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English(EN) New podcast with @finbarrtimbers! We survey the latest post-training recipes, from GLM 5.1, Kimi K2.6, DeepSeek V4, Xiaomi MiMo V2.5, Nemotron Ultra, etc. and d

AI模型:训练后技巧与未来趋势探讨

新一期播客节目中,Nathan Lambert和Finbarr Timbers讨论了AI模型训练后技术的最新进展。对话涵盖了行业向多教师策略内蒸馏的转变、Olmo风格技巧的应用,以及训练后技术对大规模AI工作的广泛影响。节目还涉及快速发展的AI领域内的职业建议,回顾了GLM 5.1、Kimi K2.6、DeepSeek V4、Xiaomi MiMo V2.5和Nemotron Ultra等模型。 AI

影响 为AI研究人员和开发人员提供了对当前AI模型训练方法和未来趋势的见解。

排序理由 讨论AI模型训练技术和职业建议的播客。

在 X — Nathan Lambert (Interconnects) 阅读 →

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

AI模型:训练后技巧与未来趋势探讨

本文如何被排名

Signal score
0 / 100
Composite score across the factors below. Higher = stronger signal that this story matters right now.
Newsworthiness bucket
Commentary
讨论AI模型训练技术和职业建议的播客。
Source corroboration
Single-source cluster
Only one publisher covered this so far. Single-source stories can still rank when the publisher is high-authority, but they lack cross-source corroboration.
Topics
model release, opinion
Editorial topic classification. Feeds into how the story surfaces on /topic/<slug> hub pages and into the per-entity coverage mix.
AI-industry relevance
High
Clearly on-topic for AI-industry coverage.
Story freshness
105 days old
Aged out of breaking-news scoring windows; ranking reflects the durable signal from the full source set.

完整方法见我们的编辑标准。

报道来源 [1]

  1. X — Nathan Lambert (Interconnects) TIER_1 English(EN) · natolambert ·

    与@finbarrtimbers的最新播客!我们回顾了最新的训练后技术,包括GLM 5.1、Kimi K2.6、DeepSeek V4、Xiaomi MiMo V2.5、Nemotron Ultra等。

    New podcast with @finbarrtimbers! We survey the latest post-training recipes, from GLM 5.1, Kimi K2.6, DeepSeek V4, Xiaomi MiMo V2.5, Nemotron Ultra, etc. and discuss: - Why the industry slowly shifted to multi-teacher on-policy distillation (MOPD). - What an Olmo-style recipe ht…