Presented by SolidigmLiquid cooling is rewriting the rules of AI infrastructure, but most deployments have not fully crossed the line. GPUs and CPUs have moved to liquid cooling, while storage has depended on airflow, creating an operationally inefficient hybrid architecture.What appears to be a pragmatic transition strategy is, in practice, a structural liability. “A hybrid cooling approach is an operationally inefficient situation,” explains Hardeep Singh, thermal-mechanical hardware team manager at Solidigm. “You’re paying for and maintaining two entirely separate, expensive cooling infrastructures, and could be exposed to the worst-of-both-world's problems.” While liquid cooling requires pumps, fluid manifolds, and coolant distribution units (CDUs), air-cooled components [...]
When Liquid AI, a startup founded by MIT computer scientists back in 2023, introduced its Liquid Foundation Models series 2 (LFM2) in July 2025, the pitch was straightforward: deliver the fastest on-d [...]
When an AI agent loses context mid-task because traditional storage can't keep pace with inference, it is not a model problem — it is a storage problem. At GTC 2026, Nvidia announced BlueField- [...]
Alembic Technologies has raised $145 million in Series B and growth funding at a valuation 13 times higher than its previous round, betting that the next competitive advantage in artificial intelligen [...]
Have you played around with the new iOS 26 yet? Here's how to download it on your iPhone if you haven't yet — once you do, you'll notice several new changes, including a clear design [...]