People focus on whether the existing generative models, as we're now calling them all the time, are leading us into kind of artificial general intelligence. I'm more worried about humans orchestrating a bunch of powerful tools and maybe automating those tools in such a way that the tool keeps going. You could imagine if, again, these models are essentially generating output that's probable. They don't know anything about reality or intent or anything like that. There's no knowledge there. It's just completion. So they could complete someone's request saying, well, how should I fix this issue with my airplane or helicopter? And the model could say, well, just take that part off. It
Chris and Daniel take a step back to look at how generative AI fits into the wider landscape of ML/AI and data science. They talk through the differences in how one approaches “traditional” supervised learning and how practitioners are approaching generative AI based solutions (such as those using Midjourney or GPT family models). Finally, they talk through the risk and compliance implications of generative AI, which was in the news this week in the EU.
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