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AI training method exceeds GPT-3 performance with fewer parameters

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Re: AI training method exceeds GPT-3 performance with fewer parameters

#6

GPT3's strength is on language generation, so using *GLUE for evaluating it (where encoder type models are just better) and claiming to have 99.9% less parameters is sensationalism.

Yes, it can do simple yes/no questions but can it write dad jokes like GPT-3?

Re: AI training method exceeds GPT-3 performance with fewer parameters

#7

GPT3's strength is on language generation, so using *GLUE for evaluating it (where encoder type models are just better) and claiming to have 99.9% less parameters is sensationalism.

That's kind of like saying that this super cheap SUV from 2003 is a better off-roader than the latest Ferrari. Like, true statement, but vacuous none the less.

Re: AI training method exceeds GPT-3 performance with fewer parameters

#8
If you want to read the source, I recommend skipping to their follow-up paper (same authors): https://arxiv.org/abs/2009.07118

Edit: tangentially related but for those who like to have a glance from their phone, arxiv-vanity is great instead of squinting at a pdf: https://www.arxiv-vanity.com/papers/2009.07118/

Re: AI training method exceeds GPT-3 performance with fewer parameters

#10
post #6

GPT3's strength is on language generation, so using *GLUE for evaluating it (where encoder type models are just better) and claiming to have 99.9% less parameters is sensationalism.

Yes, it can do simple yes/no questions but can it write dad jokes like GPT-3?

For me another question is crucial: is it open (i.e. is there an open source reference implementation) or closed like the so-called "OpenAI" products/services?
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