This is still the dominant frame of thinking about machine learning and AI, at least across industry that has shifted a bit though. Some of these, what's called self supervised models started coming out. And now we're in this kind of wave of generative AI, which is the kind of first wave of AI that has really hit the public perception so widely. The idea being that there was kind of a maybe a first shift, and then a second shift that I've seen.
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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