Nvidia

A new cloud-computing company promises to provide scarce AI processing power to startups and researchers. Voltage Park, a nonprofit north of Silicon Valley, will offer processing power from 24,000 top-of-the-line Nvidia H100 graphics processing units (GPUs)...

An upstart supplier of AI chips secured a major customer. Cerebras, which competes with Nvidia in hardware for training large models, signed a $100 million contract with Abu Dhabi tech conglomerate G42. The deal is the first part of a multi-stage plan to build a network of supercomputers.

Nvidia’s top-of-the-line chips are in high demand and short supply. There aren’t enough H100 graphics processing units (GPUs) to meet the crush of demand brought on by the vogue for generative AI, VentureBeat reported.

The next generation of video games could be filled with AI-generated text, speech, characters, and background art. Nvidia announced a system that enables players to converse directly with in-game characters. Meanwhile, game developers are using generative AI to produce media assets.

Chinese companies have found loopholes to sidestep United States limits on AI chips. Facing severe limits on U.S. exports of high-performance chips, Chinese AI firms are purchasing them through subsidiaries and using them through cloud services, the Financial Times reported.

Typical text-to-image generators can generate pictures of a cat, but not your cat. That’s because it’s hard to describe in a text prompt precisely all the things that distinguish your pet from other members of the same species.

Given a number of images of the same scene, a neural network can synthesize images from novel vantage points, but it can take hours to train. A new approach cuts training time to a few minutes.

Advanced AI requires advanced hardware. What if the global supply of high-end AI chips dries up? Most of the world’s advanced AI processors are manufactured in Taiwan, where tension with mainland China is rising.

New U.S. restrictions on chip sales aim to hamper China’s AI efforts. The U.S. government published sweeping limits on sales of processors that involve U.S. designs and technology to Chinese businesses. U.S. officials stated that the restrictions are meant to prevent China from militarizing AI.

Nvidia, known for chips designed to process AI systems, is providing access to large language models. Nvidia announced early access to NeMo LLM and BioNeMo, cloud-computing services that enable developers to generate text and biological sequences respectively.

The ban impacts Nvidia's A100 and H100 chips, and AMD's MI250.

Is your colossal text generator bogged down in training? Nvidia announced a chip designed to accelerate the transformer architecture, the basis of large language models such as GPT-3.

I believe that natural language processing in 2022 will re-embrace symbolic reasoning, harmonizing it with the statistical operation of modern neural networks. Let me explain what I mean by this.

The trend toward ever-larger models crossed the threshold from immense to ginormous. Google kicked off 2021 with Switch Transformer, the first published work to exceed a trillion parameters, weighing in at 1.6 trillion.

DeepMind released three papers that push the boundaries — and examine the issues — of large language models.