Roman Chernin is the CBO and cofounder of AI infrastructure company Nebius. His career spans over 20 years in the tech industry. Every major advance in AI begins with model training, but the ...

If you purchased AI servers within the past two years, your discussions likely centered on three core questions: GPU count, ...

Given the high costs and slow speed of training large language models (LLMs), there is an ongoing discussion about whether spending more compute cycles on inference can help improve the performance of ...

Since about 2020, AI has largely focused on training bigger and better models. Large language models (LLMs) ballooned from millions of parameters to trillions. This proved effective: The largest ...

Predictive, generative, and agentic AI are not successive generations. They coexist inside enterprise systems, each placing fundamentally different demands on the underlying compute infrastructure.

Forbes contributors publish independent expert analyses and insights. Dr. Lance B. Eliot is a world-renowned AI scientist and consultant. Inferences, love them or hate them. You decide. One thing that ...

Google announced that it will begin selling TPUs to select third-party data center operators, marking the company's formal entrance into the merchant AI accelerator market where Nvidia dominates. The ...

The CNCF is bullish about cloud-native computing working hand in glove with AI. AI inference is the technology that will make hundreds of billions for cloud-native companies. New kinds of AI-first ...

The standard guidelines for building large language models (LLMs) optimize only for training costs and ignore inference costs. This poses a challenge for real-world applications that use ...

Google Kubernetes Engine is moving from hype to hardened practice as teams chase lower latency, higher throughput and portability. In fact, the GKE inference conversation has moved away from ...