GoPlus「Web3鬼故事」第二期 | 警惕「美女大佬」杀猪盘

长文源：区块律动Publicado em 2002-08-24Última atualização em 2024-08-02

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OpenAI Completely Overhauls Codex, Grows Its Own Mouse, Schedules Itself to Outwork Humans

OpenAI has fundamentally transformed Codex from a coding assistant into a versatile AI agent capable of autonomous computer control. The updated Codex can now operate in the background with its own independent cursor, allowing it to run applications like Xcode, test software, and fix bugs without interrupting the user’s workflow. It features a built-in browser for real-time visual editing of web pages, enabling developers to make changes through direct UI interactions. The release also introduces over 90 plugins for tools like JIRA, CircleCI, and SharePoint, integrating end-to-end development and productivity workflows. A new "heartbeat" feature allows Codex to self-schedule tasks, maintain context across sessions, and work autonomously over extended periods. Additional enhancements include memory capabilities, support for handling GitHub code reviews, multi-tab terminals, and built-in file generation for Excel, PDF, and PowerPoint. Currently, advanced computer control is available on macOS (excluding EU/UK users), with Windows support limited to data retrieval. This expansion positions Codex as a foundational step toward OpenAI’s planned "super-app," combining coding, automation, and multi-tool integration into a single platform.

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Bitcoin Recovery Fails To Lift Market Sentiment From Extreme Fear

Despite Bitcoin's recent recovery to around $74,800, the overall market sentiment remains in "extreme fear," according to the Crypto Fear & Greed Index. The index, which measures investor sentiment based on factors like volatility, social media, and trading volume, is at a value of 23, just inside the extreme fear zone. This marks a continued period of bearish sentiment since late 2025. Although Bitcoin's rally provided a brief uplift in mid-March, the current price movement has not been enough to shift market psychology into a more positive or greedy territory. For sentiment to improve, a sustained bullish momentum may be required.

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World Models Shift from Prediction to Planning: HWM and the Challenge of Long-Horizon Control

World models have evolved from focusing on representation learning and future prediction to addressing long-horizon planning challenges. While models like V-JEPA 2 demonstrate strong predictive capabilities using large-scale video pre-training, they struggle with multi-stage control tasks due to error accumulation and exponential growth in action search space. HWM (Hierarchical World Model) introduces a two-level planning structure: a high-level planner outlines coarse subgoals over longer time horizons, while a low-level executor handles short-term actions. This decomposition reduces planning complexity and error propagation. In experiments, HWM achieved 70% success in real-world robotic tasks where flat models failed entirely. Complementary efforts include V-JEPA (focused on representation), HWM (on hierarchical planning), and WAV (World Action Verifier, on self-correction). Together, they mark a shift from pure world modeling to integrated systems capable of prediction, planning, and verification—key to deploying world models in real-world agents and long-term tasks.

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