Skip to content
Live
#Meta
  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.

    Same story · 2 outlets

    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.

  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.

  2. The Verge · AI80

    AI industry in the US faces regulatory and data center construction resistance after the midterm elections

    After the Democratic Party won both the Senate and House in the US midterm elections, the AI industry is facing the prospect of tighter regulation and slower data center construction, with 43 out of 44 local data center bans passed in the vote. Elected officials have promised to summon CEOs of AI companies to testify, and experts believe that Trump and the Republican Party in Congress have basically ended their efforts to ban state-level AI restrictions.

    Why it matters: The midterm election results and the vote on local data center bans provide specific signals for observing the direction of US AI regulation.

  1. ITHome · AI72

    Microsoft, Google, Oracle, and other five tech giants have pledged to invest more than 3 trillion US dollars in AI infrastructure.

    According to Bloomberg, Alphabet, Meta, Microsoft, Amazon, and Oracle have pledged to invest more than 3 trillion US dollars in data centers and other fields in the coming years, with a total of 1.3 trillion US dollars in lease payment commitments and a total of 1.9 trillion US dollars in other procurement commitments.

    Why it matters: The contract commitments of the five giants in terms of scale and scope are listed together, revealing the capital structure and recovery pressure of AI data center investments.

  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.

You are all caught up