Shawn Wang: belief

Transcript context

…And many times when you try to use a product like this, you often don't know what questions to look for or the things to look for. So we kind of made this decision very deliberately that instead of asking the users just follow-up questions directly, we kind of lay out, hey, this is what I would do. Like, these are the different facets. For example, here it could be like what additives are allowed and how that differs or labeling. Uh, restrictions and so on in products. The aim of this is to kind of tell the user about the topic a little bit more and also get steer. At the same time, we elicit for like, uh, you know, a follow-up question and so on. So we kind of did that in a joint question. It's kind of like editable chain of thought. Right. Exactly. Exactly. Yeah. I think that, you know, we were talking to you about like your top tips for using deep research. Yeah. Your number one tip is to edit the page. Just edit it. Right. So like we actually, you can actually edit conversationally. We put in a button here just to like draw users' attention to the fact that you can edit. Oh, actually you don't need to click the button. You don't even need to click the button. Yeah. Actually, like in early rounds of testing, we saw no one was editing. And so we were just like, if we just put a button here, maybe people will like. I confess I just hit start a lot. I think like we see that too. Like most people hit start. Um, like it's like the, I'm feeling lucky. Yeah. Yeah. All right. So like I, I can just add a, add a step here and what you'll see is it should like refine the plan and show you a new thing to propose. Here we go. So it's added step seven, find information and milk and meat labeling requirements in the US and the EU, or you can just go ahead and hit start. I think it's still like a nice transparency mechanism. Even if users don't want to engage, like you still kind of know, okay, here's at least an understanding of why I'm getting the report I'm going to get, um, which is kind of nice. And then while it browses the web and Morgan, you should maybe explain kind of how it, how it browses. We show kind of the, the websites it's reading in real time. Yeah. I'll preface this with, I haven't, I forgot to explain the rules. You're a PM and you're a tech lead. Yes. Okay. Yeah. Just for people who, who don't know, we maybe should have started with that. I suppose. Yeah. Yeah. We do each other's work sometimes as well, but more or less that's the boundary. Yeah. Yeah. Um, yeah. So, so what's happening behind the scenes actually is we kind of give this research plan that is a contract and that, uh, you know, has been accepted, but then if you look at the plan, there are things that are obviously parallelizable, so the model figures out which of the sub steps that it can start exploring in parallel, and then it primarily uses like two tools. It has the ability to perform searches and it has abilities to go deeper within, you know, a particular webpage of interest, right? And oftentimes it'll start exploring things in parallel, but that's not sufficient. Many times it, it has to reason based on information found. So in this case, it, one of the searches could have led the EU commission has these additives, and it wants to go and check if the FDA does the same thing, right? So, uh, this notion of being able to read outputs from the previous turn, uh, ground on that to decide what to do next, I think was, was key. Otherwise you have like incomplete information and your report becomes a little bit of a, like a high level, uh, bullet points. So we wanted to go beyond that blueprint and actually figure out, you know, what are the key aspects here. So, yeah. So the, this happens iteratively until the model thinks it's finished. All its steps. And then we kind of entered this, uh, analysis mode and here there can be inconsistencies across sources. You kind of come up with an outline for the report, start generating a draft. The model tries to revise that by self critiquing itself, uh, you know, to find out to finalize the prompt, uh, finalize the report. And that's probably what's happening behind the scenes.…

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