The computational demands of training and deploying sophisticated artificial intelligence have forced a fundamental re-evaluation of how global data centers are constructed and managed by industry leaders. Meta Platforms Inc. has solidified its commitment to this new era by entering into a massive,
Maryanne Baines has spent years in the trenches of cloud evaluations, picking apart provider stacks, testing platform behaviors under stress, and guiding public-sector teams from policy to production. With the European Commission’s sovereign cloud tender—worth up to €180 million over six years—now
Lead: A Sharper Question About AI Scale Budgets shifted, data maps sprawled, and a tougher question cut through the noise: who truly commands AI at enterprise scale when chips, models, data, and power constraints collide in the same boardroom conversation? On stage at Next, Google Cloud offered an
Boardrooms are louder now as AI PC pilots give way to rollouts that promise faster work, lower latency, and tighter data control while forcing hard choices on budgets, skills, and governance. That shift has pushed the conversation from curiosity to execution: who gains, how fast, and at what cost.
Trading desks and risk teams kept hitting a wall: petabyte-scale data pipelines ballooned cloud bills while overnight jobs crept into trading hours, and a single ad hoc query could idle analysts for minutes as CSVs slogged across object storage. That bottleneck framed the appeal of Delta Parquet,
Regulators did not wait for collaboration vendors to catch up, and UK enterprises with cross-border exposure increasingly demanded unambiguous proof that meeting recordings, chat logs, call metadata, and AI outputs stayed within national boundaries. That pressure culminated in a notable change:
