Processors

A new computing cluster delivers more bang per chip. Cerebras unveiled Andromeda, a supercomputer based on its processors. Unlike conventional clusters, the system’s processing speed rises linearly with additional processors.

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.

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

The hardware that runs the latest AI systems faces rising uncertainty as models grow larger and more computationally intensive. The U.S. Commerce Department sounded an alarm over bottlenecks in the availability of semiconductor chips.

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.

Google designed its own AI chip for its new smartphone — a snub to Qualcomm, the dominant chip vendor in Android phones. What’s new: Google debuted the Tensor chip last week

After years of trailing other tech giants in AI, Apple has a new ambition: to become the industry’s leading purveyor of products powered by machine learning. In an interview with Ars Technica, the company’s AI chief argues that its pro-privacy.

A neural network wrote the blueprint for upcoming computer chips that will accelerate deep learning itself. Google engineers used a reinforcement learning system to arrange the billions of minuscule transistors in an upcoming version of its Tensor Processing Unit (TPU) chips.

Large transformer networks work wonders with natural language, but they require enormous amounts of computation. New research slashes processor cycles without compromising performance.

A major corporate acquisition could reshape the hardware that makes AI tick.What’s new: U.S. processor giant Nvidia, the world’s leading vendor of the graphics processing units (GPUs) that perform calculations for deep learning, struck a deal to purchase UK chip designer Arm for $40 billion.

Chips specially designed for AI are becoming much faster at training neural networks, judging from recent trials. MLPerf, an organization that’s developing standards for hardware performance in machine learning tasks, released results from its third benchmark competition.

A high-profile semiconductor startup made a bid for the future of AI computation. UK startup Graphcore released the Colossus Mk2, a processor intended to perform the matrix math calculations at the heart of deep learning more efficiently than other specialized processors.

From server to smartphone, devices with less processing speed and memory require smaller networks. Instead of building and training separate models to run on a variety of hardware, a new approach trains a single network that can be adapted to any device.

Quantum computing has made great strides in recent years, though it still faces significant challenges. If and when it gets here, machine learning may be ready for it.

Many of this year’s hottest AI companies are taking the spotlight from last year’s darlings.What’s new: CB Insights, which analyzes early-stage companies, published its annual list of the 100 “most promising” startups in AI.