Logan Kilpatrick: belief

Transcript context

…This is for the builders out there. What's an AI thing you would pay for if someone built it with their personal work? I think more stuff around like transfer learning for, like making transfer, learning easier. Like I think that's truly the way to. Build really cool things is transfer learning, fine tuning, and I, I don't think that there's enough. Jeremy Howard who created Fasted AI talks a lot about this. I mean, it's something that really resonates with me and, and for context, like at Apple, all the machine learning stuff that we did was transfer learning because it was so powerful. And I think people have this perception that they need to. Build things from scratch and that's not the case. And I think especially as large language models become more accessible, people need to build layers and products on top of this to make transfer learning more accessible to more people. So hopefully somebody builds something like that and we can all train our own models. I think that's how you get like that personalized AI experiences you put in your stuff. Make transfer learning easy. Everyone wins. Just just to vector in a little bit on this. So in the stable diffusion community, there's a lot of practice of like, I'll fine tune a custom dis of stable diffusion and share it. And then there also, there's also this concept of, well, first it was textual inversion and then dream booth where you essentially train a concept that you can sort of add on. Is that what you're thinking about when you talk about transfer learning or is that something…

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