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Anthropic launched Claude Meetings, Claude Whiteboards and Claude Sheets, with Claude joining video calls as a visible participant that drafts plans and tasks in real time while discussion is ongoing. The move follows OpenAI's ChatGPT office suite and Meta's Muse agent, signaling intensifying competition among the three firms over AI-powered workplace suites.

eBay has blocked third-party AI agents, including Meta's Muse, from browsing listings and pulling price and shipping details, breaking agent-generated shopping digests. The move follows similar restrictions by Amazon, Target and others, underscoring how access barriers are limiting the real-world utility of AI shopping agents.

Meta announced that its Muse AI agent is now available on Apple Watch and Android Wear OS, letting users interact with the assistant via voice calls, texts, or dictation directly from their smartwatch. The launch follows Muse's App Store debut in September and a dedicated iPad app in October, signaling Meta's push to make Muse a central consumer AI entry point. Muse surpassed 10 million U.S. downloads within 40 days, a milestone reached by only 11 other apps.

Former Meta engineer Evan X. Merz argues that teams heavily reliant on AI-generated code are shipping brittle codebases riddled with subtle technical debt, with even senior engineers overlooking glaring issues. He contends AI did not deliver order-of-magnitude productivity gains and that high-quality software will still depend on human developers.

Meta released Muse Ember, its smallest and most efficient model to date, targeting high-frequency agent workloads such as tool calling, coding subtasks and long-document parsing. On the Artificial Analysis intelligence index it scores about 36 at top reasoning effort, matching Claude Haiku 5.5 and beating GPT-6 Luna, while costing roughly one-third per task at about $0.136, placing it on a favorable efficiency frontier. It is available now via Meta Model API and Muse Code, with more efficient models reportedly in training.

Meta released Muse Ember, its smallest model, matching Claude Haiku 5.5 at 36 on the Artificial Analysis Intelligence Index at roughly $0.136 per task versus $0.411 for Haiku. Positioned as the execution layer in a two-model agent split alongside the planning-focused Muse Wonder, it natively handles text, images, audio and video with a 1M-token context and up to 512K output tokens. The trade-off is weaker real-repo mergeability on FrontierCode 2.0-AA, and several results are Meta internal runs.

Meta has launched Muse Ember, its smallest and most efficient model to date, purpose-built for complex reasoning and high-frequency agentic workloads. It matches Claude Haiku 5.5 on the Artificial Analysis Index (36) at one-third the per-task cost, while leading on agentic and multimodal benchmarks such as AutomationBench-AA and OSWorld 2.1. The model is available immediately via Meta Model API, Google Cloud and Oracle Cloud, priced at $0.10/$0.50 per million input/output tokens.

Meta has updated its iOS Muse app with Apple Watch support, letting users invoke the personal AI agent from their wrist via typing, voice input, or voice calls. Muse is already embedded in Instagram and Facebook, and the watch interface carries the yeti mascot motif, echoing the design of the Muse Charm device unveiled in September.

Meta released Muse Ember, its smallest model to date, claiming intelligence on par with Claude Haiku 5.5 at roughly one-third the cost. It targets token-heavy agent workloads such as tool calls, coding subtasks, routing, extraction and long-document parsing, and is available now on the Meta Model API and in Muse Code. Pricing is $0.10 input and $0.50 output per 1M tokens up to 200K tokens, rising to $0.30 and $1.50 beyond that.

Meta has launched Muse Ember, its smallest and most efficient model yet, purpose-built for the routine work AI agents do all day: tool calling, small coding tasks, request routing, data extraction and long-document processing. Meta claims it delivers more intelligence per dollar at every reasoning level than Claude Haiku 5.5 or GPT-6 Luna, at roughly $0.14 per task, though Haiku still leads on real coding benchmarks. The multimodal model handles up to one million tokens and is available now via the Meta Model API and Muse Code at $0.10 per million input tokens and $0.50 per million output tokens.