Cloud AI Inference Workload Capacity Consumption to Surpass Training by 2033, Reaching 46 GW by 2035

Enterprise AI deployment is shifting cloud economics from model building to production-scale inference, with code generation emerging as the biggest long-term demand driverNEW YORK, May 21, 2026 ...

How RecursiveMAS speeds up multi-agent inference by 2.4x and reduces token usage by 75%

UIUC and Stanford's RecursiveMAS lets AI agents collaborate in embedding space instead of text, cutting token usage by 75% ...
VentureBeat

How Snowflake's open-source text-to-SQL and Arctic inference models solve enterprise AI's two biggest deployment headaches

Snowflake has thousands of enterprise customers who use the company's data and AI technologies. Though many issues with generative AI are solved, there is still lots of room for improvement. Two such ...
Semiconductor Engineering

A Comprehensive Guide to Understanding AI Inference on the CPU

As AI continues to revolutionize industries, new workloads, like generative AI, inspire new use cases, the demand for efficient and scalable AI-based solutions has never been greater. While training ...