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Harrison Chase

Published podcast speaker

Claims
21
Episodes
1
Shows
1
Named items
0

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What Harrison said.

21 transcript-backed records

10 / belief

Like one, like, you know, if we think about what it takes to build a really reliable, like context-aware reasoning application, there's probably a bunch of different nodes that are doing a bunch of different things.

“Like one, like, you know, if we think about what it takes to build a really reliable, like context-aware reasoning application, there's probably a bunch of different nodes that are doing a bunch of different things.”
Speaker
Harrison Chase
Publisher
Latent Space

12 / belief

I think another example of this, I mean, Langsmith, which we can maybe talk about was like very kind of like, I think we worked on that for like three or four months before announcing it kind of like publicly, two months maybe before giving it to kind of like anyone in beta.

“I think another example of this, I mean, Langsmith, which we can maybe talk about was like very kind of like, I think we worked on that for like three or four months before announcing it kind of like publicly, two months maybe before giving it to kind of like anyone in beta.”
Speaker
Harrison Chase
Publisher
Latent Space

13 / belief

Yeah, we'll probably go. And yeah, we'll do more of that because I think that's definitely part of the application of a chain or agent is you start with a default one, then you improve it over time.

“Yeah, we'll probably go. And yeah, we'll do more of that because I think that's definitely part of the application of a chain or agent is you start with a default one, then you improve it over time.”
Speaker
Harrison Chase
Publisher
Latent Space

15 / evaluation

I think maybe orchestration is a little bit more than 5%, but I like agree that those are like really big pain points that get exacerbated when you have these complex chains and agents where you can't really see what's going on inside of them.

“I think maybe orchestration is a little bit more than 5%, but I like agree that those are like really big pain points that get exacerbated when you have these complex chains and agents where you can't really see what's going on inside of them.”
Speaker
Harrison Chase
Publisher
Latent Space

16 / evaluation

Yeah, I mean, I think that's, you know, you talk about like, again, this whole space is just changing so fast, but you talk about something that could like really change how, because like, you know, a lot of lang chain is kind of like a data orchestration tool in some sense.

“Yeah, I mean, I think that's, you know, you talk about like, again, this whole space is just changing so fast, but you talk about something that could like really change how, because like, you know, a lot of lang chain is kind of like a data orchestration tool in some sense.”
Speaker
Harrison Chase
Publisher
Latent Space

17 / recommendation

To reduce hallucinations, we did a webinar on like evaluating RAG this past week. And I think there's this great project called RAGOS that evaluates four different things across two different spectrums.

“To reduce hallucinations, we did a webinar on like evaluating RAG this past week. And I think there's this great project called RAGOS that evaluates four different things across two different spectrums.”
Speaker
Harrison Chase
Publisher
Latent Space

18 / recommendation

You probably start with like a zero-shot prompt. But I think that's a really powerful one that's probably just talked about less because you don't need it right off the bat.

“You probably start with like a zero-shot prompt. But I think that's a really powerful one that's probably just talked about less because you don't need it right off the bat.”
Speaker
Harrison Chase
Publisher
Latent Space

19 / evaluation

I definitely think probably the main ones, like basically the LLM. So the reason I think the debugging in Lancsmith and debugging in general is so needed for these LLM apps is that if you're building, like, again, let's think about like what we want people to build in with LangChain.

“I definitely think probably the main ones, like basically the LLM. So the reason I think the debugging in Lancsmith and debugging in general is so needed for these LLM apps is that if you're building, like, again, let's think about like what we want people to build in with LangChain.”
Speaker
Harrison Chase
Publisher
Latent Space

20 / preference

We still think there's, it's just really application specific. So we prioritized instead, making it easy for people to write custom evaluators and then run them client side and then upload the results so that they can manually inspect them because I think manual inspection is still a pretty big part of evaluation for better or worse.

“We still think there's, it's just really application specific. So we prioritized instead, making it easy for people to write custom evaluators and then run them client side and then upload the results so that they can manually inspect them because I think manual inspection is still a pretty big part of evaluation for better or worse.”
Speaker
Harrison Chase
Publisher
Latent Space

21 / evaluation

I don't know if those are like underappreciated though, because I think a lot of people talk about text splitting as being a hard part, and it is a really important part of creating these retrieval applications.

“I don't know if those are like underappreciated though, because I think a lot of people talk about text splitting as being a hard part, and it is a really important part of creating these retrieval applications.”
Speaker
Harrison Chase
Publisher
Latent Space
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