Alignment researchers, how useful is extra compute for you?

post by Lauro Langosco · 2022-02-19T15:35:31.751Z · LW · GW · 4 comments

Contents

  TLDR
  Introduction
  Main idea
    Potential benefits
    Potential problems
  Form
None
4 comments

TLDR

If you work in AI alignment / safety research, please fill out this form on how useful access to extra compute would be for your research. This should take under 10 minutes, and you don't need to read the rest of this post beforehand—in fact it would be great if you could fill out the form right now.

Introduction

I want to get an idea of how much demand there is for a university-independent organization that manages a compute cluster for academic AI alignment groups and independent researchers. Currently I don’t know anybody who is willing to run such an organization, but if demand is large one could either actively look for people to run such a project or find an existing organization that is willing to take it on.

Main idea

Non-industry AI safety research organizations have a hard time procuring compute. Groups spend many researcher-hours on managing servers on a relatively small scale. Common obstacles are 1) having to deal with university bureaucracy (e.g. regarding hiring, engineer wages, and procurement) and 2) missing out on economies of scale.

Proposal: A university-independent organization that provides access to compute for academic AI alignment research groups as well as independent researchers. Such an organization could pay high wages for its engineers (compared to academic labs) and benefit from economies of scale.

Potential benefits

• Time saved: currently, researchers spend time applying for compute grants, setting up and maintaining servers, and setting up software environments after switching between systems. Easy access to large amounts of compute would avoid most of these time costs.
• Expanded capability to do research: a centralized organization could afford to manage larger compute clusters than those usually used by individual labs. The difference is even larger for independent researchers, who might not have access to large-memory GPUs at all.

Potential problems

• Gatekeeping: just like with other resources such as funding, deciding who gets access can be hard and risks becoming a political problem. OTOH, subject-specific grants are common / accepted within academia. Still, management of access would have to be done carefully.
• Demand: some groups have access to large university clusters and may not need this service. I’m currently uncertain about how large the demand for this is.
• Leadership: even if it were clear that this is a good idea, I don’t know of anyone who is willing to run this project. This seems like a solvable problem though, once we have a clear idea of what the demand is.

Form

If you haven't already, please fill out this form about how much extra compute might accelerate your research (<10 mins).

4 comments

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