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// ai hardware

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theme-connectedinfrastructuredata centersai hardware

VAST Data bets KV cache storage becomes AI's new bottleneck

Source: SiliconANGLE

The shift from training to inference-heavy AI workloads is creating a storage crisis at a specific, previously overlooked layer: the key-value caches that LLMs need to keep in memory during token generation. VAST's pivot here reflects real infrastructure pain—companies building AI systems are hitting memory limits faster than compute limits, and traditional cloud storage can't handle the random-access patterns required. Specialist vendors are now hunting the exabyte-scale cache market that didn't exist two years ago. Whoever controls the cache layer owns a critical chokepoint in AI deployment, much as GPU makers owned compute bottlenecks.

theme-connectedinfrastructurecapital allocationai hardware

AI Infrastructure's Missing Piece: Access to Capital

Source: SiliconANGLE

Argentum's positioning exposes a real bottleneck in the AI buildout: while chip manufacturers and power companies have captured industry focus and venture capital, the financing layer itself has become the actual constraint. The company is essentially selling access to capital markets and financial structures as infrastructure, targeting the LPs and institutions writing the largest checks rather than the technologists—a play that only works if data center operators and chip buyers are actually capital-constrained, not just capital-hungry.

theme-connecteddata centersinfrastructureai hardware

SpaceX's Colossus Data Center Wasn't Ready for Grok

Source: The Next Web

SpaceX built Colossus 1 as a dedicated training facility for Grok but couldn't operationalize it in time, so rented the idle infrastructure to Anthropic instead of sitting on unused capacity. Custom-built AI data centers remain brittle—hardware procurement and deployment still outpace the software and operational maturity needed to run them profitably. Even well-capitalized infrastructure plays like SpaceX monetize transitional periods rather than absorb the overhead, a rational calculus in the current AI buildout cycle.