AI Frontier Review

Agentic serving and model-internal computation raise systems questions

Agentic serving and model-internal computation raise systems questions

TAO jointly schedules LLM inference around tool readiness, cache value, and token footprint, reporting up to 26.8% lower latency and 29.5% higher decode throughput across 12 settings; deployment impact depends on workload and baseline validation. A separate report of a RISC-V CPU compiled into Qwen 3.5 weights is an intriguing model-computation result, but its claims need independent reproduction.

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Updated Oct 29, 2026
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