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) by 2028?[1]
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).[1]
This means that, while the co
I was parsing your comment here as saying that the marginal impact of a GiveWell donation was pretty close to GiveDirectly. Here it seems like you don't endorse that interpretation?
I was wrong about that. The next step for GiveWell would be to drop the bar a little bit (e.g. to 3-7x GiveDirectly), rather than drop all the way to GiveDirectly.
https://twitter.com/moskov/status/1455210000855359490
I'm curious why you and many EA's who focus on longtermism don't suggest donating to longtermist cause areas (as examples often focuses on Givewell or ACE charities). It seems like if orgs I respect like Open Phil and long term future fund are giving to longtermist areas, then they think that's among the most important things to fund, which confuses me when I then hear longtermists acting like funding is useless on the margin or that we might as well give to GiveWell charities. It gives me a sense that perhaps there's either some contradiction going on, or... (read more)
I am also curious to understand why you think that earning to give is more impactful than 98%+ of jobs. Also, did you mean 98% of EA-aligned jobs or all jobs?
Thanks for the answer.
Just to make sure I understand #1.
You're saying that if I donated 1000€ to GiveWell right now, my donation would be expected to have 10 times as much impact as a donation to GiveDirectly? However, in the coming years that might change to 5x or 2x?