跳到正文
只看一手#未经AI处理
4月21日周二
  5. OpenAI News

    Scaling Codex to enterprises worldwide

    【RSS 原文 · 未经 AI 筛选或翻译】OpenAI launches Codex Labs, partners with with Accenture, PwC, Infosys, and others to help enterprises deploy and scale Codex across the software development lifecycle, and hits 4M Codex WAU.

4月20日周一
  1. Berkeley AI Research

    Gradient-based Planning for World Models at Longer Horizons

    【RSS 原文 · 未经 AI 筛选或翻译】GRASP is a new gradient-based planner for learned dynamics (a “world model”) that makes long-horizon planning practical by (1) lifting the trajectory into virtual states so optimization is parallel across time, (2) adding stochasticity directly to the state iterates for exploration, and (3) reshaping gradients so actions get clean signals while we avoid brittle “state-input” gradients through high-dimensional vision models. Large, learned world models are becoming increasingly capable. They can predict long sequences of future observations in high-dimensional visual spaces and generalize across tasks in ways that were difficult to imagine a few years ago. As these models scale, they start to look less like task-specific predictors and more like general-purpose simulators. But having a powerful predictive model is not the same as being able to use it effectively for control/learning/planning. In practice, long-horizon planning with modern world models remains fragile: optimization becomes ill-conditioned, non-greedy structure creates bad local minima, and high-dimensional latent spaces introduce subtle failure modes. In this blog post, I describe the problems that motivated this project and our approach to address them: why planning with modern world models can be surprisingly fragile, why long horizons are the real stress test, and what we changed to make gradient-based planning much more robust. This blog post discusses work done with Mike Rabbat, Aditi Krishnapriyan, Yann LeCun, and Amir Bar (* denotes equal advisorship), where we propose GRASP. What is a world model? These days, the term “world model” is quite overloaded, and depending on the context can either mean an explicit dynamics model or some implicit, reliable internal state that a generative model relies on (e.g. when an LLM generates chess moves, whether

4月16日周四
  3. OpenAI News

    Codex for (almost) everything

    【RSS 原文 · 未经 AI 筛选或翻译】The updated Codex app for macOS and Windows adds computer use, in-app browsing, image generation, memory, and plugins to accelerate developer workflows.

4月15日周三
4月14日周二
4月13日周一
4月10日周五
  1. OpenAI News

    ChatGPT for marketing teams

    【RSS 原文 · 未经 AI 筛选或翻译】Learn how marketing teams use ChatGPT to plan campaigns, create content, analyze performance, and turn insights into action with practical AI workflows.

  3. OpenAI News

    AI fundamentals

    【RSS 原文 · 未经 AI 筛选或翻译】Learn what AI is, how it works, and how tools like ChatGPT use large language models. A clear, beginner-friendly guide to understanding artificial intelligence.

  4. OpenAI News

    Personalizing ChatGPT

    【RSS 原文 · 未经 AI 筛选或翻译】Learn how to personalize ChatGPT using custom instructions and memory to get more relevant, consistent, and tailored responses.

  8. OpenAI News

    ChatGPT for research

    【RSS 原文 · 未经 AI 筛选或翻译】Learn how to use ChatGPT for research to gather sources, analyze information, and create structured, citation-backed insights.

  11. OpenAI News

    Research with ChatGPT

    【RSS 原文 · 未经 AI 筛选或翻译】Learn how to research with ChatGPT using search and deep research to find up-to-date information, analyze sources, and generate structured insights.

  13. OpenAI News

    Using skills

    【RSS 原文 · 未经 AI 筛选或翻译】Learn how to create and use ChatGPT skills to build reusable workflows, automate recurring tasks, and ensure consistent, high-quality outputs.

  14. OpenAI News

    Healthcare

    【RSS 原文 · 未经 AI 筛选或翻译】Explore how clinicians use ChatGPT to support diagnosis, documentation, and patient care with secure, HIPAA-compliant AI tools.