GTP-4 integration will make NPCs in video games a whole lot more interesting
AI
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Domino Named Top 200 North American Tech Company Again
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We are honored to be included for the 2nd consecutive year among the top 200 premier North American technology companies, as rated by Deloitte's #Fast500 list. We're ever grateful to our amazing customers, without whom this wouldn’t be possible: https://
domino.buzz/3Ap2Ma3 #MLOps -
Nvidia forecasts in-line with Street, adapting to slowdown
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Nvidia’s forecast in-line with Street, says ‘quickly adapting’ to global economic slowdown // $NVDA $AMD $INTC $CSCO $ANET https://
thetechnologyletter.com/the-posts/nvid
ias-forecast-in-line-with-street-says-quickly-adapting-to-global-economic-slowdown
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Society Takes Longer Than Expected to Adopt Powerful AI
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(this is a little bit different than 'slow takeoff'–i think it will just take society longer to figure out what to really do with very powerful than intuition suggests)
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AGI Development Timeline and Delayed Societal Impact
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prediction: agi gets built sooner that most people think, and takes much longer to "change everything" that most people imagine
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DALL-E API Now Available in Public Beta
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DALL·E API in action 🎬
— Lilian Weng (@lilianweng) 16 novembre 2022
Ref: https://t.co/pwg5emm17f https://t.co/FSrxbd6ok2DALL·E API in action Ref: https://
openai.com/blog/dall-e-ap
i-now-available-in-public-beta/
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NFL Knowledge Gap, ML Speed, and Accuracy-Explainability Trade-offs
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Also:
1. The speaker in your paper doesn't know the NFL.
2. We can do even weak-knowledge ML a lot faster than evolution.
3. There's very often a tradeoff between accuracy and transparency/explainability, and often accuracy is more important. -
Tabula-Rasa Model Oxymoron: NFL Theorem and Fundamental Assumptions
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"Tabula-rasa model" is an oxymoron, by the NFL theorem. The question is what are the fundamental assumptions that need to be built in. Causality is a candidate. The laws of physics are another.
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Climate Models Replaced by Superior Alternative Method
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Who needs climate models now? This does the job much better.
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Learning Actions from Data Rather Than Building Them In
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We don't need to build it in, because it's very easy to learn from data (cf. infants). And we arguably shouldn't, because what your actions are can change (e.g., moving your hands vs. driving your car).