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Task-specific optimization in multimodal models can significantly boost performance by dynamically reallocating shared computation resources between vision and language components.
Verification of coding agent outputs is now the bottleneck, not generation, and targeted design can significantly enhance performance while curbing reward hacking.
Foundation models may excel at forecasting, but their accuracy doesn't always translate to better resource allocation decisions in cloud environments.
