other / built
Avalon
“At that time we built Avalon as a research environment to help us learn particular things.”
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other / built
“At that time we built Avalon as a research environment to help us learn particular things.”
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20 transcript-backed records
01 / evaluation
“At that time we built Avalon as a research environment to help us learn particular things.”
02 / belief
“I think one thing that's really interesting about agents actually is that they can be forked.”
03 / belief
“I think we've always intended to build, you know, to try to build the next version of the computer, enable the next version of the computer.”
04 / belief
“Two is I think we did a really good job of creating a high growth environment and an environment where people felt really safe.”
05 / belief
“I think as a philosophy, we believe in releasing things that will be helpful to other people.”
06 / belief
“I think, you know, that's the gap that we see a lot of today is everyone who's trying to build agents to get to the point where it's robust enough to be deployable.”
07 / belief
“I think maybe like a lot of what I'm interested in is constructing a kind of senious.”
08 / belief
“As a scientist, I have learned so much about my fields and a lot of that data is maybe hard to fine tune or on, or maybe hard to like put into pre-training.”
09 / belief
“I think the rate at which we discover new capabilities of existing models and kind of like build hacks on top of them to make them work better is something that has been surprising and awesome.”
10 / belief
“You know, I think when von Neumann made the von Neumann architecture, he was like, the biggest blocker will be like, we need this amount of memory, which is like, I don't remember exactly like 32 kilobytes or something to store programs.”
11 / belief
“We believe that, and we have internally, I think some things that like an interface, for example, that lets me really easily like see what the agent execution is, fork it, try out different things, modify the prompt, modify like the plan that it is making.”
12 / preference
“On the theoretical side, we like really believe in like deeply understanding, like when we actually fine tune on individual examples, like what's going on, when we're pre-training, what's going on, like debugging tools for these agents to understand like what's going on.”
13 / commitment
“They could potentially be our customers and they're trying out all sorts of interesting things. And I think being an investor, looking at the space from the other side of the table, it's just a different hat that I routinely put on.”
14 / preference
“We built Avalon mostly because we couldn't use Minecraft very well to like learn the things we wanted.”
15 / evaluation
“I think the like whole like relay circuits can be thought of as can be mapped to Boolean operators and a set of other like theoretical breakthroughs, which essentially were abstractions.”
16 / preference
“All of them? I think the only successful agents are the ones that do really small things.”
17 / evaluation
“On the market side, recruiting is a market that is endogenously high churn, which means because people start hiring and then we hire the role for them and they stop hiring.”
18 / commitment
“I think if you ask any of my friends, they would tell you that I'm obsessed with agency, like human agency and human potential.”
19 / evaluation
“That was like an improvement. But then we wrote programming languages with these higher levels of abstraction and that allowed a lot more people to do this and much faster.”
20 / preference
“I like to think about team members as creative agents, because most companies, they think of their people as assets and they're very proud of this.”