Then it was models like Minerva that could actually solve math problems, and the discovery that LLMs were one-shot learners and could write code.

After that, the improvement felt pretty steady, with IMO gold feeling like a watershed moment.

And recently OpenAI's solution to the planar unit distance problem is starting to actually freak me out a bit.

> The 2026 multicenter placebo-controlled trial extending this work enrolled 240 participants with early Alzheimer’s... The intervention group showed slower decline on standard cognitive scales by about 30% versus placebo.

But there's no such study in the references section. Not sure what's going on there but I want to see the data before I believe this.

> Consider two scenarios, first a firm that used to buy a $10,000 HR service from an outside provider now buys that HR service for $10,000 from an AI HR provider. In that case the output still is captured in national accounts and all that disappeared was the wages and workers. In the second version that $10,000 service is now done internally for $10 of tokens. In that scenario GDP has declined by $9,990 despite the same work being done.

Comments URL: https://news.ycombinator.com/item?id=48343960

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Also sending this article to family members so they're aware of this kind of thing.

"Treated models" - it sounds like they're trying really hard to hide the fact that this was all in mice. From the paper:

> Therefore, using a mouse model, this study investigated whether IN administration of hiPSC-NSC-EVs in late middle age can significantly reduce oxidative stress and curb microglia-mediated neuroinflammaging in the hippocampus.

Cool! But please be honest in your press releases.

I'm curious for people with different kinds of work, where are we along this progression? Is it still too dumb, and you would like it to automate more of the boring stuff? Or is it good enough that you wish we could wind the clock back (to when)?.

For the sake of this conversation, let's assume that everyone gets to keep their job; AI just changes what the job is like (though I'm not saying that's what will happen...).

Comments URL: https://news.ycombinator.com/item?id=48270966

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This is a good analogy for AI work displacement. Probably would resonate with some of the college students who boo'ed Eric Schmidt.

I'm also afraid of a world where AI completely replaces human mathematicians, but if we remain collaborators, then that's a world I can still feel excited about.

I also wonder if it is to see whether the remaining employees pick up the extra workload using AI...

https://en.wikipedia.org/wiki/Elo_rating_system

(I hate ads too, but I think I understand the alternative perspective).

That's a really compelling argument against the Turing Test. But in order to build such a machine, you would need an enormous amount of compute to populate the answers. The interesting question is then whether consciousness emerged while doing all that pre-compute.

I'll even take it a step further; most of an LLM's training is next-token prediction on random internet content. A newly-trained LLM will just continue whatever text appears in its context window, like an extremely capable autocomplete. The illusion of an entity that takes turns in conversation and presents a consistent personality is tacked on at the last minute through RLHF. This was the transition from GPT to ChatGPT.

Any positive evidence of LLM consciousness should probably mostly be taken from the model before post-training, where it displays remarkable capabilities but shows no sign of a consistent personality, and likely no signs of self-awareness or self-understanding.