In recent months, the CEOs of leading AI companies have grown increasingly confident about rapid progress:
* OpenAI's Sam Altman: Shifted from saying in November "the rate of progress continues" to declaring in January "we are now confident we know how to build AGI"
* Anthropic's Dario Amodei: Stated in January "I'm more confident than I've ever been that we're close to powerful capabilities... in the next 2-3 years"
* Google DeepMind's Demis Hassabis: Changed from "as soon as 10 years" in autumn to "probably three to five years away" by January.
What explains the shift? Is it just hype? Or could we really have Artificial General Intelligence (AGI)[1] by 2028?
In this article, I look at what's driven recent progress, estimate how far those drivers can continue, and explain why they're likely to continue for at least four more years.
In particular, while in 2024 progress in LLM chatbots seemed to slow, a new approach started to work: teaching the models to reason using reinforcement learning.
In just a year, this let them surpass human PhDs at answering difficult scientific reasoning questions, and achieve expert-level performance on one-hour coding tasks.
We don't know how capable AGI will become, but extrapolating the recent rate of progress suggests that, by 2028, we could reach AI models with beyond-human reasoning abilities, expert-level knowledge in every domain, and that can autonomously complete multi-week projects, and progress would likely continue from there.
On this set of software engineering & computer use tasks, in 2020 AI was only able to do tasks that would typically take a human expert a couple of seconds. By 2024, that had risen to almost an hour. If the trend continues, by 2028 it'll reach several weeks.
No longer mere chatbots, these 'agent' models might soon satisfy many people's definitions of AGI — roughly, AI systems that match human performance at most knowledge work (see definition in footnote).
This means that, while the compa
I think this is a good point, predictably enough--I touch on it in my comment on C/H/M's original post--but thanks for elaborating on it!
For what it's worth, I would say that historically, it seems to me that the introduction of new goods has significantly mitigated but not overturned the tendency for consumption increases to lower the marginal utility of consumption. So my central guess is (a) that in the event of a growth acceleration (AI-induced or otherwise), the marginal utility of consumption would in fact fall, and more relevantly (b) that most investors anticipating an AI-induced acceleration to their own consumption growth would expect their marginal utility of consumption to fall. So I think this point identifies a weakness in the argument of the paper/post (as originally written; they now caveat it with this point)--a reason why you can't literally infer investors' beliefs about AGI purely from interest rates--but doesn't in isolation refute the point that a low interest rate is evidence that most investors don't anticipate AGI soon.
I feel like a real economist now — I’ve got my first referee report to read the prior literature :)
My gut feeling is that it will increase, because it might lead to an increase in lifespan. That’s so far beyond what we can do now that I think marginal utility goes up.
Depends how much it costs to lengthen life, and how much more the second added century costs than the first, and what people’s discount rates are… but yes, agreed that allowing for increased lifespan is one way the marginal utility of consumption could really rise!