Evidence receipt / evaluation
Published · transcript-backedAnkur Goyal: evaluation
11 Oct 2024 Latent Space Production AI Engineering starts with Evals — with Ankur Goyal of Braintrust
“There's a lot of people, it should be fairly obvious if you look at our customer list, who they are, but I won't call them out specifically, that are doing CodeGen and running the code that's generated in arbitrary environments, but they have also morphed their code into this dumb pattern that I'm talking about, which is like, I'm going to write some code that calls an LLM, it's going to write some code, I might show it to a user or whatever, and then I might just run it.”
Source trail
Everything needed to verify it.
- Speaker
- Ankur Goyal
- Attribution
- Verified speaker
- Claim type
- evaluation
- Recorded
- 11 Oct 2024
- Publisher
- Latent Space
Transcript context
…When Code Interpreter was introduced last year, I was like, this is AGI. There's a lot of people, it should be fairly obvious if you look at our customer list, who they are, but I won't call them out specifically, that are doing CodeGen and running the code that's generated in arbitrary environments, but they have also morphed their code into this dumb pattern that I'm talking about, which is like, I'm going to write some code that calls an LLM, it's going to write some code, I might show it to a user or whatever, and then I might just run it. I like the word Voyager that you use. I don't know anyone who's doing that. Guy Podjarny Voyager is in the paper. My term for this, if you want to use the term, you can use mine, is core versus LLM core. This is a direct parallel from systems engineering, where you have functional core imperative shell. This is a term that people use. You want your core system to be very well defined and imperative outside to be easy to work with. The AI engineering equivalent is that you want the core of your system to not be this Shoggoth, where you just chuck it into a very complex agent. You want to sprinkle LLMs into a database. Because we know how to scale systems, we don't know how to scale agents that are quite hard to be reliable.…
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