The focus of artificial-intelligence spending has gone from training models to using them. Here’s how to understand the ...

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 ...

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 ...

As the AI infrastructure market evolves, we’ve been hearing a lot more about AI inference—the last step in the AI technology infrastructure chain to deliver fine-tuned answers to the prompts given to ...

These tech stocks look particularly well positioned to benefit from this opportunity.

“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 ...

Ahead of Nvidia Corp.’s GTC 2026 this week, we reiterate our thesis that the center of gravity in artificial intelligence is ...

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 ...

Nvidia just paid $20 billion for Groq's inference technology in what is the semiconductor giant's largest deal ever. The question is: Why would the company that already dominates AI training pay this ...

Demand for artificial intelligence (AI) inferencing is a game changer for Nvidia.