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All news · Today4 items

#Meta

All collected and published items, ordered by time. Picks are a selected subset.
10/15Thu
10/14Wed
  1. Alexandr Wang · X35

    Alexandr Wang Says Muse Wonder Is Fast and Token-Efficient

    @merge_api says Muse Wonder completes an average task in 6.8 minutes, compared with 13.2 minutes for Claude Opus 5.5 and 15.3 minutes for Claude Sonnet 5.5. The quoted post says the scores are 52.4, 57.6, and 56.0, respectively. Alexandr Wang calls Muse Wonder “super fast and token efficient” and says, “give it a go!” https://twitter.com/merge_api/status/2110385332046762163

  4. Latent Space42

    Gemini 4 Argon Goes GA as AI Engineer NYC Highlights Benchmarks

    Google released Gemini 4 Argon globally for coding, knowledge work, enterprise workflows and cyber defense, with access through the Gemini API and several Google products. Introductory API pricing is $2 per million input tokens and $10 per million output tokens, with cached input discounted 95%; Artificial Analysis reports rates double after November 30. At AI Engineer NYC, about 20,000 people joined keynotes on AI and finance, including a discussion of benchmarking models like Argon by Vals AI’s CEO.

  7. Simon Willison64

    Simon Willison updates llm-meta-ai 0.2 for Meta AI’s Muse Wonder

    Simon Willison updated his llm-meta-ai plugin to support Meta AI’s newly released Muse Wonder models. He shares pelican drawings across six reasoning levels, from minimal to max, and compares them with Muse 1.3 and Muse 1.2, reporting material drawing improvements between releases. He suggests these may be Meta’s first Fable class models and reports that Artificial Analysis scores Muse Wonder (Max) as equivalent to GPT-6.1 Sol.

  8. Alexandr Wang · X48

    Alexandr Wang Shares a Cheeky Muse* Post About Muse Wonder

    Alexandr Wang’s post says Mark Zuckerberg and Wang came to the pub to discuss Muse Wonder, described in the quoted post as their new frontier model. The post lists discussion topics including Muse Wonder, how frontier models are built, agentic commerce, and Meta Superintelligence Labs. Wang adds that the cheeky Muse* was made with Muse Wonder.

  9. The Verge · AI58

    Ray-Ban Meta Audio glasses review: I don’t miss the camera

    Victoria Song finds the camera-free Ray-Ban Meta Audio glasses comfortable and useful as open-ear headphones, while finding Muse Spark helpful mainly for simple requests and reminders. Her review unit lasted two full workdays without returning to its case, but audio suffered from sound leakage and loud surroundings. Removing the camera eased her discomfort wearing smart glasses in public, though she argues that it does not resolve broader privacy concerns and finds the glasses expensive for their current capabilities.

  10. TechCrunch · AI60

    Facebook launches Your Algorithm to give users more control over recommendations

    Meta launched Your Algorithm on Facebook, allowing users to describe in natural language what they want to see more or less of in Feed and Reels. Meta says preference changes affect recommendations in real time. An updated three-dot menu provides access to the feature and Interested or Not interested options, with possible follow-up questions to clarify feedback.

  11. The Verge · AI66

    Mia Goth’s representatives criticize Instagram over viral AI-generated image

    Mia Goth’s representatives say a viral Instagram image of the actress was AI-generated and posted by a verified fan account they had repeatedly asked Instagram to remove. Hundreds of thousands liked the image, and outlets including People treated it as authentic. Meta’s rules exempt still images from mandatory AI labeling. The account appeared to have been wiped from Instagram by Tuesday morning; Meta did not immediately respond to a request for comment.

  12. The Verge · AI64

    Facebook will let you customize your feed algorithm using AI

    Facebook’s new Your Algorithm feature will let users add and manage topics they want to see in their feed and Facebook Reels. Users can select “interested” or “not interested” on posts and may receive follow-up questions about their preferences. Meta says natural language feedback will update recommendations in real time within the same session, and that it is using LLMs more in its ranking systems.

  13. Alexandr Wang · X54

    Alexandr Wang Highlights Early User Impressions of Muse Wonder in Muse

    Alexandr Wang says the top use case when building Muse Wonder was serving consumers in Muse and welcomes users enjoying the upgrade. In the quoted post, @_simonsmith reports no noticeable personality or writing regressions versus Spark, better UI judgment, and detection of subtle code bugs. Smith remains unsure whether Wonder also powers background tasks such as goal summaries and the news feed.

10/13Tue
  1. Latent Space84

    Meta launches Muse Wonder and Muse Wonder Full frontier models

    Meta Superintelligence Labs released Muse Wonder and Muse Wonder Full, its second-generation model family for personal and professional agentic work. Latent Space reports that Wonder is available through the Meta Model API and Muse Code, while Full is limited to Muse Code subscribers. Artificial Analysis gives Wonder Full and Wonder Intelligence Index v4.3 scores of 56 and 52, respectively, versus Opus 5.5’s 58; Wonder supports a 1M context window and text, image, video, and audio inputs, with text-only output.

    Why it matters: The benchmark breakdown compares Wonder variants with competing models on agentic performance and token usage, showing how their relative standing changes across tasks rather than a single ranking.

  2. 宝玉 · X50

    Muse fixes unusually fast quota usage and resets muse code

    Alexandr Wang says the issue causing unusually fast quota usage for muse wonder and muse wonder full has been identified and fixed. Users will now see much lower usage against their limits. Wang also announces a muse code reset, as promised after the fix. Baoyu comments that Muse now has enough users that he feels awkward saying Meta also reset limits in an unnoticed corner. 😅

  9. Alexandr Wang · X46

    Alexandr Wang calls a Muse Wonder game a “banger”

    @bubbleboi said Muse downloaded Blender and a facebuilding tool, found an image of Mark Zuckerberg, and is emulating Metal Gear Solid V on an M3 MacBook Pro to put Zuckerberg’s face on Venom Snake. @bubbleboi also said Muse completed a Minecraft task in a browser. Alexandr Wang reacted: “tbh seems like muse wonder made a banger game”

  13. The Decoder83

    Meta releases Muse Wonder models with gains in coding and agent benchmarks

    Meta released Muse Wonder and Muse Wonder Full, scoring 52 and 56 on the Artificial Analysis Intelligence Index v4.3, versus 48 for Muse Spark 1.3. Both support a one-million-token context window and text, image, video, and audio inputs, with stronger coding and agent results but weaker factual knowledge than leading competitors. Muse Wonder is available through Meta's API and Muse Code at higher prices than its predecessor; Muse Wonder Full is currently limited to Muse Code users.

    The same story is shown in the picks as 《Meta releases frontier models Muse Wonder and Muse Wonder Full》

  21. Alexandr Wang · X32

    Alexandr Wang Posts “MUSE WONDER”

    🍉 MUSE WONDER 🍉 @hdubugras says Alex and Meta are on a roll, and that the model has replaced Astra/Opus in a variety of their workflows. They say it handles day-to-day tasks efficiently and quickly, and offer congratulations. Alexandr Wang’s reaction: “🍉 MUSE WONDER 🍉”

  22. 宝玉 · X80

    Meta releases Muse Wonder for developers as consumer access remains unclear

    Baoyu reports that Meta released Muse Wonder and Muse Wonder Full on October 12, with Muse Wonder available today through Meta Model API and Muse Code, while Full is limited to Muse Code subscribers. Meta’s blog says consumer access is coming soon, whereas Zuckerberg says subscribers can use it today. The models support a 1 million token context window and multimodal input with text output. Meta reports strengths in sustained agentic work, coding, and memory, but its comparisons include internal benchmarks and competitor runs that may not be optimally configured.

    The same story is shown in the picks as 《Meta releases frontier models Muse Wonder and Muse Wonder Full》