As artificial intelligence companies clamor to build ever-growing large language models, AI infrastructure spending by Microsoft (NASDAQ:MSFT), Amazon Web Services (NASDAQ:AMZN), Google ...

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, ...

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

If GenAI is going to go mainstream and not just be a bubble that helps prop up the global economy for a couple of years, AI ...

Nvidia is aiming to dramatically accelerate and optimize the deployment of generative AI large language models (LLMs) with a new approach to delivering models for rapid inference. At Nvidia GTC today, ...

Everyone is not just talking about AI inference processing; they are doing it. Analyst firm Gartner released a new report this week forecasting that global generative AI spending will hit $644 billion ...

‘People are running out of inferencing capacity,’ Oracle CTO and co-founder Larry Ellison said. Oracle missed expectations for its latest quarterly performance but blew away analysts with $455 billion ...

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 ...

Forbes contributors publish independent expert analyses and insights. Victor Dey is an analyst and writer covering AI and emerging tech. As OpenAI, Google, and other tech giants chase ever-larger ...

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 ...