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Forget disjointed pipelines and structured inputs: PlanAudio uses an LLM and semantic latent chain-of-thought to directly synthesize unified audio from free-form text prompts.
LLMs can be sped up by over 2x without sacrificing accuracy, by compressing the input and predicting multiple output tokens at once using a unified framework.
Despite advances in AI, the best models struggle to match even a third of human performance in real-world video post-production tasks.
Autonomous ML research agents achieve significantly better long-horizon performance by maintaining durable state through a shared workspace, suggesting that orchestration and memory are more critical than raw reasoning power.