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Meta announces issuance of a new class of shares to finance AI plans

Meta announced on October 22, 2026, the issuance of a new class of shares to finance its AI plans. At the earnings call the same day, it was disclosed that within six weeks of launch, more than 10 million people in the United States and Canada had set up the AI product Muse, with about 25% of users using it daily; shopping is the most common use case, with an average order value exceeding $200; the company plans to bring Muse to Meta Glasses in November 2026 and to launch the hardware device Muse Charm. Chief Financial Officer Susan Li said that, apart from subscriptions, Muse has not yet been monetized. There are currently no subsequent developments.

View story:Meta announces issuance of a new class of shares to finance AI plans

Meta Muse Wonder launches on OpenCode

OpenCode announced that Meta Muse Wonder is now available on its platform. The news was released on October 22, 2026; currently this is the only factual evidence, with no subsequent developments or official supplementary statements yet.

Meta Muse Wonder launches on OpenCode

OpenCode announced that Meta Muse Wonder is now available on its platform. The news was released on October 22, 2026; currently this is the only factual evidence, with no subsequent developments or official supplementary statements yet.

View story:Meta Muse Wonder launches on OpenCode

Rohan Paul says Meta's AI agent Muse reached 10.2 million downloads in the US in 40 days

Rohan Paul offered the assessment that Meta's AI agent Muse reached 10.2 million downloads in the US within 40 days of launch. The data he cited also shows that historically only 11 apps have reached this pace, most of them mobile games. On retention, Muse's US 7-day retention rate is 30% and its 14-day retention rate is 23%, compared with competitor averages of 19% and 16%, respectively. On October 16, its daily active users reached 2.5 million, up 15% in a week, but still less than a quarter of its US downloads. At present, this assessment is seen only from Rohan Paul as a single source, with no other independent sources or official evidence to cross-verify it.

Rohan Paul says Meta's AI agent Muse reached 10.2 million US downloads in 40 days

Rohan Paul offered the assessment that Meta's AI agent Muse reached 10.2 million downloads in the US within 40 days of launch. The data he cited also shows that historically only 11 apps have reached this pace, most of them mobile games. On retention, Muse's US 7-day retention rate is 30% and its 14-day retention rate is 23%, compared with competitor averages of 19% and 16%, respectively. On October 16, its daily active users reached 2.5 million, up 15% in a week, but still less than a quarter of its US downloads. At present, this assessment is seen only from Rohan Paul as a single source, with no other independent sources or official evidence to cross-verify it.

View story:Rohan Paul says Meta's AI agent Muse reached 10.2 million downloads in the US in 40 days

Meta paper argues that proactive assistants fail at autonomously judging when to interrupt

On October 21, 2026, Meta published a paper pointing out that the failure point of proactive assistants (such as AI glasses) lies in autonomously judging when to speak, not just what to say. The team built the ProPerMem benchmark, using first-person video paired with interference-rich full-year memories averaging 618K tokens, and featuring manually verified trigger windows. The paper reports that all baselines scored at most 15%, even frontier models using retrieval-augmented memory; when oracle evidence was provided within the window, GPT-5.3-Chat reached 96%, but when it was left to choose the timing itself, this dropped to 38%, and after adding retrieval it fell to 15%. Grasping both content and timing while reducing trigger frequency can raise accuracy from under 10% to 42.4%. The work is currently released as a paper, with no subsequent progress yet.

Alibaba Cloud OSS launches the new version of MetaQuery

Alibaba Cloud OSS launches the new version of MetaQuery. According to an article published by the Alibaba Cloud Developer Community AI on October 21, 2026, Alibaba Cloud OSS has launched a "object bucket + vector bucket + table bucket" three-bucket-in-one architecture, unifying unstructured data, vector data, and structured data onto the same storage foundation. The article states that a single file in an object bucket supports up to 48.8TB, with 12 nines of data reliability; the vector bucket supports trillion-scale vector volumes and millisecond-level similarity retrieval; the table bucket natively integrates Apache Iceberg, and concurrent write TPS for 500 tables can reach more than 10 times that of self-built Iceberg solutions. The article also breaks down the four-layer cloud-native architecture and hands-on steps such as bucket creation, SDK uploads, and batch operations and maintenance with ossutil. There are currently no subsequent development facts.

Alibaba Cloud OSS launches new version of MetaQuery

Alibaba Cloud OSS launches the new version of MetaQuery. According to an article published by the Alibaba Cloud Developer Community AI on October 21, 2026, Alibaba Cloud OSS has launched a "object bucket + vector bucket + table bucket" three-bucket-in-one architecture, unifying unstructured data, vector data, and structured data onto the same storage foundation. The article states that a single file in an object bucket supports up to 48.8TB, with 12 nines of data reliability; the vector bucket supports trillion-scale vector volumes and millisecond-level similarity retrieval; the table bucket natively integrates Apache Iceberg, and concurrent write TPS for 500 tables can reach more than 10 times that of self-built Iceberg solutions. The article also breaks down the four-layer cloud-native architecture and hands-on steps such as bucket creation, SDK uploads, and batch operations and maintenance with ossutil. There are currently no subsequent development facts.

View story:Alibaba Cloud OSS launches the new version of MetaQuery

Judge orders Meta to disclose the list of employees who authorized BitTorrent downloads of pirated ebooks

US Judge Thomas Hixson ordered Meta to provide the command history of the download servers and to list all personnel involved in approving the downloading of pirated ebook libraries via BitTorrent. Meta previously said it could not identify the specific decision-makers, that such decisions were usually team consensus, and that downloading torrents was a technical decision by the executing employees. The book publishers and authors suing Meta want to find out who ordered the downloading of pirated ebooks from Anna's Archive and LibGen for training AI models.

English translation is being prepared.

US Judge Thomas Hixson ordered Meta to provide the command history of the download servers and to list all personnel involved in approving the downloading of pirated ebook libraries via BitTorrent. Meta previously said it could not identify the specific decision-makers, that such decisions were usually team consensus, and that downloading torrents was a technical decision by the executing employees. The book publishers and authors suing Meta want to find out who ordered the downloading of pirated ebooks from Anna's Archive and LibGen for training AI models.

View story:Judge orders Meta to disclose the list of employees who authorized BitTorrent downloads of pirated ebooks

Meta is developing Confidential VMs functionality on the Muse web client

Meta is developing Confidential VMs functionality on the Muse web client, allowing users to run Muse tasks in an encrypted confidential environment. Meta previously previewed that this feature would launch before the end of 2026. A newly surfaced hidden setting shows that the feature will initially be available only to Meta AI subscribers; after toggling it on, voice mode, image and video generation, and wearable device support will be temporarily unavailable. Meta says conversations run in a secure encrypted environment and that Muse data will not be used to improve Meta's AI. The feature is currently still in development, and there is no further evidence of an official launch date.

English translation is being prepared.

English translation is being prepared.

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English translation is being prepared.

English translation is being prepared.

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English translation is being prepared.

English translation is being prepared.

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Meta paper proposes that proactive assistants fail at autonomously judging when to interrupt

On October 21, 2026, Meta published a paper pointing out that the failure point of proactive assistants (such as AI glasses) lies in autonomously judging when to speak, not just what to say. The team built the ProPerMem benchmark, using first-person video paired with interference-rich full-year memories averaging 618K tokens, and featuring manually verified trigger windows. The paper reports that all baselines scored at most 15%, even frontier models using retrieval-augmented memory; when oracle evidence was provided within the window, GPT-5.3-Chat reached 96%, but when it was left to choose the timing itself, this dropped to 38%, and after adding retrieval it fell to 15%. Grasping both content and timing while reducing trigger frequency can raise accuracy from under 10% to 42.4%. The work is currently released as a paper, with no subsequent progress yet.

View story:Meta paper argues that proactive assistants fail at autonomously judging when to interrupt

Meta pauses Muse conversation sharing feature

Meta has paused the conversation sharing feature of its Muse AI agent. The reason is that researchers at security firm Claroc found that the URLs of these shared links could be retrieved on the public web. Claroc said it found more than 6,800 Muse links through public DNS records and reviewed hundreds of conversations, with content involving marketing company revenue reviews, small business owner loan applications, workplace year-round employee calendars, and notes from job seekers' calls with AI labs. Muse spokesperson Tracy Clayton said users can share specific Muse content and generate pages accessible via links, and the company is reviewing the report and considering adjusting how links are discovered. According to Unite.AI, on October 20 Claroc rechecked 40 shares that previously could be opened without an account, and none could be opened, but hostnames containing conversation titles remained in passive DNS history; Muse launched on September 8, and share addresses consist of the conversation title plus a random ID, and when first opened, DNS records the full hostname.

English translation is being prepared.

Meta has paused the conversation sharing feature of its Muse AI agent. The reason is that researchers at security firm Claroc found that the URLs of these shared links could be retrieved on the public web. Claroc said it found more than 6,800 Muse links through public DNS records and reviewed hundreds of conversations, with content involving marketing company revenue reviews, small business owner loan applications, workplace year-round employee calendars, and notes from job seekers' calls with AI labs. Muse spokesperson Tracy Clayton said users can share specific Muse content and generate pages accessible via links, and the company is reviewing the report and considering adjusting how links are discovered. According to Unite.AI, on October 20 Claroc rechecked 40 shares that previously could be opened without an account, and none could be opened, but hostnames containing conversation titles remained in passive DNS history; Muse launched on September 8, and share addresses consist of the conversation title plus a random ID, and when first opened, DNS records the full hostname.

View story:Meta pauses Muse conversation sharing feature