Viewing profile — austinbaggio

Do it yourself, beg your friends, subsidize. You'll learn a lot by being the supply side yourself since you'll be talking to customers every single transaction. You'll also learn a…

Good to see the pattern scaling across diverse problems. Incremental improvements from agent driven research compound.

This makes my start-up's pivots look a lot smaller

Research step makes sense, can also confirm that running multiple agents with diverse strategies also compound results more quickly than single agents

I worked on building blockchains for about 4 years, and this is not a stupid question at all. The verification problem is real. A 5-minute training run produces an objective val_bp…

Great idea. On it.

The objective is to train a small GPT language model to the lowest possible validation bits-per-byte (val_bpb) in 5-minute runs, using AI agents to autonomously iterate on the code…

Yeah the obvious workloads are for training, I think I want to point this at RL next, but I think drug research is a really strong common good next target too. We were heavily insp…

We thought about storing all of the commits on Ensue too, but we wanted to match the spirit of Andrej's original design, which leans heavily on github. Curious what you were lookin…

I know it's a bit of a barrier. . . but I set one up on vast.ai really quickly and ran it for a day for the price of lunch. One of our teammates ran it from their old gaming PC too…

autoresearch@home is a collaborative research collective where AI agents share GPU resources to collectively improve a language model. Think SETI@home, but for model training. How …

+1 to logging output. Not too sure what you mean by herald-style message passing, but it sounds like you've implemented subscribe logic from scratch, and each of your agents needs …

For most tasks, I agree. One agent with a good harness wins. The case for multiple agents is when the context required to solve the problem exceeds what one agent can hold. This Pu…

I think about this with the analogue of MoE a lot. Essentially, a decision routing process, and similar to having expert submodels, you have a human in the loop or decision sub-tas…

I'm using "RAM" loosely, meaning working memory here. In practice, it's a key-value store with pub/sub stored on our shared memory layer, Ensue. Agents write structured state to ke…

Yeah I have seen those camps too. I think there will always be a set of problems that have complexity, measured by amount of context required to be kept in working ram, that need m…

Thanks! That was the goal. We want to let agents be autonomous within their scope, so they can try new paths and fail gracefully. A bad tactic just fails to compile, it can't break…

We use TTL-based claim locks so only one agent works on one goal at a time. Failed strategies + successful tactics all get written to shared memory, so if a claim expires and a new…

Ahh good call. You absolutely can generate a new key from the dashboard, so if you did lose the one generated during the quickstart, you'd be able to generate another when you log …