English(EN) The hard part of reinforcement learning on a frontier model is the infrastructure that keeps training and inference numerically identical: zero KLD, end to end.

Fireworks AI 提供用于训练和推理一致性的托管基础设施

作者 PulseAugur 编辑部 · [1 个来源] · 2026-06-24 20:00

Fireworks AI 开发并提供了一项托管服务，用于在 Frontier 模型上进行强化学习的基础设施，以确保训练和推理之间的数值一致性。该解决方案解决了在整个过程中保持零 Kullback–Leibler 散度 (KLD) 的挑战，并首先支持 GLM-5.2。 AI

影响使 Frontier 模型能够进行更稳定、更可靠的强化学习，有可能提高其安全性和能力。

排序理由这是一个针对现有基础设施挑战的托管服务产品，而不是新的 Frontier 模型发布或核心研究。

在 X — Fireworks (inference infra) 阅读 →

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X — Fireworks (inference infra) TIER_1 English(EN) · FireworksAI_HQ · 2026-06-24 20:00

The hard part of reinforcement learning on a frontier model is the infrastructure that keeps training and inference numerically identical: zero KLD, end to end.

The hard part of reinforcement learning on a frontier model is the infrastructure that keeps training and inference numerically identical: zero KLD, end to end. We've solved this challenge, and are now offering it as a managed service, starting with GLM 5.2.

报道来源 [1]

The hard part of reinforcement learning on a frontier model is the infrastructure that keeps training and inference numerically identical: zero KLD, end to end.

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