Every ChatGPT query, every AI agent action, every generated video is based on inference. Training a model is a one-time ...

We all have the habit of trying to guess the killer in a movie before the big reveal. That’s us making inferences. It’s what happens when your brain connects the dots without being told everything ...

The next generation of inference platforms must evolve to address all three layers. The goal is not only to serve models efficiently, but also to provide robust developer workflows, lifecycle ...

Edge AI is the physical nexus with the real world. It runs in real time, often on tight power and size budgets. Connectivity becomes increasingly important as we start to see more autonomous systems ...

“I get asked all the time what I think about training versus inference – I'm telling you all to stop talking about training versus inference.” So declared OpenAI VP Peter Hoeschele at Oracle’s 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 ...

A.I. chip, Maia 200, calling it “the most efficient inference system” the company has ever built. The Satya Nadella -led tech ...

AI inference demand is at an inflection point, positioning Advanced Micro Devices, Inc. for significant data center and AI revenue growth in coming years. AMD’s MI300-series GPUs, ecosystem advances, ...

AI/ML training traditionally has been performed using floating point data formats, primarily because that is what was available. But this usually isn’t a viable option for inference on the edge, where ...