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Meta / Llama

Meta's AI dynamics: Llama and Muse series models, the Superintelligence Lab, and Meta AI products.

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10 Nov, 02:37Updated
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Major events

  1. Meta launches Muse Ember: its smallest and most efficient model 4 sources

    Meta launches Muse Ember, its smallest and most efficient model designed for complex reasoning tasks, outperforming Claude Haiku 5.5 and GPT-6 Luna in smartness-to-cost ratio, with a cost of 0.10 USD per million input tokens and 0.50 USD per million output tokens, supporting a 1M context window and 512K output tokens.

  3. Meta Infrastructure Chief and Joint Engineering Chief Santosh Janardhan to Leave in 2027 2 sources

    Santosh Janardhan, Meta's Infrastructure Director and Joint Engineering Director, is expected to leave the company in early 2027. Meta is investing tens of billions of dollars in AI and data center construction, and this departure constitutes a major change in the company's management.

  4. Meta FAIR releases e-means: an algorithm that outperforms k-means in 10 fewer iterations 2 sources

    Meta FAIR's e-means algorithm achieves k-means's 25-iteration loss level within 1.4 to 2.6 iterations, with GPU speed improvements of 10-45 times and CPU speed improvements of 8-15 times, without hyperparameter tuning, and has been integrated into FAISS 1.16.0

  6. Meta releases Muse Ember: An ultra-small, highly efficient model designed for repetitive tasks of AI agents. 2 sources

    Meta releases Muse Ember, its smallest and most efficient AI model to date, designed for handling the repetitive tasks of AI agents, such as calling tools, processing small-scale coding tasks, routing requests, extracting data, and processing long documents.

Latest stories

Nov 10Tue1–3
  1. TechCrunch · AI72

    Meta releases lightweight model Muse Ember, highlighting agent execution and low cost.

    Meta Superintelligence Lab releases lightweight model Muse Ember, priced at 10 cents per million tokens, focusing on high-frequency agent tasks such as tool calling, coding subtasks, routing, extraction, and long document parsing.

    Why it matters: Meta uses a pricing of 10 cents per million input tokens and the Artificial Analysis comprehensive benchmark to place the lightweight model in the agent execution context, comparing it with Haiku and Luna.

Nov 6Fri
  1. ITHome · AI72

    Meta launches real-time voice chat and virtual avatar features for AI assistant Muse

    Meta announces the launch of real-time voice chat and virtual avatar features for its personal AI assistant Muse, rolling out first to users in the United States, covering mobile, web, and Mac apps. The feature is supported by two models, Muse Realtime Voice and Muse Realtime Avatar, capable of streaming vertical videos at a resolution of 448×768 and 25 frames per second. The delay from the user finishing speaking to receiving the first audiovisual response is approximately 870 milliseconds.

    Why it matters: The original text provides the latency, resolution, and interaction methods for real-time voice and virtual avatars, allowing readers to judge the maturity of such face-to-face intelligent agent interactions.

Oct 30Fri
  1. Meta Engineering66

    Meta rolls out JiTTesting to production: Use LLM to generate tests and catch bugs before code merge

    Meta announced that Catching JiTTests has been put into internal production, using LLM to automatically generate executable tests for diffs to be merged, exposing behavioral differences before the code is landed

    Why it matters: Meta has disclosed the production deployment details and quantitative results of JiTTests, available for evaluating the implementation of LLM-generated tests in ultra-large-scale codebases.

Related topics

Anthropic / Claude44 this monthOpenAI / ChatGPT43 this monthGoogle / Gemini31 this monthNVIDIA23 this month

Related models

Muse Wonder FullRank 10 · AA index 50.1Muse WonderRank 15 · AA index 43.6Muse Spark 1.3Rank 16 · AA index 36.6Muse EmberRank 18 · AA index 36Muse Spark OpenRank 38 · AA index 24.9Muse GlimmerRank 57 · AA index 6.3