Karl Freund

In the world of quantum computing, some of the world's most important tech giants are striving to achieve a permanent advantage over classical

If you are worried about Nvidia's ability to maintain its lead, worry no more. Nvidia's got this.

Karl Freund, Contributor 9 min read Nvidia's updated Roadmap is based on GPUs, LPUs, CPUs, NPUs, and networking chips. Nvidia

The just-released quarterly MLPerf benchmarks provided an update from AMD and Nvidia. AMD finally beat the B300, just barely, but only on a small model few still run.

Infleqtion is one of the leaders in applying the neutral atom modality to quantum computing delivering room-temperature scalable quantum computing.

Cadence and Nvidia have teamed to present the first example of Level 5 AI EDA agent to automate the work of design verification, turning a months-long effort into 1 day.

By using log math, Tensordyne can replace multiplications with additions, resulting in better than 10X performance and energy efficiency over GPUs and other ASICs

Tensordyne has unveiled the Napier processor, an AI accelerator leveraging 16th-century logarithmic math to revolutionize inference. By converting complex multiplication into simpler addition, this air-cooled system significantly boosts efficiency, claiming a 17-fold performance-per-watt improvement over Nvidia's GB300 for DeepSeek-R1 inference. Designed specifically for LLMs, the Napier processor features a two-tiered memory architecture and offers substantial cost savings. A single Tensordyne rack delivers 1300 tokens per second for a 2T MoE model at 120kW, costing just $11 per million tokens, starkly outperforming Nvidia/Groq's 800 TPS at 1.5MW and $150. This innovative, lower-cost solution is poised to attract major hyperscalers and data centers seeking efficient AI infrastructure.

The rise of Agentic AI, capable of setting goals and executing multi-step tasks, is fundamentally altering AI infrastructure requirements. Unlike traditional generative AI, these proactive systems demand ultra-low latency and consume far more tokens, pushing the CPU from a mere support role to a critical orchestrator of complex workflows. This shift is expected to quadruple CPU core demand in data centers, driving a need for highly efficient, hybrid computing across devices, edge, and cloud. Qualcomm is strategically positioning itself to capitalize on this, leveraging its mobile and edge strengths. Its "DragonFly" platform, an "efficiency-first" inference solution for data centers, promises superior performance per watt through advanced memory and liquid cooling, aiming to make agentic AI affordable and scalable despite Qualcomm's late entry into the data center market.

Qualcomm is gearing up to transform itself into an Agentic AI Infrastructure company. We look into what that means, and its upcoming DragonFly AI Server chip