
本期信号从产品功能转向基础设施:OpenAI 同日开源安全 CLI、推出两款转写 API 模型,并公开讨论前沿模型发展速度与科学计算 Agent 的责任边界。
More opensource goodness. We have just released a CLI and TypeScript SDK for finding, validating, and fixing security vulnerabilities in your code. Scan repositories, review changes, track findings over time, and run security checks in CI.中文翻译:又一个开源成果。我们刚刚发布了一个 CLI 和 TypeScript SDK,用于发现、验证和修复代码中的安全漏洞。它可以扫描代码仓库、审查变更、跨多次运行追踪发现结果,并在 CI 中执行安全检查。
We're introducing two new transcription models in the API:• GPT-Live-Transcribe: built for low-latency live transcription. • GPT-Transcribe: optimized for asynchronous transcription of completed audio files and batch workloads.Both models better understand context and deliver more accurate transcription on real world audio across accents and languages, including for short phrases, numbers, specialized terminology, and speech with loud background noise.中文翻译:我们正在 API 中推出两款新的转写模型:GPT-Live-Transcribe 面向低延迟实时转写;GPT-Transcribe 面向已完成音频文件的异步转写和批处理。两款模型都能更好地理解上下文,并在不同口音和语言的真实音频中提高准确度,尤其覆盖短语、数字、专业术语和嘈杂背景下的语音。
At the core of our mission is working through how to ensure increasingly powerful AI benefits everyone.We believe that, at some point in the future, AI acceleration for frontier model development may be so high that the world will need to pace the rate of AI advancement.We hope to contribute to work led by the U.S. government, alongside other labs and the open-source community, to develop the tools and mechanisms that could make that possible.中文翻译:我们使命的核心,是思考如何确保日益强大的 AI 造福所有人。我们认为,在未来某个时点,前沿模型开发的加速速度可能高到世界需要控制 AI 进步的节奏。我们希望与其他实验室和开源社区一起,为美国政府主导的工作贡献力量,开发出能够实现这一目标的工具和机制。
Across eight case studies spanning industry and academia, we explore what this shift means for scientific computing—and why human verification, stewardship, and long-term maintenance matter. https://t.co/LmZurP9NME中文翻译:我们通过覆盖产业界和学术界的八个案例,考察这一转变对科学计算意味着什么,以及为什么人工验证、负责维护和长期维护仍然重要。
| 模型 | 官方定位 | Context Aware ASR 语义准确率 | 公开错误率对比 |
|---|---|---|---|
| GPT-Live-Transcribe | 低延迟实时转写 | 38.5% → 44.6% | Common Voice 19.70%,对比 GPT-Realtime-Whisper-1 的 20.33% |
| GPT-Transcribe | 异步文件转写与批处理 | 41.6% → 45.2% | Common Voice 19.27%,对比 Whisper 的 40.37% |
npm install @OpenAI/codex-security 与 npx @OpenAI/codex-security@latest --help。14x.com
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