It's 3 AM and Fable 5 just solved a bug for me that I've been struggling with for a week, impossible to find on an adversarial PPO training where the gradient was becoming almost zero… Well, it fixed it. And it also increased my parallelism to 4,557 steps/env/s.
RESEARCH
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Claude Fable makes testing other models feel pointless
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Testing models for other labs just feels completely pointless now after trying Claude Fable. Genuinely feels like a waste of time… this model is just so above and beyond incredible. Hats off to the Anthropic team.
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Concentration of power, capabilities, wealth in AI: open source needed
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The concentration of power, capabilities, and economic wealth is the greatest risk in AI. We need open science and open source more than ever!
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Claude Fable 5 Hints Future AI Competition Key Is Capability Boundary Design
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Claude Fable 5 这次最值得看，不只是“更强模型发布”。
— 艾略特 (@elliotchen100) 10 juin 2026
而是 Anthropic 开始把最前沿能力拆成两层：大众可用的 Fable，加安全分类器；受信任场景里的 Mythos，开放更少限制。
AI 产品接下来竞争的关键，可能会从“谁的模型最强”，变成“谁能把能力、风险和分发边界设计清楚”。 https://t.co/t8vlcSB4KVClaude Fable 5 is the most noteworthy this time, not just because of a 'stronger model release'.
Rather, it's that Anthropic has started splitting cutting-edge capabilities into two layers: Fable, available to the public with a safety classifier; and Mythos, used in trusted scenarios with fewer restrictions.
The key to future AI product competition may shift from 'whose model is strongest' to 'who can clearly design the boundaries of capabilities, risks, and distribution'. -
Disappointment at Anthropic’s silent degradation of Fable 5
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As advocates of open research, we are disappointed to see Anthropic silently degrading Fable 5 for AI development. "Any topic related to building pre-training pipelines, distributed training infrastructure, or the design
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XGBoost for Regression, Predictive Modeling, and Time Series Analysis Book Review
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XGBoost for Regression, Predictive Modeling, and Time Series Analysis — Learn how to build, evaluate, & deploy predictive models: http://
amzn.to/4l2YcU9 v/ @PacktDataML —
My review: XGBoost is definitely the focal point and central contribution of this book, along with all -
Larger base model capacity improves training data memorization
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Yes, because the base model has far more capacity than all the previous ones, so it's better at memorizing the training dataset.
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Gemini 3.5 Pro and GPT-5.6 near release; Anthropic frontier lab
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It's already June 9th, and Gemini 3.5 Pro and GPT-5.6 are nearing release (Google even already announced 3.5 Pro during i/o) Rumor has it that GPT-5.6 will be released as early as next week. So far, it's safe to say that – guardrails aside – Anthropic is truly the frontier lab
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Debate on AI reasoning: Marcus hopes for Dwarkesh response
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what constitutes reasoning in AI is a critical debate. i hope that @dwarkesh_sp will respond.
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On-Policy Distillation geometry: fewer weight updates, preserves structure
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“On the Geometry of On-Policy Distillation” OPD is not just SFT mixed with RLVR. It has its own update geometry. This paper shows that OPD updates fewer weights than SFT and preserves pretrained structure better, while staying less constrained than RLVR. The key finding is