Reading up on CoreWeave

The AI infrastructure buildout could require $7.5 trillion in spending by 2030, creating trillions in enterprise value for neoclouds like CoreWeave and Nebius.

GPU rental prices surged 48% in 60 days, signaling an AI compute shortage that will reshape startup competition and access to frontier models.

Giving Karpathy's autoresearch agent access to 16 GPUs enabled 9x faster optimization by running experiments in parallel and enabling factorial grid searches.

AI disruption threatens to compress software revenue, putting at risk the $475 billion in BDC loans and highly-leveraged data-center debt built on that revenue's durability.

GPUs are being financialized as a new asset class through debt securitization, derivatives, and tokenization, despite rapid obsolescence threatening traditional financial infrastructure.

LMCache is a vendor-neutral KV cache management layer that reduces time-to-first-token and improves throughput for LLM inference by enabling persistent storage and reuse of cached states.

AI inference infrastructure is bifurcating into reserved compute platforms, which monetize predictability, and inference APIs, which monetize utilization through aggregation.

Rapid GPU upgrade cycles threaten to make hyperscalers' hardware unprofitable, creating a financial crisis from accelerated depreciation and risky loans.