I'm still a bit surprised that you think the system (DistBelief) that first combined large scale model- and data- parallelism with backprop-based training of very large neural nets is a "dead end", given that nearly every large-scale model that is trained today combines these
RESEARCH
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DistBelief convolutions development shared weights 2012
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We supported shared weights from very early in DistBelief development, and we started adding support for various kinds of convolutions in March of 2012 (because convolutions are a very sensible idea for some things!), and you visited in July, I believe.
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DistBelief Convolutions Backpropagation Training Before ICML 2012
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DistBelief supported convolutions and end-to-end training with convolutions via backprop before the ICML 2012 paper appeared (even though that particular paper didn't use convolutions).
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Mapping the Mind: Speech Production Understanding Advances
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Mapping The Mind: Advances In Understanding Speech Production https://
forbes.com/sites/williamh
aseltine/2024/04/08/mapping-the-mind-advances-in-understanding-speech-production/?utm_source=dlvr.it&utm_medium=twitter
… #Innovation #ArtificialIntelligence #MachineLearning -
Matrix Classes and Neural Networks: From BPTT to Modern Frameworks
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In the 90s I had to first implement matrix classes before I could even start coding neural nets – it was awful! I suffered so much with BPTT! Matlab did make things more efficient and was great until Python arrived. Leon Bottou and Yann Lecun pioneered SGD and torch style
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Python and C++ in Computer Science Education Since 2005
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There is a record. We started using python for teaching in 2008 (
https://
cs.ubc.ca/~nando/340-200
8/index.html
…) but the team was on if from around 2005. Of course, some people still preferred matlab (eg @sirbayes who still loves it ). Our MoE work (PAQ8) around 2008 was all on C++ because of -
Automatic Differentiation Frameworks Revolutionized Machine Learning Development
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To be honest, Geoff still uses Matlab and that is how we got dropout and distillation. I think software frameworks based on automatic differentiation (eg torch) changed the game, but whether it was lua, matlab or python seemed to matter less. Granted I prefer python and indeed my
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DeepMind scientist advancing mathematics with AI technology
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Alex @SashaVNovikov is by far one of the brightest scientists I know, and his @GoogleDeepMind team is making impactful and fascinating contributions to advancing mathematics with AI. Highly recommend it!
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AI Pioneer’s Book Available at Discounted Kindle Price
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Some of you can get my book “The Worlds I See: Curiosity, Exploration and Discovery at the Dawn of AI” for $1.99 on Kindle now – it’s a limited promotion!
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Scaling Deep Learning: The Controversial Path to AI Performance
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Back then, the idea that scaling deep learning would lead to significant performance gains was controversial. Several senior academic colleagues were advising me not to waste time trying to scale deep learning, but to just focus on inventing new algorithms, which was where they