Evidence receipt / recommendation
Published · transcript-backedJoe Reeve: recommendation
8 Jun 2023 Latent Space From RLHF to RLHB: The Case for Learning from Human Behavior - with Jeffrey Wang and Joe Reeve of Amplitude
“Because the LLMs can do a lot more of the reasoning, but we can make sure that the context we're providing is much more specific and generally much better by using the traditional ML models.”
Source trail
Everything needed to verify it.
- Speaker
- Joe Reeve
- Attribution
- Verified speaker
- Claim type
- recommendation
- Recorded
- 8 Jun 2023
- Publisher
- Latent Space
Transcript context
…Yeah, there is a little bit of a contrast, conflicts, because you already had all these ML models in-house and you're spinning up a new AI team and you're like, no, let's do all of this with GPT-3. Are the existing ML researchers saying like, no, this is a complete misuse of text generation? Or are they excited about it? Is it unlocking new things? Yeah, actually, it's the combining these things. So we're able to use the traditional ML to shorten the fields, to narrow the number of things we need to pass into the LLMs. Because the LLMs can do a lot more of the reasoning, but we can make sure that the context we're providing is much more specific and generally much better by using the traditional ML models. Yeah, okay. And then the pain points that you're experiencing are hallucination. And then also like the multi-query thing. What do you think you wish for? Or what do you think you're thinking about to solve those pain points?…
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