Anthropic had refused Pentagon demands that it remove safeguards on its Claude model that restrict its use for domestic mass surveillance or fully autonomous weapons, even as defense officials insisted that AI models must be available for “all lawful purposes.” The Pentagon, including Secretary of War Pete Hegseth, had warned Anthropic it could lose a contract worth up to $200 million if it did not comply. Altman has previously said OpenAI shares Anthropic’s “red lines” on limiting certain military uses of AI, underscoring that even as OpenAI negotiates with the U.S. government, it faces the same core tension now playing out publicly between Anthropic and the Pentagon.
Trade-offThe trade-off versus gVisor is that microVMs have higher per-instance overhead but stronger, hardware-enforced isolation. For CI systems and sandbox platforms where you create thousands of short-lived environments, the boot time and memory overhead add up. For long-lived, high-security workloads, the hardware boundary is worth it.
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The problem gets worse in pipelines. When you chain multiple transforms — say, parse, transform, then serialize — each TransformStream has its own internal readable and writable buffers. If implementers follow the spec strictly, data cascades through these buffers in a push-oriented fashion: the source pushes to transform A, which pushes to transform B, which pushes to transform C, each accumulating data in intermediate buffers before the final consumer has even started pulling. With three transforms, you can have six internal buffers filling up simultaneously.