Description du poste
TLDR: Compute will likely be a bottleneck in short-timelines, so I am helping launch Chips for Humanity. Please fill out our survey to inform us of your compute needs if you work in AI safety.
Our Theory of ChangeIf timelines are short (I personally believe they are short...but I also know one should not make sweeping statements in a pseudo corporate type of post), a lot of the most important safety research will happen around "crunchtime" (no better way to define this than: when things start getting Serious), and a lot of it will be done by AI.
That research runs on compute, compute may be scarce by then, and grant money moves slowly. So we will secure compute ahead of time and get it to third party safety researchers quickly.
In More Detail:
I believe third party AI safety research is where tokens and compute will be importation when things get serious and as we approach crunchtime. This research will need tokens from closed source models, for AI labor and experiments, and also compute to run open source models.
If things go well, empirical safety work will speed up about as much as AI R&D does.
If AI can automate AI research, it can likely automate a lot of safety research too, and every automated researcher needs compute to run on.
A lot of the research that will be helpful will likely need compute of its own. Frontier companies could stop offering their models through the API, or, even if they don’t, a lot of the experiments which will be beneficial to run need weights-level access that a frontier lab will not be able to provide access to.
When demand spikes, there may be no compute left to buy, so it has to be secured early. It could become extremely scarce and we should secure it in advance. Compute in this case needs to move faster than grant money usually does. If someone wants to run an experiment today, we want to be able to give them compute to run it quickly.
What we're doing:I'm working with Nicky Pochinkov and Alexa Zelenin on Chips for Humanity, wh