“Building up few shot example data sets and really using those. I think it's much faster and cheaper than fine tuning models. It's easier to do than trying to like. Programmatically change the prompt in some way.”
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 Harrison Chase
Opinion
Chase: Open-source models still lag behind Claude 3 and GPT-4
“Like there's, I think we see increasingly interest in open source, but the reasoning abilities are still just like lagging behind Cloud three or GPT four. And I think like for a lot of the applications that it kind of, it probably depends on the types of appli…”
Harrison ChaseMar 28, 2024▶ 22:06No Priors Ep. 57 | With LangChain CEO and Co-Founder Harrison Chase
PredictionNot checkable as stated
Chase: Long context windows will not replace chaining and AI agents
“There are also things where it requires iterations. You need to like decide what to do, interact with the environment, get that back. So this whole idea of chaining and agents, I don't like,
That's less around context windows and more around interacting with t…”
Harrison ChaseMar 28, 2024▶ 18:07No Priors Ep. 57 | With LangChain CEO and Co-Founder Harrison Chase
Insight
Chase: Needle-in-a-haystack benchmarks fail to represent real RAG reasoning
“That, that actually really doesn't reflect a lot of RAG use cases in, in my opinion, because like that's the needle in the haystack is like, okay, given this long context, can I find a single information point? But oftentimes RAG is about seeing multiple infor…”
Harrison ChaseMar 28, 2024▶ 18:44No Priors Ep. 57 | With LangChain CEO and Co-Founder Harrison Chase
Opinion
Chase: AI agent memory is extremely nascent and lacks interesting developments
“I feel it's like a field that's just, like, super, super nascent. Like, I don't, I actually am underwhelmed at the amount of, like, really interesting stuff that's going on there.”
Harrison ChaseMar 28, 2024▶ 9:44No Priors Ep. 57 | With LangChain CEO and Co-Founder Harrison Chase
Insight
Chase: Successful production AI agents operate as controlled state machines
“And I think the things that we see making it into production and informed a lot of the development of laying graph is, or is something in the middle where it's like this controlled state machine type thing.”
Harrison ChaseMar 28, 2024▶ 12:01No Priors Ep. 57 | With LangChain CEO and Co-Founder Harrison Chase
AssertionNot checkable as stated
Chase: Developers only implement model fine-tuning after reaching critical scale
“We see people experimenting with it. I think the only real place where they're doing it is when they've reached like really critical scale which I still don't think is that many applications to date.”
Harrison ChaseMar 28, 2024▶ 20:24No Priors Ep. 57 | With LangChain CEO and Co-Founder Harrison Chase
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