MIT dropout Claire Wang is simulating nervous systems in worms to unlock better brain-computer interfaces

uh certainly a uh certainly

pretty rough to look at.

It is very weird. It's uh it's not it it didn't nail like the beauty of many of these things. Anyway, uh we have our last guest of the show, Claire Wang. Building biologically accurate simulations of nervous systems. Elegant

pure research.

Welcome to the show, Claire. How are you doing?

Great to meet you.

Hi, nice to meet you.

Thank you so much for taking the time. Uh, please introduce yourself.

Age of research.

Age of research. Yeah. Tell us tell us a little bit about what you're working on.

Yeah, of course. So, I'm Claire. I actually just dropped out, but I was a junior at MIT studying electrical engineering, computer science. Uh a lot of my interests in the past bit has been in the field of neuroch includes a focus in um whole brain emulation with a focus on doing this with worms first but also like how useful this could be for brain computer interfaces and understanding consciousness maybe

um in that sort of direction.

So uh I mean we we've talked to a number of uh of of companies that are working on brain computer interfaces bumping into this general uh scientific discipline. uh what was the decision to not join one of the existing efforts or stay in academia and actually go out on your own.

Yeah, that's a good question. So, I would say like um there's still a lot of current efforts that I think I really believe in. Yeah.

Um and that like I'm good friends with them, would help out with them. I think there's a lot of bets that people have to make and these bets are unfortunately kind of fundamental science bets of like, oh, is this physics going to work? Is this like biological

like truth actually true? Yeah.

So, I think like while these people I think all these bets are like interesting, there's no 100% and so I think it kind of makes sense to um instead make your own bet on what you think makes the most logical sense. That's that's kind of my reasoning here. Yeah.

Yeah. Do you also think it's a better time than ever to be working more independently on biotech generally because of the advance of AI? And we've talked to a couple companies that are sort of working on uh you know the AWS of of lab equipment more rentals projects so that maybe you don't need to raise you know a billion dollars out of the gate and build a biosafety level two lab on day one. uh do you feel like more empowered to do uh you know to validate those uh hypotheses that you were articulating earlier?

Yeah. No, I think that's a that this is like probably the right time. I think there's a mix like definitely the AI um definitely a sururgence like insurgence of like alternate science funding

um a willingness for academics and for example like people in startups to work together. Um, I also think that people are just much more open to, you know, new ideas and research risk in startups, which I think like, you know, 10 years ago you'd be told like never ever invest in research risk versus now like everything is a research risk.

So, I think I think that's like a really good time

um for you to do it like

right now. Yeah.

Yeah. Jordy, you have you had a question or

Yeah. I mean, my my main question was like figuring out when when that right moment is because there's especially after the, you know, the announcement of the fellowship this week. I'm sure you've been offered uh I'm sure people would offer you millions of dollars over email to just say like it's fine if you want to just keep doing research.

Um but uh but I guess you'll know it. Well, help me help me bridge the gap between uh what we've seen in BCI with mostly reading from the brain, getting an X and Y output so you can control a mouse on a computer. Incredibly impactful technology. Uh and then uh simulating nervous systems. Uh how are these two things related in your mind? Why are they important to overlap? Like what is the overlap?

Yeah. Yeah. So I think right now BCI technology is very powerful in the sense that it is on a great path towards clinical applications. Yeah.

Um soon like people who are paraplegics can maybe walk again and people who are blind can see again.

Um but a lot of this comes from almost like post hawk problem solving. You like throw enough data at a model of like someone's brain and like maybe you can help them like move their arm in the xy direction. Sure.

Or like move a mouse in a specific way. Yeah,

but when you are able to like actually decode information from the brain and read and understand like uh you know exact signals coming from every region of the brain being able to like truly like control the brain for example like if you know which regions to activate then you have a more naturalistic control method. So like instead of like only being able to move my arm left to right you can move your arm like very naturalistically in any like degree of freedom. And I think that's kind of the like power of being able to simulate the brain. um you could do a lot of like research understanding of like one of the most complex things in the universe. Uh and I mean obviously like we're not starting with the human brain but any level tells you the sort of data that you need and tells you the sort of like imaging techniques that work and I think through that you get um a lot more information and like progress in BCF.

Why C elegance and not mice or monkeys or something else? uh is it cost or do you have a firm belief that what if it works in C elegance it'll scale uh is there prior art like what what excites you about that particular target

yeah um so celigans is 300 neurons it's really dumb it's like really just not I mean it's not close to humans at all but I think the the argument is like we can't even simulate the celigans there's a lot of benefits gives us it is translucent um you could do it's much easier to do gene therapy so like fluorescent therapy So easier to image as well. Um and also they're just like very simple. They have graded potentials instead of action potentials. So I think the idea is we can't even do so. So we have to start with that and there's uh a lot of like what is the sort of data that you need like do I need voltage data or is calcium data enough? Um is light sheet or electron microscopy enough? So like there's all these questions that can answer and once we answer that question obviously the goal is to move on to like zebra fish and mice and fly um and so on. But right now like we are not close or or like we're not close to mouse for example because like

there's no way to image the mouse brain while the mouse is still alive.

Yeah.

Um yeah

but you came with

fascinating. Uh are you thinking about you'll do you think you'll wind up with co-founders? Like how how early are you in the process of like turning something into a company? Do you want to just sort of like be on your own or do you want to build a some sort of team even if it's loose? How do you think about like research collaboration? Yeah. So, um I mean I've been able I've been lucky to work with some of the most amazing researchers. Um and I think these are people I want to continue to be around and learn from, but I think in terms of specifics like finding co-founders, finding the right um bet, for example, the scientific bet I want to make sure.

That's still up in the air. I'm still like learning. I'm still meeting a lot of people

and seeing like what do I believe in and what do I like think makes the most sense. So, it's still quite early stage for me.

Are you going to move to San Francisco?

Yeah. Uh yeah, probably

reluctantly maybe.

I mean I like SF. I lived in SF in the past but like I don't know.

Yeah,

it's kind of a principles thing.

Yeah. Have you always been pure researcher or do you have entrepreneurship background as well? What else have you done?

Oh yeah. I mean I would say like almost most of my background is very clean mix between like the startup space and uh research. Like I've done a lot of work in like for example working at various startups, helping out with startups, some like small scale like investing stuff. So I I I think like I have a good mix up of both sides.

That's very fun. Well, good luck.

Well, come back on whenever you have news and congratulations.

Yeah, we'd love to catch up soon.

Great to meet you.

Have a great rest of your day. We'll talk to you soon. Goodbye.

Intel is up.

Intel's up

massively.

The the market is broadly down today. Uh,

Intel is up 15% after hours.

They reported earnings.

That's good news.

Let us see. Intel reported

he pulled a bread continues to cook with his Intel B.

He needed another win. It had been a couple days since he had a massive win.

Yep.

I think there's actually another story in here from today about a memory company that he invested that's doing very well.

More breaking news in the journal. Bob Iger is returning to where?

Disney.

Thrive. Thrive. No way. That's amazing.

Back to Thrive.

Love it.

Yeah, I think he he's been an LP in Thrive. He also bought a piece of Thrive.

That's right.

Okay. Well, that'll be a good uh next act for him. I'm very interested to see where he goes. There's a whole alumni class coming together. Reed Hastings is out and on to the next thing. We'll see where they go. Hopefully,

uh back to Intel. Intel announced its first quarter earnings after the bell on Thursday, beating an uh analyst expectations on the top and bottom line and providing better than anticipated Q2 guidance on strong data center sales.

Uh Intel said it expects revenue of 13.8 to and 14.8 billion for the second quarter. Wall Street was anticipating uh 13 billion and uh as of this morning they were they they were at around 100 100 um times uh PE

and so it's only I guess uh only up for Intel

climbing the ranks climbing the ranks. Uh Tesla also released Q1 earnings um revenue of 2 uh 22.4 billion versus 21.4 billion estimated. So they beat on topline. Uh they also beat on net income uh 1.45 billion versus 1.17 uh billion estimate. The interesting uh article in the journal was that uh Elon was being more cautious about Tesla uh talking saying uh I think we need to get realistic about some timelines. So, uh, he is, uh, certainly not, you know, pumping everyone up and and he's trying to sort of reset around, uh, the fundamentals. And so, um, we will see where that goes. It is a wild timeline that, uh, SpaceX, if it goes out at 1.75, uh, trillion, will be bigger than Tesla, which is sitting around 1.1 1.2 trillion these days. So, uh, still both huge companies.

Credit to Bubble Boy over on X. two hours ago. He says, "Everyone asked me about how I'm playing earnings." He says, "Doubling down. 25% of my portfolio is in Intel calls."

Wow. There we go, Bubble Boy. Congrats.

Well done.

Good.

Well played

stuff. Well,

well played.

Thank you for tuning in to our Teal Fellowship Giga stream. We will be back tomorrow at 11:00 a.m. Pacific. Leave us five stars on Apple Podcasts and Spotify. Sign up for our newsletter at tvpn.com. Throw that flashbang, Jordy, because we are out of here. It's been an honor.

It's been an honor and a pleasure for hanging out with us and we will see you

tomorrow.

We'll see you soon.

Goodbye.