An AI masterclass with Hayden Smith from Pearler
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What is the main topic discussed in this episode?
I think it is as profound as they say. I think it is just going to change everything. Like you can essentially largely, as these models get better, replace most of the work that professional service people are doing in Australia. Four out of ten Australians that are employed. It's life changing.
We're just talking about like building this amazing vehicle that's like a million times safer than anyone driving. And they're trying to take all these dumb cat videos and memes and just shit talking online. And they're like, hmm, what are we going to make from this? If you want to know how AI actually works and whether you should invest in it or a part of it, we call that the supply chain. This is the episode for you. I'm joined by Chief Technology Officer at Perla, Hayden Smith, who just told me that he's been teaching computer science for nine or 10 years. And we're going to talk about each different part of what makes an AI like ChatGPT or Claude actually work. And then we're going to drop down into the different parts of that whole supply chain and figure out what companies do what bit and why does that matter?
Can I make money from that? That's what we're going to be talking about in this episode where we talk about LLMs, AI, and talk about all the hardware that goes in, ETFs, and the companies behind this mega trend. All that and more in this episode of the podcast. Welcome to the Australian Finance Podcast by Rask. Together, we will improve your relationship with money, discover the world of investing, save more money, and design the life you want. Please don't forget to subscribe to the show on Apple, Spotify, YouTube, or wherever you get your podcasts because we share at least two wonderful episodes every week. You should know that our favorite episodes drop on a Monday and a Friday with bonuses on Wednesdays.
Finally, to hear more from us and get show notes and all those other wonderful things like free courses, head to rask.com.au to find us online. Now, Hayden, I just said in the hook that you have been teaching computer science for quite a while. True or false?
Yeah, it has been. I started teaching in 2013. 2013. Yeah, a while ago now.
So, you're kind of like in these glory years of like There was the time before AI and then there's the time after AI. Yeah. But there are events that happened even just in this time of you teaching that have been remarkably important to where we are today and then where we're going.
Yes.
We're going to start this episode with what had to take place in order to get to where we are. And then we're going to try and as we go through the episode, identify the companies and maybe then some of the ETFs that people might be investing in to get exposure to either all of this trend or part of this trend. My first question to you is very simple. When people say AI, artificial intelligence, what do they actually mean?
What is it? Oh, it's a pretty nothing term, honestly. It's like it describes when a computer system gives the impression that it's intelligent, like a human, that it's more than just, you know, cogs and levers, but it seems to... demonstrate whatever the hell you would call intelligence. It's not anything technical. You know, things like machine learning have technical descriptions.
Well, that was going to be my next question. It's like, what is the difference between AI, air quotes, and things like these other phrases, machine learning, deep learning, and generative AI? Like, what are the differences? Feel free to use examples.
AI is a word like, you know, good governance or, you know, it's not like a technical thing you could point to. It's just like... an outcome, big philosophical thing. Machine learning is something that's been around for a long time. In fact, I was working with this really old guy a few years ago and he was the second university medalist back in like the 60s or 70s at my uni. And he said to me, I'm so sick of people talking about machine learning. He's like, we were doing machine learning back then. And machine learning is basically mathematics.
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