So now, let me ask you, someone suggest brought up. The reason why we are able to do that, say for instance, and like computers don't, is because we are grounded in real world knowledge of what we are experiencing. Yeah. So how exactly do you transfer that into neurons that are embodied in something other than a circuit? How do you bring that real world grounded or is the real world grounded knowledge that we have because of the network of neurons that we have in our brain?

Our ability to acquire that real world knowledge is what's fascinating. So something like a tiger or a snake, that could be a genetic prior, right? Generations and generations of people who didn't run when they saw tigers got eaten. But you'll also learn to fear electrical shocks, let's say. It's very unlikely there's a predisposed genetic prior to make you scared of electricity, because we just haven't interacted with it for that long. But we learn, don't we? Rapidly. You show a child once or twice, you show them a video, they learn, oh, electricity, bad. One or two samples is all that they'll typically need. And that's due to the absolute mass of parallelization and flexibility of a neural system. We can make these connections.

How long does it take your neurons, processors to learn as they play pong? Or is this an experiment that's still ongoing?

We're still just scratching the surface of this. This is science as it's happening. And we've wanted to be really, we kind of like to think of ourselves as like anti -hype scientists. So we wanted to show people like, look, here's this work. It's covered in warts. It's messy. It's janky. But it seems to be doing something. So we wanted to share it with people. So we were able to see some learning. We basically tested for say 20 minutes at a time. And we could find like very big differences from the first five to the last 15. So within five minutes, they were reorganizing and actually, we recently found out it could be even quicker than five minutes for them to reorganize. And then the learning of peers over the next couple of minutes as they start to upregulate and improve. I'm still trying to figure out, is this just a natural

order of neural function because there's a saying, neurons that fire together, wire together. Yeah,

yeah.

Is that what you're talking about when you said the learning aspect? Is

that what they say up in the hood? I mean, where'd you get this?

Classic line

for something called heavy in plasticity and neurons at fire together, wire together. It's been a mantra in neuroscience since, uh, Oh gosh, don't test me on the history of that, but for a long time. Okay.

Maybe this start up in the hood. Okay.

Yeah. In our hood, in the hood we said, yeah. Yeah, it was a dude named Jamal. Okay, okay, thank you. I know him.

Thank

you.

The white, Jamal the wise. Jamal the wise. Yes, the white. Is that what you're seeing when you talk about this learning aspect that happens in this short period of time that you're observing? That's

actually just one part of what we're seeing. So yeah, this thing called heavy plasticity. Absolutely massively upregulates incredibly rapidly once they're in these environments. But what's cool is that there's actually so much more that's going on and you can break this down and find so many different processes that are interacting at different timescales. So that's why when I say like the complexity of these one of the few things that really is parallel to is those massive macro scale interactions that can happen on that galaxy level. It's absolutely mind -blowing.

What you're talking about now that I'm putting all this together is freakin crazy because what you're talking about right now is a biological computer, basically, that has the ability to do what we do, because computers right now can't do what we do. They can't do the silicon. It can't do what we do. The real world grounded knowledge that is necessary to do what we do. It can make huge calculations and tons of associations. but it has to see all those associations in order to make them. And what you said earlier is what really makes sense. You show a child a ball, it will know a ball if you show it a baseball, if you show it a basketball, it's going to say ball. Whereas if you show a computer that, you have to show that computer every single kind of ball for it to say that's a ball. What you're talking about right now with using neurons, you can turn these things on and off instead of zeros and ones. And instead of zeros and ones where you got to show every single thing that is, it can actually do what we do and it can start to make associations

on its own.

Am I

right when I say this? That's certainly what we're hoping to be able to show. And you've got this neat thing here where you have a ground truth. Let's say people are going for artificial generalized intelligence. And we just we don't know if you can achieve what you're talking about with silicon. It's never been done before. But you me, as I said, cats, rats, birds, bees, to some extent have this generalized intelligence, you have this ground truth that using this hardware, this wetware, it is possible to have these effects. So the question isn't if it's possible, but how do you get there? And that's a very different place to start from. Let me just for

once, I'm sorry guys, because I'm freaking out right now. You're freaking me out, man. I'm just saying. Okay, here's the question, Brett. And I'm not trying to be disrespectful at all. That means it's about to be disrespectful. Well, I don't mean to be why the hell would you want to do this? This I mean this could go horribly wrong in a lot of ways Like you could literally create the intelligence that becomes the next species It won't be a computer. It'll be something much more. That's what I'm getting. You're scared, Chuck. I'm scared. Yeah, I'm sorry. I'm scared. You're scared.

By the way, the Terminator had biological tissue affixed to its exoskeleton.

But not and I think this is important thing, not a biological brain. Right. And I think when you when you think about the risk, something that can self -replicate rapidly, be hard to get into the internet and all these things that we worry about AGI, all those fears are missing from biological intelligence. At the end of the day, even if you do create an incredibly intelligent system in a dish, let's say that happens. Let's say we go completely out there, super intelligence in a dish, it's still not really going to be able to manage, you know, against a small courtful of bleach. So these things are controllable. Like they're controllable. This is one aspect of it. Even if we achieve what you're saying. It's not going to jump out at Petri dish and kick your ass. Exactly. Any capabilities we provide it is something we have to provide it. And we have no intention of doing any of this in the near future. And at the end of day, it will be discreet or it'll be controllable. It'll be just one brain, much as we are.