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Meta denies Muse is built on OpenClaw but admits heavy inspiration

The Verge reports that Meta's Muse AI agent shares significant code and design similarities with OpenClaw, prompting allegations of direct derivation. Meta's product head denies copying but acknowledges OpenClaw's influence, while security concerns persist regarding both platforms.

4 min readRead the original reporting
Source-provided image accompanying Meta denies Muse is built on OpenClaw but admits heavy inspiration
歸因報告來源記錄
出版商
theverge.com
來源連結
theverge.comhttps://www.theverge.com/report/1000180/muse-openclaw-instinct-lookalike
來源類型
新聞媒體的報道-不是第一方文件。

我們無法獨立確認的內容: 此聲明歸因於指定的商店。我們沒有根據第一方文件對其進行驗證。 (theverge.com)

背景60 秒內了解這一點

從這裡開始

關鍵術語

記憶體(代理記憶體)
AI 代理程式跨步驟或會話使用儲存的上下文來提高連續性。
開源模型
使用公共權重或程式碼發布的模型,用於檢查、調整和重複使用。
人工智慧代理
一種可以觀察、推理並採取行動來實現目標的軟體系統,通常使用工具和記憶體。
測試一下自己AI 代理測驗

發生了什麼事

The Verge reports that social media users have alleged Meta's new consumer , Muse, is directly built on the open-source platform OpenClaw due to identical file names and personality documentation lines. Meta's head of product for Superintelligence Labs, Nat Friedman, denied that Muse was built on OpenClaw, stating it was built from scratch but heavily inspired by it. The report also highlights that Instinct, another AI agent platform, shares similar messaging-based features with OpenClaw. While Meta claims Muse is more secure, the article notes that a zero-day vulnerability was recently flagged in Muse, and Meta retains access to user data in its isolated VMs.

The Verge reports that allegations have circulated on social media suggesting Meta's Muse is a wrapper around the open-source platform OpenClaw. Evidence cited includes identical core file names such as SOUL.md and memory, as well as matching lines in personality-governing documents, such as the instruction to be 'genuinely helpful, not performatively helpful.'

Nat Friedman, head of product for Meta’s Superintelligence Labs, responded to these claims on X, stating that Meta built Muse 'from scratch.' However, he acknowledged that Muse is 'heavily inspired as a product' by OpenClaw, which he first used in January. Friedman explained that the team purchased hundreds of Mac Minis to test the platform and aimed to create a version that could be made safe, secure, and scalable to billions of users.

The report also examines Instinct, an platform fundraising at a $2.5 billion valuation. Like OpenClaw, Instinct allows users to communicate with agents via messaging tools. Users have reported using Instinct for tasks such as filling out medical paperwork, canceling subscriptions, and booking appointments, mirroring the use cases that drove OpenClaw's initial traction.

The Verge notes that while OpenClaw was a one-man weekend project that gained massive popularity, it had significant security issues, including malware in its skill repository. Meta claims Muse addresses these issues by storing user data in an isolated Linux VM called the Muse Secure VM. However, the article points out that Meta can still access this data, and a zero-day vulnerability was recently identified that allows attackers to hijack the agent.

來源詳情: theverge.com ↗

為什麼這很重要

This development clarifies the lineage of major commercial AI agents, confirming that OpenClaw's significantly influenced industry leaders like Meta. It highlights the tension between rapid product adoption and security integrity, as both Muse and OpenClaw face criticism for security flaws. The report underscores that while commercial agents offer better accessibility and integration, they may not yet resolve the fundamental security risks present in the underlying open-source architecture that inspired them.

The confirmation that major AI products are derived from or heavily inspired by OpenClaw validates the impact of open-source development on the broader industry. It suggests that the 'grassroots' approach of OpenClaw has become a blueprint for commercial offerings from major tech companies.

The security implications are significant. While Meta positions Muse as a secure alternative to OpenClaw, the persistence of a zero-day vulnerability and the company's retained access to user data raise questions about the actual security improvements. This is critical for users who may be adopting these agents for sensitive personal tasks.

The report highlights a shift in the market from experimental, local-first tools to scalable, cloud-integrated commercial products. This shift brings broader accessibility but also concentrates control and data handling in the hands of large corporations, potentially altering the privacy landscape for AI users.

Interactive Mechanism

互動機制:它實際上是如何運作的

以互動方式探索這項發展背後的基礎技術。

Agent Lifecycle Stage:
1
User Intent & Planning: "Audit customer refund request #4092 and settle payment."
2
Tool Calling: Emits structured JSON call crm_get_transaction(id='4092').
3
Guardrail & Verification:🛡️ Paused: High-value action requires human operator sign-off.
4
Final Settlement: Refund recorded, email receipt dispatched, and audit log stored.
Core takeaway: An AI agent is not just a language model—it is a closed loop of planning, tool invocation, and environment feedback. Production systems require self-healing retries and strict human approval guardrails.
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接下來看什麼

Monitor for independent security audits of Muse's isolated VM architecture to verify Meta's claims about data protection. Watch for further regulatory or public scrutiny regarding the similarity between Muse and OpenClaw, as well as the implementation of Meta's promised cryptographic measures to prevent company access to user data later this year.

Independent verification of the security claims surrounding Muse's isolated VM environment is needed, particularly regarding the zero-day vulnerability mentioned in the report.

The implementation of Meta's promised cryptographic measures to prevent company access to user data later this year will be a key indicator of whether Muse truly improves on OpenClaw's security model.

Further developments in the legal or public discourse regarding the similarity between Muse and OpenClaw, as well as the broader implications for open-source adoption by major tech firms.

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