Google is responding to criticism of AI data center water use with a framework for replenishment, transparency, and site-specific cooling choices. Its commitments include returning more water than data centers consume by 2030, avoiding water-intensive cooling in stressed regions, funding local infrastructure, using alternatives like reclaimed wastewater, and annual disclosures. The core tension remains that saving water can increase electricity demand.
Astera Labs is expanding its Taiwan operations and cloud lab presence to deepen integration with local ecosystem partners. The company also says its Scorpio X switch chips are shipping, targeting interconnect bottlenecks in AI infrastructure. The announcement positions Taiwan as a key base for Astera Labs as it pursues the AI interconnect architecture market.
Microsoft used Build to present itself as both an AI platform and a first-party model lab, announcing seven MAI models across reasoning, code, image, transcription, and voice. The standout was MAI-Thinking-1, described as a 35B active MoE with 256K context and clean data lineage. The recap also ties the launches to GitHub Copilot, Windows agent runtime ambitions, Web IQ grounding APIs, Foundry distribution, and MAIA 200 hardware.
Dow presented its DOW™ Cooling Science platform at COMPUTEX TAIPEI 2026, highlighting high-performance silicone-based solutions. The platform targets thermal management challenges in AI data centers and advanced semiconductors as computing density rises. The announcement positions materials science as part of the broader AI infrastructure ecosystem, alongside industry collaboration under the “AI Together” theme.
South Korean chip startup Xcena raised a $135 million Series B at a $570 million valuation, bringing total funding to $185 million. The company argues AI inference is increasingly constrained by memory movement, not just GPU compute. Its prototype MX1 chip uses CXL to process data closer to DRAM, with Samsung foundry mass production planned by late 2026 and revenue targeted for 2027.
Snowflake reported stronger-than-expected results and raised its annual product revenue forecast as enterprise demand grows. The company signed a five-year, $6 billion AI infrastructure agreement with AWS, expanding a previously smaller commitment. It also acquired Natoma to strengthen AI agent governance, positioning itself as a core enterprise AI platform.
TechCrunch reports that large exchanges are developing derivative products around AI tokens. The shift reflects a changing view of tokens: less as outputs from computation and more as input commodities, comparable to electricity or bandwidth. If these products emerge, AI token futures could let companies and investors manage exposure to future AI compute demand and pricing risk.
Ars Technica reports that Nvidia will invest $150 billion annually to make Taiwan an AI “epicenter.” The headline frames the move against Trump’s effort to make the US an AI hub, suggesting the policy push may be backfiring. The provided source text does not specify investment targets, timeline, partners, or operational details, so the takeaway should remain focused on Nvidia’s strategic emphasis on Taiwan.
NVIDIA CEO Jensen Huang appeared at the site of the company’s planned new Taiwan headquarters in Beitou-Shilin. The building centers on a “transparent” design concept, using an all-glass curtain wall to symbolize trustworthiness. According to the report, construction is planned to begin by the end of 2026, with completion and opening expected in 2030.
Digital Infinite will exhibit AI-Stack and ixCSP at COMPUTEX 2026. AI-Stack focuses on managing heterogeneous AI compute resources, while ixCSP turns compute capacity into operable and billable cloud services. The article frames the company’s direction as moving from AI infrastructure toward cloud-based compute commercialization, though it does not provide benchmark data, pricing, customer deployments, or model-specific details.