This Week in Startups
00:29:55 · S4, Hon Weng Chong, Brendan Foody
[00:29:55] S4: We're all familiar with AWS, Amazon Web Services. That's the cloud platform that powers so many of your favorite brands. But do you know about AWS Activate? That's their program for startups, where they provide up to a $100,000 in AWS credits for all startups. Whether you're backed by an investor or you're bootstrapping, money is time to keep innovating, time to delight customers, and time for you to keep gaining traction. You need runway, and AWS's Activate is going to help you with that runway. We hear this story from so many of our founding university companies. They're finding product market fit, the words getting out about their product, just a little boost, finding some savings here or there to get a little extra time can be the difference between getting traction and bringing in revenue, or hey, let's call it what it is, running out of money, okay, and shutting down. AWS knows this. That's why they've created the ultimate toolkit for early stage startups looking to boost growth. With AWS Activate, you're gonna get up to a $100,000 in AWS credits, hands on support, and training, plus exclusive discounts with some of our favorite companies and tools. So start getting the support you need at every stage of your startup journey. To learn more, visit aws.amazon.com/startups/credits. That's right. Aws.amazon.com/startups/credits. [00:31:16] S3: I think you're on the right path. I mean, thing about it is that it's... We're good at some things that machines aren't, and machines are good at things that we aren't. Right? [00:31:23] S5: Right. So this is called
00:31:23 · Brendan Foody, Hon Weng Chong, Alex Wilhelm
[00:31:23] S5: Right. So this is called [00:31:24] S3: Moravec's paradox, particularly in robotics. And I think this is the motivating factor for why Elon set it up, things like Neuralink, right, and the BCI people, which is that, as AI gets smarter and better, we also need to skill up, right? They're getting, so if you think about it, the machines are getting better at what we reserve as traditionally human or biologically centered tasks. It's not beyond the realms of possibility that we could also go the other way, assuming that DCR has really become a thing, where not only do we utilize our brains for the low power stochastic computation, the probabilistic computation, but we can also just, you know, have a... I don't know, an iPhone chip in there that can just give us the square root number at the speed of thought. [00:32:03] S1: Right. So I could essentially allow compute to handle the math that I don't wanna do myself, but all the learning, can use my brain for. So Correct. I... Once again, you guys are kind of Neuralink in reverse. So Yep. Look ahead of just a just a couple of years. Not super long term, but the c l one gets into the market next year, customers. You guys are also gonna have an API to let people access the technology remotely if they don't have the lab setup necessary to run this thing. Yep. What's the next generation? Like, what are you guys gonna build after the c l one? What is the c l two?
00:32:32 · Hon Weng Chong
[00:32:32] S3: Well, I think the c l two is... We've been thinking about it and there are a lot of features that didn't make it into the CL one that we'll probably start thinking about putting it into CL two. Mean, things, your standard things, right? Make it like smaller, make it probably cheaper to obtain, easier to program, maybe more modular units. There are quite a few things that we've been thinking about. Now the question is does it take the CL two or does it get pushed out to the CL three is a discussion for the team. But again, I think it's still a little bit premature. What we really wanna do is get the CL1 out to our partners, our research collaborators, and really get their feedback, what works, what doesn't work. So that way we can sort of triage and prioritize what we wanna do for the CL2. No point of putting in features that no one else wants. I mean, we might want it, but we have the ability to just spin up whatever, CL3, four, whatever internally. But if there are features that are missing that we have on our list that's kind of lowered down our sort of priority, but it would, you know, tremendously help the the community get going faster or do more work for less. You know, I think that's something that we wanna be prioritizing.
00:33:50 · Alex Wilhelm, Hon Weng Chong
[00:33:50] S1: You talked about using mice neurons at the top of the show, and anyone who knows anything about biology and experiments knows that a lot of a lot of mice and rats die. So that Yes. Is kind of par for the course for how we currently handle ethics. Are mice neurons and human neurons radically different? Are they relatively fungible? Silly question, but I'm not sure about the answer. Before I get to an ethics question, I thought we'd start there. [00:34:14] S3: So... And and this is the really interesting thing. We we used to think that there was no difference between a human and a mouse neuron. If you read any of the papers before, I think twenty twenty two, twenty, everyone said, yeah, there's no difference, all mammalian neurons are the same. And it turns out that I think on average, human dendrites are actually longer than mouse dendrites, but they have the same number of ion channels. So these are the gates that allow the potassium and sodium to go back and forth between the cell and the external environment. And that's what generates the action potential. But having the space out more, you actually have the ability to hold more so called electrical states. Well, that's the theory that's been pushed by some of the researchers at Harvard and MIT. And so, yeah, it turns out they are different and that probably contributes to the differential in the overall performance. And we've seen that as well. The human neurons are better at playing and processing information.
00:34:14 · Hon Weng Chong, Alex Wilhelm
[00:34:14] S3: So... And and this is the really interesting thing. We we used to think that there was no difference between a human and a mouse neuron. If you read any of the papers before, I think twenty twenty two, twenty, everyone said, yeah, there's no difference, all mammalian neurons are the same. And it turns out that I think on average, human dendrites are actually longer than mouse dendrites, but they have the same number of ion channels. So these are the gates that allow the potassium and sodium to go back and forth between the cell and the external environment. And that's what generates the action potential. But having the space out more, you actually have the ability to hold more so called electrical states. Well, that's the theory that's been pushed by some of the researchers at Harvard and MIT. And so, yeah, it turns out they are different and that probably contributes to the differential in the overall performance. And we've seen that as well. The human neurons are better at playing and processing information. [00:35:17] S1: But but for now but for now, though, Han, the the mice neurons are sufficient for the state of technology and the progress you guys want to make. So we're not there's gonna eventually become a new story entitled, startups takes human neurons, puts them into computer. Are we creating a new form of consciousness? Oh, oh, panic. But it sounds like So...
00:35:35 · Hon Weng Chong
[00:35:35] S3: Well, we actually do use human neurons now. Alongside mouse neurons, human neurons is the other really big area of research because that's where a lot of the biomedical stuff happens, where we're looking for new drugs, understanding disease models and so forth. We stand at the shoulder of giants and so we use a lot of the techniques that have been developed by the, what you call the synthetic biology, the biological engineering field to grow stem cells obtained from adult cells. So if we went back about ten years ago, in Japan, there was a researcher by the name of Yamakana. Professor Yamakana won the Nobel Prize, I think a few years back for discovery of inducible pluripotent stem cells. And what he discovered was that if you took anybody's cells, your cells, my cells, skin or blood, anything that would have nuclei, and you expose them to four compounds, you can actually reverse the clock back of these cells where they go from a blood cell or a skin cell back into a naive state... Stem cell that can then become... Turn into anything. We utilize that functionality essentially grow human neurons from stem cells. So this way we don't kill any animals, it's continuously renewable as long as you provide the right conditions. And yeah, how we do it now at Cortical Labs because, you know, we we don't really particularly like killing the mice as well, and so we think that it's actually