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Hardware & Infrastructure

167 summarised stories in Hardware & Infrastructure, each linking back to the original source. Browse all topics →

Thursday, 16 July 2026

The AI compute gap: Enterprises are buying infrastructure faster than they can measure what it costs

VentureBeat AI 5 days ago 5 sources

Across 107 enterprises surveyed, AI infrastructure spending is accelerating faster than organizations can track its costs, with most unable to measure unit economics clearly despite rapid buying decisions. 83% of enterprises report GPU utilization of 50% or less, and only 44% can rigorously track what their AI compute costs, while 45% plan to evaluate AI-specialized cloud providers within the next year despite almost none using them today. The result is a compute gap where enterprises are investing aggressively in infrastructure they do not yet use while lacking visibility into the economics of what they already own, with 64% planning to switch or add infrastructure providers within twelve months.

Four MTIA Chips in Two Years: Scaling AI Experiences for Billions

Meta AI Blog

Meta is developing four successive generations of its custom MTIA AI chips scheduled for deployment between 2026 and 2027, expanding capabilities from ranking and recommendation tasks to generative AI workloads. From MTIA 300 to MTIA 500, high-bandwidth memory increases 4.5x and compute performance increases 25x within two years. The modular chiplet design allows Meta to ship new generations every six months while using the same physical infrastructure, reducing deployment friction compared to traditional chip development cycles.

What does 99.9% uptime mean for inference?

Together AI 5 days ago

Together AI explains what different uptime tiers (99%, 99.9%, 99.99%) actually require for AI inference services, mapping each to specific failure domains and architectural requirements. 99% requires node-level redundancy within a data center, 99.9% requires full data center failover with live traffic routing to both facilities, and 99.99% requires multi-region deployment with reserved failover capacity. Infrastructure ownership, continuous failover testing, and end-to-end observability determine whether providers can actually deliver their SLA claims when failures occur.

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