an if-else statement or equivalent control flow. That is a decision made by a computer on data it receives at runtime. You can argue that it's different, because we fully understand the logic of such a statement, whereas LLMs are closer to a black-box. But at Turing observed, in practice we are frequently surprised by the output of complex algorithms, even those we have authored ourselves. The more difficult the task, the more complex the algorithm we need to achieve it, and the more unexpected behaviour can emerge from it. In that way, LLMs are just the latest, highest point on a rising line of algorithmic capability and complexity.

We can (and should) try to improve AI safety and alignment, but perfect safety is probably impossible without losing the capabilities that make AI unique. Black-and-white positions that insist anyone creating or using an AI is responsible for anything it does wrong under any circumstances are also unrealistic. AI is a general purpose technology, and we have always accepted that it is not practical for suppliers to envisage and constrain every downstream use: Car manufacturers cannot prevent every instance of mechanical failure, nor can they stop cars being used in crime.

That's fundamental to how _any_ technology works. If the bar for use is "can never go wrong ever", then you need to throw away every human invention ever made.

Both articles are practically useless. All they do is reprint statements from either side, neither of which is concrete about the specifics of what supposedly happened. I.e. OpenAI says they "confirmed that these individuals mishandled sensitive information outside established company procedures".

What sensitive information? Mishandled how? Which company procedures? It's all utterly vague and impossible for an outsider to form any opinion on. All people can do is guess and apply their own pre-existing opinions. E.g. if you don't like OpenAI, you assume they're lying. Who's to say they're not? There's no solid evidence provided either way.

What I really want is journalists who do the legwork to get to the bottom of stories like this: Establish sources inside the company and use them to report on the real details of what's happened, triangulating multiple accounts and leaked documents to back-up or invalidate either side's claims. Without any of that, these stories are just gossip.

Are you comparing Opus 5.5 with GPT-6 Sol or GPT-6.1 Sol? Because they are different models.

Let's face it, it's not that remarkable. A substantial proportion of Hacker News commentary has always been people only reading the submission title, then arguing with each other based on what they imagine the article might say.

> Fact is, vibe-coded projects devolve over time into an unmaintainable mess.

We've had strong coding agents for less than a year. Anyone making such a definitive statement about how vibe-coded projects progress over time is basing it on guesswork, not evidence.

> To me if you ask to a 10 years old kid and give him a PC with Microsoft Paint on it it will you will have a much better result than any AI-generated option in the post.

FWIW, statements like this are so patently ridiculous that it actually hurts your cause.

Would this legal framework cut both ways? When AI companies use AI to make and publish mathematical discoveries, would they be able to legally prevent professional mathematicians from using them?