Japanese entrepreneur, investor and SoftBank founder
A wave of tests and product launches shows the tech industry pressing to give AI a physical form. From gig-data data collection to consumer humanoids, firms are racing to turn digital intelligence into real-world Lab-to-life tools.
SoftBank has announced a €75bn plan to build AI data centres in northern France and to develop up to 5GW of capacity by 2031. Governments and companies are tightening domestic energy plans in response, prompting talks on interconnectors, local refineries and nuclear or modular-reactor options to meet the data centres’ huge electricity demand.
The Insolvency Service has disqualified Lex Greensill from directing UK companies for nine years after finding he breached his duties as a director; the action follows the 2021 collapse of Greensill Capital and related investigations.
Galleries have been shrinking and business models have been under sustained pressure at Art Basel this month, while major players have been narrowing investments and reshaping portfolios across regions. SoftBank has reduced deal activity in Latin America; Pace has cut artists and staff; recruitment firm Hays has sold operations; and community art projects and private collectors are adapting their approaches.
Federal regulators have issued orders to regional grid operators to speed connections for large data centers while requiring transparency and rules to prevent ratepayers from subsidising grid upgrades. Tech firms and energy officials are defending faster hookups and new cooling tech; communities and experts are warning about water, electricity and local costs as data‑center buildouts surge.
SoftBank founder Masayoshi Son has argued data centers in space offer little cost benefit and that the AI race will be decided by Earth-based compute. He cites power costs, transport, and delays as barriers to orbital data centers, while emphasising the ongoing importance of on-Earth infrastructure.
The AI industry has reached a tipping point as hyperscalers project rising returns from chips and data centers. New analyses forecast trillions in 2026 revenue to justify the AI build-out, even as token costs and cheaper models pressure profitability.