If Claude Fable stops helping you, you'll never know

This immediately made me think of the Sophons silently manipulating the sensors of particle accelerators to prevent humanity from developing advanced knowledge of particle physics.

Cloud providers - at first smaller ones, then the hyperscalers - will follow suit, completely closing sales to anyone but the labs and demanding payment in equity/direct decision-making power rather than cash. There's no particular reason why the inference/training split has to be 80/20, and no amount of willingness to pay can help you in an event that turns your money worthless.

Training a new model from scratch takes serious resources. Post-training/fine-tuning an existing model, dramatically less. The knowledge for the process was esoteric two years ago, now you can ask a current model (one of several) to walk you through it, while building the tools to do it as you go. Several of my recent weekend projects have been exactly that sort of thing, just so I understand it better. "Let's make a LoRA", "let's generate a corpus of training data for fine-tuning a model for X task", "how can I put my face in a text-to-image model?" stuff like that. All of this is do-able on kinda modest local hardware (a couple of old GPUs or a Strix Halo or DGX Spark or big Mac Studio), or for a few bucks or a few hundred bucks or a few thousand bucks of cloud compute, depending on scale.

Scale that up to corporate or startup scale, with the money that's been flowing into AI for the past couple/few years, and it's obviously there's going to be a lot of competition just as the top model makers need to start ringing the cash register. That's a lot of opportunities for people to look at their ballooning Claude usage costs and find other ways to do the same thing for drastically less money. $100/month or $200/month is a no-brainer for Claude Code with probably the best model for coding, but they're pushing more users to usage-based billing which becomes cost-prohibitive real fast.

So, they desperately need to continue to be among the only ways to solve the hardest problems, and they need the alternatives to cost a similar amount. They can count on OpenAI and Google to ratchet up prices, too. They probably can't count on everybody, especially the vendors in China with different economics, to do it. And, they can't count on companies to look at their own usage and not ask, "Can we train a smaller specialist model that does this one thing we're using the Anthropic API most heavily for?"

I'm hoping they just mean stuff like using Claude for distillation by e.g. Chinese model makers, and not "how do I fine-tune Gemma 4 to write more like me?" or whatever.

Dig that moat son, we would want to automate our job away.

If so, it's possible to built great user interfaces in Chatbots and more companies/people can have amazing agentic development workflows! We don't have to live in a world where only the market leader has the most enjoyable model.

Competitor companies being nerfed?

Non Americans getting worse code?

Punishing and rewarding users to maximize engagement, like online games do affecting victories through matchmaking?

Everything the large LLM providers do now, I view it through the lens of "how does this impact their IPO".

For now, I'm really not happy about this limited rollout and then turning off. That's probably the most egregious thing I think Anthropic has done recently

You should be able to know if your problem was solvable by using your own expertise and judgement, no? If you're relying on LLMs as a substitute for those, I wouldn't expect great results.

now I understand distillation is much more important thank I thought

1. Detecting if employees from competing companies are using it and sabatoge their work, even not LLM-training related

2. Direct users to outcomes that would justify higher compute spend. Deliberately coding a project to 95% completion but designed to be losing a critical step right before one's weekly rate limit is expended

3. Reduce the quality of writing when a person is writing an essay where the argument is against the interests of the model company, or steering the user using the model for brainstorming in a direction which causes them to waste time or abandon their train of reasoning

etc. etc. The possibilities are enormous. Many people use AI daily for their job, personal advice, companionship. A model company that steers the behavior of the model towards a deliberate outcome could develop a controlling interest in human behavior and productivity at large, even with subtle influence would compound enormously over its millions of users.

Any attempt to arrest a senior officer of OCP results in shutdown.

That's always been the case with corporate LLMs.

What an interesting thing to call out as a threat. Hmm.

I don't think it's true today. It's like when schools mention "average class size", where that average is dominated by classes with like 2 students instead of classes with 100.

Much more honest would be the percentage of developers who previously used their models for the model development tasks they're targeting, but it actually looks like they're saying 100% of them are affected based on the language around it "always having been prohibited".

So awful.

They legally can steal it all and now you can't use the product of this theft to improve your own systems.

And, they can say that for anybody at any time, and you'll never know why, and there's no way to prove it.

Everyone needs a flight data recorder to prove... "here's what I was actually doing and why it was not distillation." And now you're having to prove your innocence instead of them having to prove you're guilty, and really at the end of the day, it's just the model being stupid that they're protecting themselves from.

Theres no ethical framework. No axioms. Its a mixture of legal, political, and public-facing 'rules'. And what are the rules? Youre not permitted to know.

"We reserve the right to lie about the models we provide, silently downgrade you, and give you blatant misinformation cause you triggered our unstated rules... BUT we'll still use your token budget with lots of thinking and waste your money."

No, folks. Seriously, local LLMs are where its at. You can run the model YOU want, on your hardware, with no data exfiltration.

And with tools like Krasis that can synthesize nvidia ram and system ram as unified-ish memory, makes doing Local LLMs absolutely foable, now!