Matt Bornstein

Elena Burger × Matt Bornstein × Simon Mo

vLLM has become the execution layer linking more than 1,000 open-weight model architectures to GPUs from NVIDIA, AMD, Google, Amazon, Intel, and others, making inference a strategic systems layer.Open weights increasingly offer controllable latency, data, security, and fine-tuning rather than merely cheaper tokens, while licensing and moderation pressures test whether the ecosystem can fund frontier development and trusted specialized use cases.

Naveen Rao × Matt Bornstein

Unconventional is pursuing physical learning circuits, arguing that analog dynamics could complement digital computing for stochastic, time-dependent workloads rather than simply extend matrix multiplication.The thesis targets an energy wall: U.S. data centers use roughly 4% of the national grid, while some estimates call for 400 additional gigawatts over the next decade.Commercial significance depends on finding a manufacturable paradigm within five years, with TSMC partnership, a potentially very large analog prototype and unresolved AGI claims creating major execution risk.

Erik Torenberg × Martin Casado × Jennifer Li × Matt Bornstein

AI is becoming a fourth infrastructure pillar that changes chips, data centers, distribution, and the programming model by letting applications abdicate logic to models.Context engineering, embedded integration, and switching costs may create defensibility, while objective error correction makes coding agents commercially ahead of open-ended automation.