Nvidia’s CEO Jensen Huang expects 100+ trillion parameter models by 2023

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Last month Nvidia CEO Jensen Huang during the GTC 2021 keynote claimed that he expects 100+ trillion parameter models by 2023 (the chart that was part of his presentation shows we could even see a 1000 trillion parameter model in 2023!). This is an extraordinary claim. Also last month Microsoft announced ZeRo-Infinity which represents progress toward training large models with trillions of parameters. Even if Huang is wrong and we… Read More »Nvidia’s CEO Jensen Huang expects 100+ trillion parameter models by 2023

Putting the AI in Retail: Walmart’s Grant Gelvin on Prediction Analytics at Supercenter Scale

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With only one U.S. state without a Walmart supercenter — and over 4,600 stores across the country — the retail giant’s prediction analytics work with data on an enormous scale. Grant Gelven, a machine learning engineer at Walmart Global Tech, joined NVIDIA AI Podcast host Noah Kravitz for the latest episode of the AI Podcast. Gelven spoke about the big data and machine learning methods making it possible to improve… Read More »Putting the AI in Retail: Walmart’s Grant Gelvin on Prediction Analytics at Supercenter Scale

Charles Simon, Author of Brain Simulator II – Interview Series

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Charles Simon is the Author of Brain Simulator II, a companion book to the Brain Simulator II, a free, open source software project aimed at creating an end-to-end Artificial General Intelligence (AGI) system The original Brain Simulator software was released in 1988, an enormity of time in the software world. How much of a leap forward is Brain Simulator II compared to its predecessor? Today’s system is over a million… Read More »Charles Simon, Author of Brain Simulator II – Interview Series

When is GPT-4 planned for completion?

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Is it planned for release in 2021? Are there any predictions for how much better GPT-4 will be compared to GPT-3? submitted by /u/Bovba [link] [comments]

[R] Twitter Tech Lead Michael Bronstein & Team Leverage the Erlangen Programme to Establish the Geometric Foundations of Deep Learning

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A team led by Imperial College Professor and Twitter Chief Scientist Michael Bronstein publishes a paper that aims to geometrically unify the typical architectures of CNNs, GNNs, LSTMs, Transformers, etc. from the perspective of symmetry and invariance to build an “Erlangen Programme” for deep neural networks. Here is a quick read: Twitter Tech Lead Michael Bronstein & Team Leverage the Erlangen Programme to Establish the Geometric Foundations of Deep Learning.… Read More »[R] Twitter Tech Lead Michael Bronstein & Team Leverage the Erlangen Programme to Establish the Geometric Foundations of Deep Learning