Gaming, Nobel Prizes and At-Risk Businesses in the AI Era

**Elad Gil** (0:06)
Sarah, welcome to No Priors. It's such a pleasure to have you here today with me as a guest. How are you doing?

**Sarah** (0:11)
Oh my god, I'm so happy to be here. Thanks a lot.

**Elad Gil** (0:14)
I think you are now joining the number one podcast in, actually, I don't know what.

**Sarah** (0:20)
The number one podcast amongst her friends. I'll take it.

**Elad Gil** (0:22)
Yeah, the number one podcast in her family. It's the number one podcast my mother watches regularly. So it's very exciting for all of our mothers everywhere.

**Sarah** (0:31)
I actually am pretty sure my mom is not listening to this, but if you are, hi, mom. Thanks for your support.

**Elad Gil** (0:36)
I feel happier for her. So I think one thing that I've been really fascinated with that came out recently is NotebookLM from Google. And it's funny because about a year ago or so, me and David, who was on my team, decided to do this cohort at Stanford where we would just sponsor compute and other things for Stanford students to build interesting consumer apps. And then we'd meet every week and do like office hours and just talk through other building and there's no financial transaction or ownership or anything. It was just, we just wanted to do cool stuff, particularly in consumer AI. And what one of the people prototyped was a journaling tool, where as you wrote, the sidebar would start to interpret what you were writing in your journal. And you could choose the lens through which you would interpret it. So it could interpret it as a counselor, it could interpret it as a friend, it could interpret it in different ways, and you're getting real-time feedback of that journal entry in the context of all the prior ones through that lens. And it was really fascinating consumer behavior, like it really felt like something special. And NotebookLM kind of feels like something special to me from the perspective of, you can upload different documents or information, and it'll basically turn it into two AI bots effectively, two AI bots using voice, discussing it as if it's a podcast. That's one sort of application area. It just has this really interesting feel of how can you automate really interesting aspects of information discovery, how do you integrate audio in an interesting multimodal way. Like it just kind of pulls together a lot of really interesting pieces of behavior that really resonate.

**Sarah** (2:18)
It's interesting that I think you love the voice podcast generation feature. I think other people do too. NotebookLM is my favorite new AI product of late, but that's not the way I use it. I just use it as a really nice little pre-built rag gooey, attached to all my data.

**Elad Gil** (2:42)
I agree. It's not just the podcast side of it. I think the last YC batch or two batches ago, they actually had two companies that would allow you to do that. So you could upload a document and effectively, you'd end up with a rag index against it, and then you could interrogate it and interact with it, etc.
So I guess I've seen earlier versions of that. I don't think it's been as elegant as what NotebookLM is doing, but I felt that that plus the voice piece really stood out as an interesting step forward. And I agree with you, the rag piece alone and the ability to interact with documents and data and information is super interesting. And one could argue, to some extent, Lean provides a little bit of that, Answer provides a little bit. There's a couple companies that have been doing pieces of that in interesting ways, but I agree. We're hitting the era where any piece of content can suddenly become something that you can interact with.

**Sarah** (3:29)
Also, it really helps with the cold start problem with consumers. If you insert it into an existing workflow, you use existing artifacts, you connect to existing data. I just think end users, you shouldn't rely on them to be that creative about how to engage with these capabilities and as builders, even Google builders, great job Google, enable more of these interfaces where we're just going to get a step function increase in engagement on them.

**Elad Gil** (3:56)
Yeah, it's interesting. I feel like the main consumer apps were either unintentional or prosumerish.
So, ChatGPT was kind of an experiment that was launched and became a major consumer app. Perplexity is kind of this prosumer consumer thing. You're using it for research, you're using it for search, you're using it for a couple of different things. Mid-Journey kind of started off consumer, but I think it actually has a lot of use cases that people pay subscription for that are a little bit more professional in nature. You're building out graphics for a pitch deck or whatever it may be. So, it's interesting to see that a lot of these things are starting off more as utilities, while in the consumer social era, obviously, there's a lot of just social apps that were the main consumer wave. It was basically commerce, search, and social. This time, we're seeing a lot more on information, utility, information, and content generation. This wave of technologies enabling different consumer behaviors.