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As the training data shows you. In the case of images with cat labels, for example, is to predict an image that has a cat with the right label cat instead of the wrong label microwave. And then because it has this objective during training, if it makes a mistake, if I didn't predict the next word right or if I label the cat wrong, It goes back and iterates and updates its parameters based on the mistake. It has some mathematical rules or learning rules to update. And then it just keeps doing that till it humans ask it to stop or it no longer updates, whatever stop criteria. And then you're left with a ginormous neural network that's already trained by ginormous amount of data. And in that neural network, it has all the parameters, the mathematical parameters that's already learned. Now you can take this and now you have a new sentence coming. And then it goes through this model because it has all the parameter it has learned, it predicts what I should say given the new sentence. Like, hello, hala. How is your breakfast today? And it would predict I had a great breakfast today or or whatever. So that's how it's gonna be used. So interesting. Chat gbt, it's just predicting the next word and the next word and the next word based on all the different patterns and trying to figure out what makes sense to come next. So that's super clear. What I don't understand with something like Chat Gwiti is that it's so good at writing human language, but it's known to make simple math mistakes. How is it possible that it's good at doing human language, but then on math, for example, it's known to make stupid mistakes? It's because math the way we do math in human mind is different from the way
And how that really changed your perspective about AI. AI has been around a lot longer than people think when we started self driving cars back in 2008. That was basically with a belief that cars can intelligence that is as intelligent as a driver and accordingly able to drive a car. And since then, I mean, by 2008, I think in my personal memories, I think 2008 was really the year when we knew that we cracked the code. Early 2009 Google published paper that's known as the cat paper, that white paper basically described how we asked an artificial intelligence machine to look at YouTube videos without prompting it for what to look for, and then it eventually came back and said, I found something. And we said, show us. And it turns out that it found the cat. Not just one cat, but really what Catness is all about, you know, that very entitled cuddly, furry character, basically, could find every cat on YouTube. And that was really the very first glimpse between that and the work that DeepMind was doing on playing Atari games where machines began started to show real intelligence. We then started to integrate that in a lot of things. You know, self driving cars is probably the most publicly known example, but one of the projects that we worked on was which is not the only, you know, Good Lex was not the only one working on it, but we wanted to teach grippers robotic arms. Basically, we wanted to teach them how to pick objects that they're not programmed to pick. And it's a very, very sophisticated task because we do it so easily as humans you don't remember, but if your parents were remember when you were a child and before you learned how to grip, you kept going on trial and error. You would try to grip something and then it falls and then you try again and so on. And basically, we said maybe we can teach the machines the same way
Today except that now we have computers that run billions of times faster than things that were imagined back in the 19 fifties. And so on. It's interesting. Occasionally, things happen very quickly. Oftentimes, it's shocking how slowly things happen. And how long it takes for the world to absorb ideas. Sometimes there'll be an idea, and finally, some technology will make it possible to execute that idea in a way that wasn't there before, sometimes there's an idea and it's been hanging out for a long time and people just ignored it. For one reason or another. And I think some of the things that are happening with AI today probably could have happened a bit earlier. Some things have dependent on sort of the building of a big technology stack, but it's it's always interesting to see that to me at least. It's so fascinating. This actually dovetails perfectly into my next question about your first experiences with AI. So now everybody knows what AI is, but really most of us really started to understand it and using this term maybe 5 years ago, Max, but you've been studying this for decades, even before people probably called it AI. So can you talk to us about the beginnings of how it all started? Ai predates me. That term was invented in 1956. You know, it's funny because As soon as computers were invented, basically in the late 19 forties, and they started to become things that people had seen by the beginning of the 1960s, I first saw a computer when I was ten years old, which was 1969 ish, and the time a computer was a very big thing tended by people in white coats and so on. So I first got my hands on a computer in 1972, and that was a computer that was the size of a large desk and program with paper tape and so on. And was rather primitive by today's standards, but
Used to be called Rubbish Boys. Your painting company also had a different name in the beginning. So what do you think about when you're naming your brands? What are the important elements to consider? Yeah. So I think it's naming the brands and what they look like. So let me start with Shack Shine as an example, and then I'm gonna tell you a 1 800 got junk story if I can. Yeah. So Shack Shine, similar type of situation as Wow one DAY PAINTING. How did I find the business? I was looking to get my gutters cleaned out. I found a company. It was difficult to find someone, but a friend introduced me to someone that was building this business called Shakhshan. I loved the business, saw the opportunity to also scale and grow it, and I like the name, the tongue in cheek sort of Shack Shine. You know, your home isn't really a shack, especially some of the ones that we wash windows for, but I didn't like the look and feel of the design of the logo. And so I said to Dave, who started the business, I said, if we were to partner together or acquire your business, I'd want to redesign the look and feel of your entire brand. Are you open to that? He said, yeah. I think I'd be open to it, and I don't know if he really was. We then went off and hired a designer before buying the company. Noel Fox comes in and completely redesigned and revamped the brand. I presented it to Dave, and Dave's like, man. We are doing a deal. He bought into how we repositioned the look and feel of his brand. So words and visuals are everything. How we represent ourselves to the world is incredibly important, and it needs to be consistent. So, again, the importance of branding, I'll I'll tell you a quick one eight hundred got junk story. We went from the rubbish boys to, I wanna expand out of Vancouver where I started the business. Mhmm. I was born in the United States. I wanted to expand into the United States, and I thought the word rubbish was more of a British Canadian term. Yeah. We had to come up with something different. And so our phone number at the time was 738 junk. And I said, what could we use in the United States?
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