As enterprises seek alternatives to concentrated GPU markets, demonstrations of production-grade performance with diverse ...

Researchers propose low-latency topologies and processing-in-network as memory and interconnect bottlenecks threaten inference economic viability ...

Smaller models, lightweight frameworks, specialized hardware, and other innovations are bringing AI out of the cloud and into ...

The multibillion-dollar deal shows how the growing importance of inference is changing the way AI data centers are designed ...

The AI hardware landscape continues to evolve at a breakneck speed, and memory technology is rapidly becoming a defining ...

For years, it seemed obvious that the best way to scale up artificial intelligence models was to throw more upfront computing resources at them. The theory was that performance improvements are ...

Rubin is expected to speed AI inference and use less AI training resources than its predecessor, Nvidia Blackwell, as tech ...

Over the past several years, the lion’s share of artificial intelligence (AI) investment has poured into training infrastructure—massive clusters designed to crunch through oceans of data, where speed ...

DDN today announced deep collaboration with NVIDIA to support the company’s next-generation AI factory architecture unveiled ...

In recent years, the big money has flowed toward LLMs and training; but this year, the emphasis is shifting toward AI ...

Inference is rapidly emerging as the next major frontier in artificial intelligence (AI). Historically, the AI development and deployment focus has been overwhelmingly on training with approximately ...

Nvidia’s $20 billion strategic licensing deal with Groq represents one of the first clear moves in a four-front fight over the future AI stack. 2026 is when that fight becomes obvious to enterprise ...