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 ...

The race to build bigger AI models is giving way to a more urgent contest over where and how those models actually run. Nvidia's multibillion dollar move on Groq has crystallized a shift that has been ...

Join our daily and weekly newsletters for the latest updates and exclusive content on industry-leading AI coverage. Learn More Without inference, an artificial intelligence (AI) model is just math and ...

MemryX Inc., a company delivering production AI inference acceleration, today announced its strategic roadmap for the MX4.

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 ...

Machine learning inference models have been running on X86 server processors from the very beginning of the latest – and by far the most successful – AI revolution, and the techies that know both ...

Nvidia Acquires Groq Talent In A Strategic To Move Into AI Inference in order to expand its AI ecosystem and take over the ...

It was only a few months ago when waferscale compute pioneer Cerebras Systems was bragging that a handful of its WSE-3 engines lashed together could run circles around Nvidia GPU instances based on ...

In this distributed environment, connectivity becomes foundational—a layer of invisible fabric that ties everything together. And just as important is the software stack: Development needs to scale ...

The simplest definition is that training is about learning something, and inference is applying what has been learned to make predictions, generate answers and create original content. However, ...