Post by Ben Seipel, University of Wisconsin-River Falls/California State University, Chico; with Gina Biancarosa, University of Oregon; Sarah E. Carlson, Georgia State University; and Mark L. Davison, ...
A food fight erupted at the AI HW Summit earlier this year, where three companies all claimed to offer the fastest AI processing. All were faster than GPUs. Now Cerebras has claimed insanely fast AI ...
AI inference uses trained data to enable models to make deductions and decisions. Effective AI inference results in quicker and more accurate model responses. Evaluating AI inference focuses on speed, ...
The major cloud builders and their hyperscaler brethren – in many cases, one company acts like both a cloud and a hyperscaler – have made their technology choices when it comes to deploying AI ...
You train the model once, but you run it every day. Making sure your model has business context and guardrails to guarantee reliability is more valuable than fussing over LLMs. We’re years into the ...
Educators face urgent questions around misinformation, academic integrity, and critical thinking around AI. Visual literacy ...
Google expects an explosion in demand for AI inference computing capacity. The company's new Ironwood TPUs are designed to be fast and efficient for AI inference workloads. With a decade of AI chip ...
AMD is strategically positioned to dominate the rapidly growing AI inference market, which could be 10x larger than training by 2030. The MI300X's memory advantage and ROCm's ecosystem progress make ...
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