“A final thing that we're releasing there is around 450,000 human judgments about ambiguity and question quality, which we used In the process of cleaning these evaluations”
quote is from the automated transcript, cleaned for reading:
filler sounds and stutters are removed, nothing is rephrased. names can be misheard
(the analysis reads context, assessments check outside sources). how →
More from Josh Albrecht
Insight
Albrecht: LLM emergence is an artifact of non-linear evaluation metrics
“This emergent behavior that you're seeing, Is not really emergent behavior, but is really a function of the evaluation metrics that we're using.”
Josh AlbrechtJun 25, 2024▶ 55:56State of the Art: Training 70B LLMs on 10,000 H100 clusters
Opinion
Albrecht: Training on AWS prevents diagnosing low-level hardware errors
“And if we're just using, you know, AWS or some other cloud provider, These errors are still going to be there, and you're gonna have no way to know and no way to debug this and no way to diagnose what's going wrong.”
Josh AlbrechtJun 25, 2024▶ 19:49State of the Art: Training 70B LLMs on 10,000 H100 clusters
AssertionSupported
Albrecht: Benchmark performance differences vanish once ambiguous questions are cleaned
“The main takeaway from any of the, like, actual performance is like, once you fix these ambiguous examples, a lot of these benchmarks are really saturated. Like, I think it's important to look at like, you know, like when you're talking about performance on NL…”
Josh AlbrechtJun 25, 2024▶ 1:01:43State of the Art: Training 70B LLMs on 10,000 H100 clusters
AssertionSupported
Albrecht: AgentBench paper's appendix examples are actually incorrect solutions
“Like we were looking at the agent bench paper, I think just last week for our paper club. And one of the things that we noticed is that actually like both of the examples in the appendix that are given as like traces where it got it right. This is actually not…”
Josh AlbrechtJun 25, 2024▶ 1:06:05State of the Art: Training 70B LLMs on 10,000 H100 clusters
Insight
Albrecht: Optimizing for competitive coding benchmarks does not create useful programmers
“Like, we do a lot of code generation, but we don't really do a lot on, like, code competition problems for the very, very hard ones, so that you can go very far down that route and make something like really good at those problems, but not actually that useful…”
Josh AlbrechtJun 25, 2024▶ 1:13:00State of the Art: Training 70B LLMs on 10,000 H100 clusters
Disclosure
Albrecht: Imbue avoids Kubernetes to keep cluster infrastructure simple to debug
“Less layers of infrastructure, less layers of abstraction, make it a lot easier to work with. Like we don't use Kubernetes, for example, I would just directly launch these things and it's just been much easier to debug this way.”
Josh AlbrechtJun 25, 2024▶ 34:38State of the Art: Training 70B LLMs on 10,000 H100 clusters
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