RESEARCH

→ View original post on X — @marcusborba

Comprehensive Guide to Machine Learning Free Book

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@marcusborba

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04 December 2022 3h57

Free Book: A Comprehensive Guide to #MachineLearning http://
bit.ly/2AAidka #AI #NeuralNetworks #TensorFlow #Algorithms #Programming #Python #ML #100DaysOfCode #javascript #linux #cloud #serverless #BigData #Analytics #womenwhocode #devcommunity #DataScience #DeepLearning

World Models and Reinforcement Learning in Control Theory

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04 December 2022 3h16

Agree with the last one, but we still work on a lot of reinforcement learning, because our world models are not present/perfect. @SahinLale is working at the intersection of learning and control. Check out his work for excellent theoretical background as well as empirical results

Generative AI Essential for Concept Learning Beyond Art Creation

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04 December 2022 3h14

Strongly disagree with the first one. "What I cannot create I cannot understand" – Richard Feynman. Generative AI is not just for creating fun art, it is at the core of concept learning.

→ View original post on X — @esyudkowsky

ChatGPT programmers lack epistemics and advance predictions

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@esyudkowsky

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04 December 2022 3h11

By default, I would guess that if the people programming ChatGPT responses do not even think to ask 'But is that actually true?', then the company does not have a secret internal committee where everyone has great epistemics and wrote down advance predictions.

→ View original post on X — @esyudkowsky

OpenAI could prove advance knowledge through hashed predictions

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@esyudkowsky

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04 December 2022 3h09

Well, they could always make the predictions internally, publish a hash somewhere unobtrusive but time-stamped, swear me to secrecy on the specific contents, show me the impolite internal prediction, and have me say publicly, "Sorry! I'm convinced OpenAI knew in advance."

→ View original post on X — @fchollet

Learning and Refining Semantic Categories from Single Instances

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@fchollet

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04 December 2022 2h39

Learn a word based on a single instance (e.g. this particular airplane = word "airplane"), then use the word to refer to a broad category of related things (all flying things are now airplanes), then gradually refine semantic categories (helicopters, dirigibles…)

AI for Science as True Test of AI Capabilities

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04 December 2022 2h30

I believe @AI_for_Science is a true test of #AI capabilities. While generating realistic text or images can be fun to play with, more controlled tests of #AI is easier with scientific domains where we have more concrete metrics and objectives to measure

AI for Science Community Growth at NeurIPS22

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04 December 2022 2h27

So pleased to see @AI_for_Science community grow at #NeurIPS22 When we founded AI for science initiative at @caltech in 2018, it was still considered niche. I want to thank organizers of @AI_for_Science workshop, especially student organizers who put in so much time and effort.