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
Three social forces at the root of FTX's collapse
Hi folks, I shared some thoughts I wrote up about Sam Bankman-Fried. I worry that there's a bit of a social cascade that's leading us to draw the wrong lessons from what happened. I'm not 100% confident in either the facts of what happened -- though, as a former securities litigator in the post 2008 period, I think I have more experience than most -- but I don't see a particularly compelling case for fraud. I also think the focus on a single person's supposed indiscretions, whether true or otherwise, may distract us from deeper systemic problems that FTX's collapse represents.
Very interested in others' thoughts, and especially thoughts on my diagnosis of cultural norms in EA that may have contributed to the problem at FTX. Here's the link:
https://simpleheart.substack.com/p/in-defense-of-sam-bankman-fried
Haha, I wrote a similarly titled article sharing the premise that Sam's actions seem more indicative of a mistake than a fraud: https://forum.effectivealtruism.org/posts/w6aLsNppuwnqccHmC/in-defense-of-sbf
I appreciated the personal notes about SBFs interactions with the animal welfare community. I do think the tribalism EA tribalism element is very real as well. Also appreciate the point about trying to work on something intrinsically motivating - I'm not sure that it's possible for every individual but I do feel like my own intrinsic love of work helps a lot with putting in a lot of time and effort!
Great post.