Nvidia has introduced the RTX Pro 5500, a workstation graphics card that shares its design with the GeForce RTX 5090 but offers far more video memory for AI workloads. The company is increasingly positioning gaming as a secondary part of its business. The card is aimed at professionals running large models locally.
Graphics card makers saw unusually strong unit sales in the second quarter, according to a market analysis. The uptick may be partly attributable to demand from AI computing facilities in China. The report does not specify which vendors or regions contributed most to the gain.
A widely discussed piece argues that Nvidia occupies a position in the AI economy comparable to a central bank, because access to its chips effectively sets the terms for who can build and scale large models. The comparison highlights how dependent labs, cloud providers, and startups have become on a single supplier for training hardware. It is an analytical argument rather than a report of a specific corporate or regulatory development.
A new arXiv paper examines the "job power elasticity" of large language model training, looking at how much these workloads can adjust their electricity consumption. Power supply is described as a key constraint on the growth of AI data centers, which are among the fastest-rising sources of electricity demand. The work aims to characterize how training jobs could respond to power limits.
Massachusetts has approved new clean energy requirements for data center operators, making it the third US state to tighten rules on such facilities within a few months. The measures add to a growing set of state-level restrictions on data center growth, driven largely by rising power demand from AI workloads.