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Making deep learning go brrrr from first principles (2022)

horace.io

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Re: Making deep learning go brrrr from first principles (2022)

#7
post #4

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H.He has some overlap with the EAI community which has more crab-bucket tendencies when picking topics and/or mocking other groups. Even the more positive sentiments seem to be somehow crab-bucketed a bit (and, bizarrely at least to me, a large amount of politicking).

I'll visit there occasionally, but it's just too toxic a sphere for me to want to contribute research to. I get an itchy feeling whenever I try to seriously investigate an opportunity for contributing open source research in that group.

Re: Making deep learning go brrrr from first principles (2022)

#8

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Great point about Sutton's law. I always use Hinton's Capsule Networks as an example of an algorithm that may work in theory, but doesn't scale on existing hardware, due it's voting stage, which is not parallelizable on existing hardware accelerators.

Re: Making deep learning go brrrr from first principles (2022)

#9

[flagged]

Great point about Sutton's law. I always use Hinton's Capsule Networks as an example of an algorithm that may work in theory, but doesn't scale on existing hardware, due it's voting stage, which is not parallelizable on existing hardware accelerators.

That's a great point, I hadn't really thought about that a lot, and definitely had not made the hard connection.

I do love how he continues to spin out new potential modalities for Deep Learning. While underrecognized due to the hype today, I think we darn well need far more of it these days! :D :))))

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