Lenny Rachitsky: evaluation

Transcript context

…ar way of dictionarying words. And we combine that into ImageNet and we open-sourced that to the research community. We held an annual ImageNet challenge to encourage everybody to participate in this. We continue to do our own research, but 2012 was the moment that many people think was the beginning of the deep learning or birth of modern AI because a group of Toronto researchers led by Professor Geoff Hinton, participated in ImageNet Challenge, used ImageNet big data and two GPUs from NVIDIA and created successfully the first neural network algorithm that can... It didn't totally solve, but made a huge progress towards solving the problem of object recognition. And that combination of the trio technology, big data, neural network, and GPU was kind of the golden recipe for modern AI. And then fast-forward, the public moment of AI, which is the ChatGPT moment, if you look at the ingredients of what brought ChatGPT to the world technically still use these three ingredients. Now, it's internet-scale data mostly texts is a much more complex neural network architecture than 2012, but it's still neural network and a lot more GPUs, but it's still GPUs. So these three ingredients are still at the core of modern AI. Incredible. I have never heard that full story before. I love that it was two GPUs was the first. I love that. And now it's, I don't know, hundreds of thousands, right, that are orders of magnitude more powerful. Yep.…

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