Off hand, METR, Forethought, MIT Future Tech, AI Futures Project, AI Index, HAL, and Artificial Analysis all substantially overlap with us in our research focuses and other work, though no two orgs have exactly the same remit. The list of orgs and individual researchers whose work at least partially overlaps with us is far larger.

Personally I think there is a huge amount of descriptive and forecasting research to be done around AI, far more than any one organization can or should take on. I would welcome more "competitors" and I don't want anyone who is interested in our research areas to feel like we have these topics "covered". And I'm confident there are many good critiques to be made of our work and much better analyses to can be done on the questions we've tackled.

Indeed, Anthropic is now running a staff share sale with $6B in buyers lined up. 

insanely cool!

noticed one bug: when you click "reset to defaults" it resets the country choice, not just parameter values (unexpected to me) but more importantly it keeps the UI pointed to the country you chose. Below, Nigeria is highlighted but the parameter values were reset to Chad's defaults.

i doubt it will be very consequential for EA either way. I think what matters is the discursive impact (effect on prevailing social opinion) not total viewers. and people don't care very much about Netflix shows. would be different if it was a movie that got traction.

Note that Anthropic employees can liquidate significant amounts of equity even without an IPO if Anthropic decides to run a major secondary share sale. OpenAI employees recently sold $6.6 billion in shares. 

GPT-5 is an enormous step up from GPT-4 in capabilities, to be sure, setting aside training compute.

If they time the subsidized user push right their model of expected annual recurring revenue is $10B/y and $11B in 2025 is possible

OpenAI says they already hit $10B annual recurring revenue, for what it's worth. They don't provide a breakdown but they do say this excludes major one-time deals and the licensing fees Microsoft pays to use OpenAI models in its own products (this is a substantial source of revenue, but I'm guessing OpenAI excludes this to avoid being accused of using wash transactions to juice their numbers: they in turn pay Microsoft for the servers to train and run their models).

Based on OpenAI only having 3M Team+Enterprise+Edu subscribers in May, I don't think this $10B/year rate was achieved via $1 Team trial subscriptions.

I think you are reading too much into the growth rate of free users. OpenAI has made a recent push into acquiring lots of new free users, e.g. by making signups easier and putting ChatGPT on WhatsApp, which makes their conversion rate look worse. But their revenue, which comes from paid subscribers and API usage, is still growing at a very healthy and relatively steady rate (3x from $3.4B last year, and 10x from $1B in August 2023) and my guess is that it will continue to grow rapidly.

(comment originally posted on Twitter, Cheryl's response here)

I'll flag that estimating firm-level training compute with [Epoch AI's] notable models dataset will produce big underestimates. E.g. with your methodology, OpenAI spent ~4e25 FLOP on training and 1.3e25 FLOP on research in 2023 and 2024. the latter would cost ~$30 million. but we know OpenAI spent at least $1 billion on research in 2024! (also note they spent $1 billion on research compute after amortizing this cost with an undisclosed schedule).

But I don't have a great sense of how sensitive your results are to this issue.

(this raises other questions: what did OpenAI spend $3 billion in training compute on in 2024? that's enough for 50 GPT-4 sized models. Maybe my cost accounting is quite different from OpenAI's. A lot of that "training" compute might really be more experimental)