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Definitely engineering. It’s not entirely wrong to say that the two reasons it took us until 2022 to make a ChatGPT are 1) the computing power needed and 2) the
by Sharlin 3y ago
Definitely engineering. It’s not entirely wrong to say that the two reasons it took us until 2022 to make a ChatGPT are 1) the computing power needed and 2) the size of the training corpus needed. The same goes for other generative AI – it took a corpus of a couple billion images to train a Stable Diffusion model.
- amelius 3y agoYou may argue that it took a leap of insight to get to transformer models, though.
- charcircuit 3y agoThat was not an innovation of ChatGPT.
- mannykannot 3y agoIt's pretty clear that ChatGPT is being used here as a synecdoche for recent LLMs, and transformer LLMs in particular.
- idontpost 3y ago[dead]
- charcircuit 3y ago"Transformer is All You Need" is from 6 years ago. It isn't an advancement that happened last year.