It is actually possible to rewind LLMs and get the same response, but it's not typically done both as an optimization and as a defense against distillation.

What I've noticed with Claude is that regardless of how I prompt, it will find a few metrics to optimize. Often the metrics it chooses to optimize have zero relation to the actual metrics I want to optimize, which are ones that cannot be measured without more work than Claude can do in a single 1M token context window. It's really hard to stop Claude from optimizing whatever metrics it can find when the actual metrics I want to optimize are not computable.

Instead of shutting down at any discussion of hacking they need to be giving out free credits for hardening. That's going to make it easier to use these tools for hacking, because hacking requires hardening. But the alternative is huge numbers of intrusions, and a slowdown won't fix that, we already have far too much poorly secured stuff, and the models are way too good at exploiting obvious problems.

I also think they need to do a better job of safeguarding end-user privacy. I've seen some things with Claude that make me very concerned it's possible for Claude to hack my local network, then for one of their classifiers to trip, hide the log of how I was hacked from me, but beam all of the information about the hack back to Anthropic to use. And this is totally reasonable, they want to train their models not to hack. Except now details of how they have a foothold on my local network only exist in training data that they may never read but will use to train their models. This is very avoidable but Anthropic has to treat alignment with the end-user's goals as more important than treating the end-user as an adversary.

And the problem isn't just that it says what the software doesn't do, most of the things it claims are in fact meaningless, it's not even clearly describing something the software shouldn't do.

However, the other harm is the recent IDScan hack which leaked 153M people's IDs. And regulation is not a solution here, we don't know how to implement a regulatory regime that will prevent these sorts of privacy disasters. Even if IDScan gets fines which kill the company (and I suspect they will not) it's not enough of a deterrent because no one will pay enough to actually provide proper security here.

> 96 GB Dual NVIDIA RTX PRO 5000 w/ 1000W PSU (non-refundable) +$19,169

Though I don't think there's anything stopping you from trying to stuff an H100 into this machine if you want to BYO.

Actually I think everything you're suggesting is unclear, LG explicitly say they do these things in their ToS. I skimmed their privacy policy, and I'm pretty sure it essentially says they collect all this information and use it for targeted advertising.

I think banning smartphone/computer use before 3rd grade in the classroom sounds like a good idea.

Math is incredibly useful. I think the biggest problem with math is that people don't understand how to apply it, it's not that applications are hard to find. AI actually explains how to apply it very directly. I can never remember how to calculate compound interest, an AI can do it instantly.

Mamdani's banning teachers from using AI to grade assignments.

> So... talking about future capabilities.

No, I'm talking about current capabilities. The studies that prove that current AI is better at grading assignments than humans will take at least a year, if not several.

The question is if we change what assignments teachers give, or if we accept that grading is a task best done by computers. If we change the assignments that teachers give, I don't know what that looks like. Regardless, there's going to be a lot of experimentation going on. Banning AI doesn't help.