I'm with @JeffDean on this. DistBelief taught us early important lessons about scaling up deep learning, and it was general enough for many algorithms including supervised backprop. Obviously, we got a lot of software and hardware architecture details "wrong" back in 2012 —
COMPUTING
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AI-Optimized Data Warehouses: Performance, Governance, and Usability
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#AI can address the data warehouse's biggest challenges — performance, governance, and usability — with data intelligence. Join us for our upcoming virtual even to dive into the details of AI-optimized data warehouses https://
dbricks.co/3TN5y1L -
Virginia Tech AutoDrive Uses Simulation for Autonomous Vehicle Development
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Learn how the Virginia Tech AutoDrive team used simulation to replicate real-world scenarios and gained valuable insights from the process http://
spr.ly/6019jT9Yc #AutoDrive #ADAS #Simulink -
DistBelief Distributed Training System Framework Comparison
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DistBelief is the distributed training system used for that paper & 1000s of other things. Your statement is equivalent to implementing an unsupervised algorithm in PyTorch, seeing modest results (like 70% relative improvement in SoTA on Imagenet 20k) & declaring PyTorch a dead
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CPU GPU TPU support evolution in machine learning framework
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(Initial version supported CPUs. Later versions added support for GPUs and TPUs).
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Supervised ConvNets Scale Better With Smaller Parameter Count
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Supervised convnets worked just fine with disbelief (in fact they scale better because of the smaller parameter count). For example: https://
papers.nips.cc/paper_files/pa
per/2013/hash/7cce53cf90577442771720a370c3c723-Abstract.html
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EU Digital Ambassadors Discuss AI, Chips, and Quantum Innovation
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When 23 digital EU ambassadors meet in Brussels, what do they talk about? #ArtificialIntelligence #chips #semiconductor #quantum #innovation #technology #digitaleu @DigitalEU @ArturHabant @elaniaz @PawlowskiMario @JolaBurnett @BetaMoroney @CurieuxExplorer @Shi4Tech @enilev… pic.twitter.com/uI9SNFncRH
— Nicolas Babin (@Nicochan33) 4 mai 2024When 23 digital EU ambassadors meet in Brussels, what do they talk about? #ArtificialIntelligence #chips #semiconductor #quantum #innovation #technology #digitaleu @DigitalEU @ArturHabant @elaniaz @PawlowskiMario @JolaBurnett @BetaMoroney @CurieuxExplorer @Shi4Tech @enilev
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CUDA and C++ Origins Behind AlexNet’s Deep Learning Revolution
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# CUDA/C++ origins of Deep Learning Fun fact many people might have heard about the ImageNet / AlexNet moment of 2012, and the deep learning revolution it started. https://
en.wikipedia.org/wiki/AlexNet What's maybe a bit less known is that the code backing this winning submission to the -
Stanford Archives and Computer People for Peace: Historical Computing Resources
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The archives at Stanford are well worth the visit. Computer People for Peace is also worth checking on.
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Fused Classifier Kernel: Algorithmic Improvement Beyond Torch Compile
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this is exactly what we're doing in the fused classifier kernel, and this is an *algorithmic* improvement on top of today's torch compile, which doesn't do this