Scaling to Doom — the CL1 platform and the cloud wetware pitch

50:58you the health of the neurons, the amount of oxygen there is, the amount of CO2 there is, and so on and so forth. So, it can regulate temperature, it can manage gas exchange, it can clear metabolic waste cuz these neurons are alive, so they're going to be creating waste. All of this other stuff. And they can actually survive in that in vitro petri dish for up to 6 months. It's a very long time. Okay. For a sort of little mini organoid to survive. >> So how about the software? This is very cool. So for the for the Pong for the Pong story, they had a customuilt C C++ machine language type thing. Nobody wants to code in C++. I get that you

51:38want the base layer >> Yes. of your software to be in C++ because we want very low latency, right? And C is an extremely fast language. Python is quite slow, but at the high level, I want to code in Python. Okay? And then maybe the Python gets transferred into C. And what they did was they created something called a cortical cloud and a Python API. So now you don't need C++. And you've got a cloud computer of a bunch of CL1 platforms that are each >> like, you know, little tiny >> brains on a dish that I can now just like get into my, you know, on my laptop. I can access it's open open

52:19platform. I mean, you have to like apply and say like this is what I want to do with it. But this is I think very clever from Cortical Labs because >> even IBM like one of the reasons why KisKit which is the quantum computing platform for IBM like their software platform that's used a lot because they've created a cloud platform where theorists and like people who want to do testing of quantum algorithms and things like that they can go into KisKit they can apply for time on the IBM quantum computer. they've got like a dilution refrigerator with that IBM quantum computer and they can like test out their algorithms and like their error correction methodologies and things like that. So democratizing it is a really good way for like a startup or like a

53:00small computer lab to be like, "Hey, we've created the hardware. Why don't you guys go at it?" >> Yes. Right. >> Yes. >> It's very Matrixesque. If you remember the scene where Neo unplugs and he sees all the pods of humans to capture heat for the machines, that's what that effectively wetwware server rack. AWS Nvidia server rack looks like. >> Exactly. Yeah. It's like AWS but for like wetwware >> for wetware. >> It's it's pretty crazy. An AWS for a brain on a chip. >> That is so outrageous. Amazon Web Services for those who don't know is the infrastructure layer that provides the back end for uh a large amount of all of the software applications that you use every day.

53:40>> Yeah, exactly. So with that in mind, now that we've got a cloud computing platform, >> Yes. >> now independent researchers and developers >> can mess around with it. And this is where we get into Sean Cole. He's an independent developer. >> Okay. >> Who wanted to use the CL1 platform >> to play Doom Freedom >> Classic. Okay. And the, you know, one of the I don't know why this is a meme, >> but like whenever you have like a new piece of computation or something, everyone's like, "Can it play Doom?" >> Can it play Doom? >> Right. Like, like even the ESA has like made >> satellites play Doom and things like that. So, I guess it's a meme. And the guys at Cortical Labs knew this was a

54:22meme. Yes. >> And knew that if they could make their little thing play Doom, it would get a lot of hype. And it certainly worked. >> And I just want to give a shout out to John Carmarmac who was the inventor of Doom at ID Software and literally was one of the pioneers that created all the video game like like he that that was the like the 3D platform like that concept and what they did at the time is what created all firsterson shooter style or like all these types of games. >> So is Doom before um what's the James Bond >> James Bond Golden Eye? >> Yeah. I I don't have a a chronological knowledge, >> but I feel like James Bond Golden Eye

55:02was also kind like from what I've I've never played Doom, but I've seen the videos while I was researching this and it looked a kind of like >> it's similar. >> Yeah. >> But it's not Doom. >> Yeah, it's not Doom. I guess >> I I was a 64 guy. I played Golden Eye all the time. I love the music, but but Doom is sort of >> Doom is kind of like this OG. >> It's it own thing. >> Yeah. So, it it is way more complex than Pong. So, you know, one of the things that I as I was like researching Doom and I was like watching some videos of people playing Doom, you know, it's really you're transitioning from a 2D linear game like Pong to now it's kind of like this 2.5dimensional. I wouldn't really say threedimensional because it's like >> first person and like the it's not

55:43really fully threedimensional, I would say, but there's still it involves complex navigation, threat detection, and all of this other very cool stuff. So it's a way harder problem. >> Yes. >> Than >> up, down, >> how close. >> Yes. Exactly. Right. Oh, you're already getting there. Is like those are the sort of salient things that I need to code in. You know, before in Pong, I needed to code in position of my paddle and where the ball is here. In this case, I need to figure out where what direction the enemy is and how close they are. Anyways, let's get to um >> the stem the cells. We got 200,000 human pluropotin stem cells. >> Yes. >> So this is a fourth of what we had in

56:23Pong. >> So fewer than what we have in >> Pong. Right. Okay. Yep. >> But because of like the cloud computing nature and the fact that >> this is all in Python, the guys were able to map the engine to the tissue in just a week. >> And this is what it looks like. >> Jesus. So, you've got you've got your