Evidence receipt / commitment
Published · transcript-backedAarush Selvan: commitment
18 Feb 2025 Latent Space The Inventors of Deep Research
“When we built deep research, I think there was a few things that we took a few different bets, uh, around how this, how it should work.”
Source trail
Everything needed to verify it.
- Speaker
- Aarush Selvan
- Attribution
- Verified speaker
- Claim type
- commitment
- Recorded
- 18 Feb 2025
- Publisher
- Latent Space
- Episode
- The Inventors of Deep Research
Transcript context
…What about learning from others? Obviously, I mean, open AI is deep research literally as the same name. I'm sure. Yeah. I'm sure there's a lot of, you know, contention. Is there anything you've learned from other people trying to build similar tools? Like, do you have opinions on maybe what people are getting wrong that they should do differently? It seems like from the outside, a lot of these products look the same. Ask for a research, get back a research, but obviously when you're building them, you understand the nuances a lot more. When we built deep research, I think there was a few things that we took a few different bets, uh, around how this, how it should work. And what's nice is some of that is actually where we feel like was the right way to go. So we felt like agents should be transparent around telling you upfront, especially if they're going to take some time, what they're going to do. So that's really where that research plan, we showed that in a card, we really wanted to be very publisher forward in this product. So while it's browsing, we wanted to show you like all the websites. It's reading in real time, make it super easy for you to like double-click into those while it's browsing. And the third thing is, you know, putting it into a side-by-side artifacts so that you could ideally easy for you to read and ask at the same time. And what's nice is you kind of, as other products come around, you see some of these ideas also appearing in, in other iterations of this product. So I definitely see this as a space where like everyone in the industry is learning from each other, good ideas get reproduced and built upon. And so, yeah, we'll, we'll definitely keep iterating. And, and kind of following our users and seeing, seeing how we can make, make our future better. But yeah, I think, I think like it's, it's like, this is the way the industry works is like, everyone's going to kind of see good ideas and want to replicate and build off of it. And on the model side, OpenAI is the O3 model, which is not available through the API, the full one. Have you tried already with the two model? Like, is it a big jump or is a lot of the work on the post-training?…
Stored transcript either side of the excerpt. The highlighted words are the published quote; the surrounding text is unedited source, never generated.