if I understand your strategy, it is attacked all the innovations of OpenAi to do your own advertising through social networks and to market your recent book. it's not honest.
robust language understanding is about building discourse models across multiple sentences (see eg http://rebooting.ai & recent thread by @mpshanahan)
on simple word problems like these, GPT-2 did not succeed once in 30 min testing
my 6-yr old son scored 100%pic.twitter.com/FLN31mdhcU
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False. - I have been pushng same key points for 30 years, book is only a few mo old. see eg https://www.newyorker.com/news/news-desk/is-deep-learning-a-revolution-in-artificial-intelligence … - Note
@mpshanahan reached exactly same conclusions, doesn't have a book to promote. - 3 more replies
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zero shot is hard! gpt2 isnt really designed for this, even though the larger models can sometimes succeed in some zero shot tasks.
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Yes, but that's his point. Humans are exceptionally good at zero-shot, where regression is poor/unpredictable. That's indicative that humans are using different methods, at least for higher-level learning.
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To be fair you're using the half-sized model to generate these not the full thing
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I love the idea of using word problems. I look forward to seeing some kind of standard scale of difficulty, with important psychological concepts as benchmarks along the way.
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What’s the difference between learning statistical properties of a dataset and understanding?
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Time.
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@GaryMarcus@mpshanahan Well said. Build domain discourse models for specific domains or for document types (news, research papers, legal documents etc) types. Also need deep linguistic learning to accompany that (Coref, pragmatics, decompose doc into its themes, etc).Thanks. Twitter will use this to make your timeline better. UndoUndo
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