I would argue Schmidhuber is taking credit away from the work that we actually built on. Everyone is aware of Schmidhuber’s accusations, few are aware I spent a significant amount of time working on NCE and talking with its authors.
RESEARCH
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Causal Analysis and Machine Learning Book for R Statistics
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A book in #Econometrics and #Statistics: "Causal Analysis: Impact Evaluation & Causal #MachineLearning with Applications in R" at http://
amzn.to/45ngdEG
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#Rstats #DataScience #ML #AI #StatisticalLiteracy #Economics #Finance #DataScientist #PrescriptiveAnalytics #Causality -
Comprehensive Machine Learning Guide for Finance and Algorithmic Trading
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Comprehensive guide to applying #MachineLearning in #Finance: https://
github.com/mfrdixon/ML_Fi
nance_Codes
… by Matthew F. Dixon
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…includes some chapters (PDF) from his book: http://
amzn.to/3BHA47J
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#AlgorithmicTrading #Fintech #ML #DataScience #Statistics #Quant #DataScientist -
Public video shows interruption during 2016 AI talk
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The video of him interrupting my 2016 talk is also public, and you don’t have to take my word for it that that’s him. He doesn’t mention artificial curiosity, just predictability minimization.
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Schmidhuber’s GAN Paper Review and Predictability Minimization Citation
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Schmidhuber was a reviewer of the GAN paper in 2014. The reviews are public. He is the reviewer that asked us to cite predictability minimization. He did not ask us to cite artificial creativity (his current complaint). He hadn’t thought of that even in 2016.
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Academic Credit in AI Research: Schmidhuber’s Role in GAN Development
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When Schmidhuber interrupted my talk on GANs in 2016, he did so at the time I was giving credit to relevant prior work: noise contrastive estimation. Schmidhuber isn’t about proper about academic credit assignment, he’s about self-aggrandizement.
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Sequence Models for Contextual Recommendations at Instacart
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Sequence models for Contextual Recommendations at Instacart https://
bit.ly/3ZbHqsc
#AI #MachineLearning #DeepLearning #LLMs #DataScience -
Compute and Data: Post-Training Data as the Next Frontier
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compute matters, but so does data. pre-training data wall -> post-training data boom @scale_AI is the data foundry that will accelerate us out of this rut
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Seq2seq Architecture: A Decade of Evolution in Deep Learning
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seq2seq 10 years later. 💙@ilyasut @quocleix. Talk 👇 https://t.co/fqZI0SXdN0 pic.twitter.com/Q5le02u1fE
— Oriol Vinyals (@OriolVinyalsML) 14 décembre 2024seq2seq 10 years later. @ilyasut @quocleix
. Talk -
AlphaFold Becomes Standard Tool for 2M+ Researchers Globally
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It was also amazing to hear how, along with 2 million+ researchers around the world, Academy members and other Nobel laureates have been making use of AlphaFold in a myriad ways in their pioneering work. It has truly become a standard tool in biological and medical research.