Well diffusers are trained unsupervised on raw pictures. I don't know how they train multi-modal LLMs on images, but yes obviously they are consuming other media than just text. I don't think, but would be happy to be corrected, that models glean much of their "knowledge" from non-textual training data.
> Fridman, the podcast’s host, defines AGI as an AI system that’s able to “essentially do your job,” as in start, grow, and run a successful tech company worth more than $1 billion. He then asks Huang when he believes AGI will be real — asking if it’s, say, five, 10, 15, or 20 years away — and Huang responds, “I think it’s now. I think we’ve achieved AGI.”
> But Huang then seemed to slightly walk back his earlier claims, saying, “A lot of people use it for a couple of months and it kind of dies away. Now, the odds of 100,000 of those agents building Nvidia is zero percent.”
I was thinking the same thing, that this wouldn't necessarily be a bad thing. I'm curious how far it will go.. if we'll get invite-only mesh networks with self-contained mini-internets and the like.
>My hairdresser knew all about it and had ordered a Mac mini.
Your hairdresser can't be a technical person because they're a hairdresser ?? I know a surgeon who writes FOSS software as a hobby. What does profession have to do with being technical or not? Most technical people are self taught anyway.
I know them very well, and they are not a coder, or a 'technical person' by a broad HN definition.
What I'm saying is that we are at the point where technology is so pervasive in our society, and the lure of AI so seductive, that many more people are excited to try things out than I might have expected.
I suppose it has similarities to the early to mid 1980s and the home computing revolution. Where many people thought they should have a computer at home, even if they were not sure what they'd do with it.
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