Transcript
Alessio [00:00:04]: Hey everyone, welcome to the Latent Space podcast. This is Alessio, partner and CTO at Decibel Partners, and I'm joined by my co-host Swyx, founder of SmallAI.
swyx [00:00:12]: Hey, and today we are very honored to have in the studio Maria and Ethan from Bee.
Maria [00:00:16]: Hi, thank you for having us.
swyx [00:00:20]: And you are, I think, the first hardware founders we've had on the podcast. I've been looking to have had a hardware founder, like a wearable hardware, like a wearable hardware founder for a while. I think we're going to have two or three of them this year. And you're the ones that I wear every day. So thank you for making Bee. Thank you for all the feedback and the usage. Yeah, you know, I've been a big fan. You are the speaker gift for the Engineering World's Fair. And let's start from the beginning. What is Bee Computer?
Ethan [00:00:52]: Bee Computer is a personal AI system. So you can think of it as AI living alongside you in first person. So it can kind of capture your in real life. So with that understanding can help you in significant ways. You know, the obvious one is memory, but that's that's really just the base kind of use case. So recalling and reflective. I know, Swyx, that you you like the idea of journaling, but you don't but still have some some kind of reflective summary of what you experienced in real life. But it's also about just having like the whole context of a human being and understanding, you know, giving the machine the ability to understand, like, what's going on in your life. Your attitudes, your desires, specifics about your preferences, so that not only can it help you with recall, but then anything that you need it to do, it already knows, like, if you think about like somebody who you've worked with or lived with for a long time, they just know kind of without having to ask you what you would want, it's clear that like, that is the future that personal AI, like, it's just going to be very, you know, the AI is just so much more valuable with personal context.
Maria [00:01:58]: I will say that one of the things that we are really passionate is really understanding this. Personal context, because we'll make the AI more useful. Think about like a best friend that know you so well. That's one of the things that we are seeing from the user. They're using from a companion standpoint or professional use cases. There are many ways to use B, but companionship and professional are the ones that we are seeing now more.
swyx [00:02:22]: Yeah. It feels so dry to talk about use cases. Yeah. Yeah.
Maria [00:02:26]: It's like really like investor question. Like, what kind of use case?
Ethan [00:02:28]: We're just like, we've been so broken and trained. But I mean, on the base case, it's just like, don't you want your AI to know everything you've said and like everywhere you've been, like, wouldn't you want that?
Maria [00:02:40]: Yeah. And don't stay there and repeat every time, like, oh, this is what I like. You already know that. And you do things for me based on that. That's I think is really cool.
swyx [00:02:50]: Great. Do you want to jump into a demo? Do you have any other questions?
Alessio [00:02:54]: I want to maybe just cover the origin story. Just how did you two meet? What was the was this the first idea you started working on? Was there something else before?
Maria [00:03:02]: I can start. So Ethan and I, we know each other from six years now. He had a company called Squad. And before that was called Olabot and was a personal AI. Yeah, I should. So maybe you should start this one. But yeah, that's how I know Ethan. Like he was pivoting from personal AI to Squad. And there was a co-watching with friends product. I had experience working with TikTok and video content. So I had the pivoting and we launched Squad and was really successful. And at the end. The founders decided to sell that to Twitter, now X. So both of us, we joined X. We launched Twitter Spaces. We launched many other products. And yeah, till then, we basically continue to work together to the start of B.
Ethan [00:03:46]: The interesting thing is like this isn't the first attempt at personal AI. In 2016, when I started my first company, it started out as a personal AI company. This is before Transformers, no BERT even like just RNNs. You couldn't really do any convincing dialogue at all. I met Esther, who was my previous co-founder. We both really interested in the idea of like having a machine kind of model or understand a dynamic human. We wanted to make personal AI. This was like more geared towards because we had obviously much limited tools, more geared towards like younger people. So I don't know if you remember in 2016, there was like a brief chatbot boom. It was way premature, but it was when Zuckerberg went up on F8 and yeah, M and like. Yeah. The messenger platform, people like, oh, bots are going to replace apps. It was like for about six months. And then everybody realized, man, these things are terrible and like they're not replacing apps. But it was at that time that we got excited and we're like, we tried to make this like, oh, teach the AI about you. So it was just an app that you kind of chatted with and it would ask you questions and then like give you some feedback.
Maria [00:04:53]: But Hugging Face first version was launched at the same time. Yeah, we started it.
Ethan [00:04:56]: We started out the same office as Hugging Face because Betaworks was our investor. So they had to think. They had a thing called Bot Camp. Betaworks is like a really cool VC because they invest in out there things. They're like way ahead of everybody else. And like back then it was they had something called Bot Camp. They took six companies and it was us and Hugging Face. And then I think the other four, I'm pretty sure, are dead. But and Hugging Face was the one that really got, you know, I mean, 30% success rate is pretty good. Yeah. But yeah, when we it was, it was like it was just the two founders. Yeah, they were kind of like an AI company in the beginning. It was a chat app for teenagers. A lot of people don't know that Hugging Face was like, hey, friend, how was school? Let's trade selfies. But then, you know, they built the Transformers library, I believe, to help them make their chat app better. And then they open sourced and it was like it blew up. And like they're like, oh, maybe this is the opportunity. And now they're Hugging Face. But anyway, like we were obsessed with it at that time. But then it was clear that there's some people who really love chatting and like answering questions. But it's like a lot of work, like just to kind of manually.
Maria [00:06:00]: Yeah.
Ethan [00:06:01]: Teach like all these things about you to an AI.
Maria [00:06:04]: Yeah, there were some people that were super passionate, for example, teenagers. They really like, for example, to speak ab
