I co-created Graph Neural Networks while at Stanford. I recognized early on that this technology was incredibly powerful.

Desert Neural Network Transformers are the basis for Tesla FSD. Neural Network Transformers continually improve with more and more data. Tesla FSD now has over 2 million cars gathering data and ...

Unlike recurrent neural networks (RNNs) or convolutional neural networks (CNNs), transformer networks do not rely on sequential processing, enabling parallelization and faster training.

Artificial Intelligence is a fascinating yet complex field, and many people don’t truly understand it until they see it in ...

Abstract: “Recent advances in deep learning have been driven by ever-increasing model sizes, with networks growing to millions or even billions of parameters. Such enormous models call for fast and ...

While large Transformer neural networks have been fed gigabytes and gigabytes of text data, the amount of data in images or video or audio files, or point clouds, is potentially vastly larger.

Through an Ising machine, which combines a mixture of quantum and classical computing, SoftBank sought to calculate optimal settings on base stations supporting a 5G network – which resulted in a 10% ...