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We’re sharing how GLM-5.3 helped build and optimize the inference infrastructure serving GLM-5.3-Flash. The system went from its first successful run to production readiness in less than two weeks, with end-to-end throughput tripling relative to the initial baseline. The key was dense feedback: local correctness tests, execution traces, microbenchmarks, and end-to-end measurements that enabled targeted hypothesis testing rather than reliance on aggregate performance metrics alone. https://t.co/yUf6OpJD7c

什么在构成我 HumanInterFace 02｜ZHGO｜创意系列｜GPT Images 2.5 https://t.co/2FJ5WgiWla https://t.co/R0jKP4hRSw

We're sharing our new framework for tracking, investigating, and disclosing instances of model misalignment at OpenAI. The framework sets criteria and timelines for public disclosure, including when we haven’t yet fully explained or mitigated the behavior. More complex cases may require longer investigation or coordination with third parties. We’ll prioritize examples that reveal new misalignment mechanisms, meaningful changes in known behavior, or findings that challenge assumptions about safety or mitigation. Alongside the framework, we’re publishing six reports on instances of misaligned behavior we’ve observed during the training or evaluation of our models in the last six months. This is a starting point. We’ll refine the process through experience and public feedback, and share more reports on an ongoing basis. https://t.co/ismCCkeE0L

什么在构成我 HumanInterFace 02｜ZHGO｜创意系列｜GPT Images 2.5 https://t.co/2FJ5WgiWla https://t.co/R0jKP4hRSw