The Latest News in AI

We publish news articles on Forbes, which are copied here for your convenience.  

My 2026 AI Predictions Have A Few Surprises

OK, I haven’t done this in a while; no excuse other than laziness. But here are ten concrete, defensible predictions for AI in 2026, with a bias toward things that materially matter for infra, enterprises, and policy. 1. Agentic AI moves from demos to staffed “digital...

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AI Training: “I’m Not Dead Yet!”

With so much focus on inference processing, it is easy to overlook the AI training market, which continues to drive gigawatts of AI computing capacity. The latest benchmarks show that the training of AI models, an immense investment in power and compute, continues to...

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Synopsys Announces New AI-Driven Solutions

Synopsys CEO Sassine Ghazi takes the stage for the first time as CEO at SNUG, joined by Nvidia CEO Jensen Huang to discuss the companies’ collaboration and much more. I never knew how close Synopsys and Nvidia were! Apparently, according to Jensen, Synopsys delivered...

Qualcomm AI Research Innovates 3D Perception Techniques

The trick of AI at the edge is reducing complexity while maintaining accuracy. And that takes a lot of primary research. When we explored the eight “AI Firsts” from Qualcomm AI Research earlier this year, it was clear to us the company’s full-stack approach to AI...

The Case for Hardware-Assisted Verification in Complex SoCs

This article was first published in EE Times. Synopsys recently launched two new hardware-assisted verification (HAV) systems, intended to address the need for specialized hardware to manage the complexity of modern chip design. In this article, we look at the...

A Look At Graphcore’s AI Software

Software for new processor designs is critical to enabling application deployment and optimizing performance. UK-based startup Graphcore, the unicorn provider of silicon for application acceleration, places significant emphasis on software, dedicating roughly half its...

NVIDIA Adds New Software That Can Double H100 Inference Performance

TensorRT-LLM adds a slew of new performance-enhancing features to all NVIDIA GPUs. Just ahead of the next round of MLPerf benchmarks, NVIDIA has announced a new TensorRT software for Large Language Models (LLMs) that can dramatically improve performance and efficiency...

Tenstorrent Could Reshape The AI And CPU Competitive Landscape

Now led by Jim Keller, the company has built a new leadership team and a new strategy. It has tremendous potential. Now it must execute. Introduction It is hard to believe the difference a year makes. In 2021, there were over 100 public and venture-backed startups...

The Age of Chiplets is Upon Us

The idea of chiplets is simple: develop the best semiconductors for the needed functions using the most proper manufacturing process. Then combine an assortment of chiplets on a multi-die package, and voila! A lower-cost approach to advanced semiconductors. The...

The NewReality: Fast Inference Processing For 90% Less?

Most of the investment buzz in AI hardware concentrates on the amazing accelerator chips that crunch the math required for neural networks, like Nvidia’s GPUs. But what about the rest of the story? CPUs and NICs that pre- and post-process the query add significant...

NVIDIA Needed A CPU, But Did It Need To Buy Arm To Get One?

I often opine that NVIDIA needs a data center-class CPU to compete with Intel and AMD, both of whom have used tightly-coupled CPU/GPU technology to win the first three U.S. exascale supercomputer deals. Connecting massive GPUs to fast CPUs over a painfully slow PCIe...

My 2026 AI Predictions Have A Few Surprises

OK, I haven’t done this in a while; no excuse other than laziness. But here are ten concrete, defensible predictions for AI in 2026, with a bias toward things that materially matter for infra, enterprises, and policy. 1. Agentic AI moves from demos to staffed “digital...