Discussion

• @jwangark James Wang on x

  1. Moore's Law lives! Nvidia's new 54 billion transistor GPU continues the march of Moore's Law, tho costs are no longer staying constant. 2. In 2020, the world's #1 chip is from a ‘gaming’ company and #2 chip is from a ‘web retailer’. How the leaderboard has changed.. https://tw…

• @etherealmind @etherealmind on x

  Couple of things about this keynote 1. Its from a kitchen, with the obvious “baking something” cheap gag. 2. there are no customers involved. 3. its less than 15 minutes long. This might be the perfect keynote for virtual events. cc @jtroyer https://twitter.com/...

• @libertyrpf Liberty on x

  “A data center powered by five DGX A100 systems for AI training & inference running on just 28 kilowatts costing $1m can do the work of a data center with 50 DGX-1 systems for AI training and 600 CPU systems consuming 630 kilowatts & costing over $11m” https://blogs.nvidia.com/..…

• @nvidia @nvidia on x

  Announcing the new NVIDIA Ampere Architecture, designed to be the heart of the elastic data center of the future: https://nvidianews.nvidia.com/ ... #GTC20

• @nvidiaembedded NVIDIA Embedded on x

  Announcing the new @NVIDIA Jetson Xavier NX Developer Kit with 10X the power of Jetson TX2 and cloud-native support. Its unique combination of size, performance and power opens the door for bringing new #AI products to market fast! Buy now. https://www.nvidia.com/... #JetsonNX ht…

• @benbajarin Ben Bajarin on x

  In data center accellerators, NVIDIA has ~65% share in Azure, AWS, and GCP. When it comes to deep learning training NVIDIA is the standard. https://twitter.com/...

• @gavinsbaker Gavin Baker on x

  1) Is Ampere being 20x better than Volta good or bad for all of the AI silicon startups that are “10x” better than Volta on a single algorithm on one framework? 😀 Especially given that *none* of them except Habana have posted the 10x results on MLPerf. https://venturebeat.com/...