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English(EN) Polymorphic Inference: self-tuning inference for open models

Together AI发布多态推理,实现AI模型自适应部署

Together AI推出了一项名为多态推理(Polymorphic Inference)的新研究议程,旨在应对AI模型、架构和硬件的快速演变。这种方法与适用于不那么动态环境的传统静态推理(Static Inference)形成对比。多态推理旨在创建自适应推理系统,这些系统可以利用AI代理和持续编译(Continuous Compilation)等技术不断进行自我优化,以应对开源模型发布速度的加快和多样化的流量形态。 AI

影响 这种方法可能带来更高效、更自适应的AI推理,这对于应对新模型发布的快速步伐和不断发展的硬件至关重要。

排序理由 该条目描述了AI推理系统的新研究议程和技术方法。[lever_c_demoted from research: ic=1 ai=1.0]

在 Together AI blog 阅读 →

AI 生成摘要 · Google Gemini · 来自 1 个来源。 我们如何撰写摘要 →

Together AI发布多态推理,实现AI模型自适应部署

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该条目描述了AI推理系统的新研究议程和技术方法。[lever_c_demoted from research: ic=1 ai=1.0]
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完整方法见我们的编辑标准。

报道来源 [1]

  1. Together AI blog TIER_1 English(EN) ·

    多态推理:开源模型的自适应推理

    Models, traffic and chips are constantly changing. Polymorphic Inference adapts to each, and Together Compiler uses AI agents to keep production inference tuned.