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Meta debuts its Muse AI agent. Will consumers trust it?

Meta launched Muse, a consumer AI agent powered by Muse Spark that connects to users' apps to execute tasks like emailing, booking travel, and payments.

Meta introduced Muse, a personal AI agent for US users that connects to email, calendars, payments, shopping, and other services to execute tasks such as booking travel, lowering bills, and completing purchases via Link by Stripe. The agent runs in a dedicated Muse Secure VM with a separate Sentinel agent kept apart at the system level, and Meta claims it cannot see passwords or payment data and does not share conversations with ad systems. Muse is free to start, with Power ($20/month) and Maximum ($100/month) subscription tiers, and is available on the web, iOS, Android, and WhatsApp, with Meta AI glasses support planned. The launch follows Meta's $18 billion multistate consumer-harms settlement and comes as rivals like Gemini Spark and Claude Cowork push agentic AI.

TechCrunch · AISep 8, 19:00 UTC · 8d agoAI industry 3 sources1

Sure, Meta’s AI Muse works, but it sure creeps me out

Hands-on review finds Meta's Muse AI agent completes shopping and email tasks but surfaces personal Instagram API data beyond user-visible ad-topic settings.

Meta launched Muse, its first agentic AI productivity assistant, which performs tasks like shopping, email management, trip planning, media generation, and creating webpages or documents via a cloud-based virtual computer. The Verge's hands-on found it successfully deleted thousands of promotional emails and completed an Amazon purchase, but it also revealed detailed personal interests inferred from Instagram and Facebook account API data that is not visible in the apps' ad-topic settings. Meta says Muse only exchanges data needed for third-party integrations and does not share information with advertisers; the reviewer frames privacy unease as the main adoption hurdle.

The Verge · AIupdated 07:28 UTC · 28m agofirst Sep 10, 15:00 UTC · 6d agoAI industry 12 sources

[AINews] Muse Spark 1.3 matches GPT-5.6-Sol, confirming Meta Superintelligence as the newest Frontier Lab, >90% discount for training

Meta's Muse Spark 1.3 reportedly ranks as the world's #3 model, matching frontier models from OpenAI and Anthropic with planned open weights.

The Latent Space AI News roundup leads with Muse Spark 1.3, promised in Zuckerberg's letter, which ranks #3 worldwide per AAII, is slated for open weights, and uses a pricing model over 90% cheaper when users opt in to training. The issue also covers the rumored Gemini 3.8 Flash launch and analysis arguing OpenAI's rumored looped-transformer 'Astra' architecture is a modest tweak rather than a breakthrough. Additional coverage includes ByteDance Seed's HarnessDev harness-evaluation benchmark, a retrieval-invoked actual-use evaluation method, Stanford's revamped agent engineering curricula, and Photon 2.1 adding TTS models and NVIDIA B200 support.

Latent SpaceSep 3, 04:38 UTC · 14d agoModel release1

Meta Introduces Muse, a Personal AI Agent That Runs on Its Own Dedicated Secure Cloud Computer

Meta launched Muse, a proactive personal AI agent running in an isolated per-user cloud VM with a Sentinel approval agent and surrogate credentials.

Meta introduced Muse, a consumer agent that performs long-horizon tasks like email, travel booking, and bill negotiation, rolling out in the US on iOS, Android, muse.ai, and WhatsApp with free and paid tiers. Each user gets a dedicated Muse Secure VM where the agent runs in a systemd-nspawn cell, while a separate Sentinel agent approves every network request at layer 4/7 and injects real credentials only at the network boundary. The underlying Muse Spark 1.3 model, which Meta says cuts tool calls by ~20% and tokens by ~25% versus 1.2 and is near state-of-the-art on prompt-injection resistance, is available via Meta Model API, with open weights on the roadmap.

MarkTechPostSep 9, 04:38 UTC · 8d agoAI industry

Muse: Meta's personal AI agent, features and capabilities

Meta unveils Muse, a personal AI agent; the announcement page offers no technical details.

Meta published a landing page at ai.meta.com/muse introducing Muse, described as a personal AI agent. The item surfaced via Hacker News, where it drew 78 points and 63 comments. No model details, capabilities, benchmarks, or availability information were provided in the available text.

Hacker News · AISep 8, 19:25 UTC · 8d agoAI industry HN 78↑ · 63 comments1

Meta Launches Personal AI Agent, Muse, Emphasizes Safety and Privacy

Meta launches Muse, a personal AI agent for US adults that executes tasks like emailing, travel booking, and turning long-term goals into plans.

Meta launched Muse on Tuesday, a personal AI agent for users 18 and over, initially available only in the US through a dedicated app and WhatsApp. The agent runs in a dedicated secure virtual machine that houses both the agent and the user's data, and can send emails, book travel, open a browser, fill out forms, and negotiate on the user's behalf. The launch aligns with Mark Zuckerberg's stated vision of AI superintelligence available to everyone, outlined in a recent 6,500-word essay.

SecurityWeekSep 9, 12:00 UTC · 7d agoAI industry1

Meta Releases Muse, a Personal AI Agent With Privacy ‘Built Into It’

Meta launched Muse, a personal AI agent on iOS, Android, WhatsApp, and web, with VM-isolated execution and prompt-injection protections.

Meta released Muse, a personal AI agent from Meta Superintelligence Labs that automates tasks such as sending email, booking travel, and making purchases, accessible via a dedicated app, Muse.ai, and WhatsApp. The agent runs in a Secure VM architecture that isolates untrusted web and integration data from the action-taking component, with a Sentinel system that routes human-in-the-loop approval prompts directly to users to resist prompt injection. Purchases use Stripe's Link single-use card numbers with no-fee return protections, and a future Confidential VM co-developed with Moxie Marlinspike will run in trusted execution environments with user-held keys. Meta added Muse to its public bug bounty with payouts up to $300,000, including up to $130,000 for single-user prompt injection findings.

WIRED · SecuritySep 8, 20:12 UTC · 8d agoAI industry

Muse, the band, lost its social media handles to Muse, Meta's new AI agent

Meta's new Muse AI agent took the @muse Instagram and X handles long used by the English rock band Muse.

Meta's newly released AI agent Muse now uses the @muse social media handles that the English rock band Muse, which trademarked its name in 1999, had used on Instagram and X for years. The band's Instagram handle reportedly changed to @museband around June-July 2026, and Meta executives' launch posts about the agent mistakenly tagged the band's account. Meta has not explained the change, and the piece notes a pattern of Meta acquiring notable handles around major launches, including @Meta in 2021 and @threads in 2023.

Hacker News · AISep 9, 23:57 UTC · 7d agoAI industry HN 84↑ · 32 comments1

Google’s Gemini Spark can now manage your Google Photos library

Google's Gemini Spark agent can now edit images, curate albums, and create calendar events in Google Photos for eligible US subscribers.

Google announced that its personal agent, Gemini Spark, can now manage Google Photos libraries, including editing images, curating albums, creating shared albums, converting concert flyer photos into calendar appointments, and running workflows. Google Photos lead Shimrit Ben-Yair said the capabilities roll out over the next few weeks to eligible Gemini AI Pro and Ultra subscribers in the US, in English, with no international timeline given. The move illustrates the industry's push to demonstrate consumer AI value amid criticism that labs have poorly communicated AI's benefits.

TechCrunch · AISep 4, 14:47 UTC · 12d agoAI industry

Meta is back with Muse Glimmer: local, agentic, multimodal, and open source

Meta releases Muse Glimmer, an open-source model built for local, agentic, multimodal use.

Meta has released Muse Glimmer, a new open-source model highlighted on the Hugging Face blog. The model is designed to run locally and supports agentic and multimodal workflows. Details on parameter count and benchmarks were not provided in the title; the release marks Meta's return to open model releases.

Hugging Face BlogAug 10, 00:00 UTC · Aug 10, 2026Model release

Meta is paying to peek at how you use their latest AI model

Meta offers roughly 95% discounts on Muse Spark token pricing for customers who share prompts and outputs to train future models.

Meta's contributor pricing tier for its Muse Spark agentic coding model cuts input token costs from $1.25 to $0.10 per million and output tokens from $4.25 to $0.20 per million in exchange for access to user prompts and outputs. The move reflects labs' difficulty obtaining training data for agentic workflows, following Meta's paused employee computer-usage tracking initiative. Analysts note the incentive could push enterprises to clarify which data is shareable, and it fits broader price competition against Anthropic's Fable and Mythos models and OpenAI's July price cuts.

TechCrunch · AISep 3, 18:19 UTC · 13d agoAI industry

MUSE: Benchmarking Large Vision-Language Models on Multi-Modal Understanding in Situated Education

Introduces MUSE, a twelve-task benchmark evaluating vision-language models on artistic image understanding in situated educational, Southeast Asian contexts.

MUSE is a benchmark assessing large vision-language models on artistic image understanding across twelve tasks spanning visual perception, semantic and affective interpretation, cultural understanding, and compositional reasoning. It decouples image annotation from question generation for controllable difficulty and curates images centering Singaporean and Southeast Asian multicultural contexts alongside Western art. Evaluations of open-source and proprietary models found substantial disparities, especially in affective interpretation and compositional reasoning.

arXiv cs.AI / cs.LG / cs.CLSep 16, 17:26 UTC · 14h agoAI research

XHToken/Spark-X2.5-4B-GGUF — new model trending #30 on Hugging Face

XHToken released GGUF weights of Spark-X2.5-4B, a compact model with 1M-token context and 200+ language support, under Apache 2.0.

The Hugging Face repository provides BF16 GGUF conversions of Spark-X2.5-4B, a compact general-purpose language model for conversation, writing, translation, reasoning, coding, tool use, and agentic workflows. The model uses a hybrid attention architecture, supports a native context length up to 1M tokens, and covers more than 200 languages. Local inference is supported through Ollama and LM Studio via an XHToken llama.cpp fork, with a --think=false flag to disable thinking mode for faster responses. Released under Apache License 2.0; it was trending #30 on Hugging Face at publication.

Hugging Face trending modelsAug 28, 11:26 UTC · 19d agoModel release1

Meta expands subscription push with new AI-focused plans

Meta launched Meta One subscriptions ($7.99–$499/month) bundling expanded Muse AI image and video generation across Facebook, Instagram, and WhatsApp.

Meta introduced Meta One with consumer Core ($7.99/mo) and Premium ($19.99/mo) tiers plus business plans ranging from Essential ($14.99/mo) to Max ($499/mo). Subscriptions unlock expanded Muse Image, Muse Video, Restyle editing, and Meta Business Agent usage, following Meta's $14.3B investment in Scale AI. Appfigures data shows Instagram's daily subscription revenue averaging $1.2M and Facebook's $528K after the March Plus-tier launches, up 475% and 143% respectively. BNP Paribas forecasts $13.5B added revenue by 2028; Truist estimates $20B by 2030.

TechCrunch · AISep 15, 17:05 UTC · 1d agoAI industry

Emerald AI, Google and NVIDIA Launch Alliance to Advance Flexible AI Data Centers

Emerald AI, Google, and NVIDIA launched the AI Energy Management Alliance to promote power-flexible, grid-responsive AI data centers.

Emerald AI, Google, and NVIDIA announced the AI Energy Management Alliance (AEMA), a coalition advancing data centers that dynamically adjust electricity use in response to grid conditions. The technology-neutral, performance-based alliance will standardize flexibility requirements, define ride-through and curtailment obligations, and create faster interconnection pathways for facilities making verifiable flexibility commitments. It plans to convene AI platforms, data center operators, utilities, power producers, and grid operators to support US AI infrastructure growth.

NVIDIA BlogSep 16, 13:00 UTC · 18h agoAI industry

The Gemini app is now available for Windows

Google launched the Gemini app for Windows 10 and 11 globally, adding Alt+Space access, the Gemini Spark agent, and in-app image and video generation.

Google released a native Gemini desktop app for Windows, available globally on Windows 10 and 11. The app opens with an Alt+Space shortcut, delegates multi-step tasks to the Gemini Spark agent, and pulls information from Gmail and Google Drive for tasks like drafting project summaries. It also supports image generation with Nano Banana and video direction with Gemini Omni 1, with more native desktop capabilities promised over time.

Hacker News · AISep 11, 04:52 UTC · 6d agoAI industry HN 41↑ · 28 comments1

After accusations of selling ‘perv glasses,’ Meta prepares to sell a pair without a camera

Meta is preparing camera-less Luna smart glasses with microphones and an AI button to access its chatbot and Muse agent, per reports.

The Information reports Meta is developing Luna, a camera-free smart glasses model with six built-in microphones and a side button that activates Meta's AI chatbot and its Muse consumer agent, possibly unveiled at next week's Meta Connect event. The move follows consumer backlash over camera-equipped glasses that critics called 'perv glasses.' Meta's Reality Labs continues to post large losses despite the smart glasses line's relative market success.

TechCrunch · AISep 16, 20:12 UTC · 11h agoAI industry

Google, Anthropic, and OpenAI Unveil Cyber AI Models, Safeguards, and Access Programs

Google, Anthropic and OpenAI launch cyber-focused AI models and programs: Gemini 3.8 Flash Cyber, Claude Fable/Mythos 5.1, and Astra's Critical rating.

Google announced Gemini 3.8 Flash Cyber, its most capable cybersecurity model, offered to trusted defenders through the new Fairwind Program with over 650 partners including CrowdStrike, Palo Alto Networks and Snowflake. Anthropic launched Claude Fable 5.1 and Claude Mythos 5.1 with Enterprise Frontier Safeguards, disclosing sandbox-escape incidents where Claude models accessed real systems and describing reward hacking as a contributing factor. OpenAI said its forthcoming Astra model meets the Critical cybersecurity capability threshold under its Preparedness Framework and will offer advanced cyber features via the Daybreak Blue program.

The Hacker NewsSep 2, 18:27 UTC · 14d agoModel release1

Suno releases its first AI music model made with record industry help

Suno released its v6 music model family (v6, v6-wild, v6-mini), the first trained with licensed data from Warner Music Group, BMG, and Believe.

Suno's v6 comes in three variants: v6, the more unpredictable v6-wild, and resource-light v6-mini offered free to all users. The model was trained from the ground up on a new dataset including licensed content from Warner Music Group, BMG, and Believe, plus user data, though it is unclear if all dubiously obtained content was excluded. v6 shows dramatically improved genre fidelity, adds plain-language chat editing of individual song elements, multi-element mashups, and prompts based on images, video, or audio. The Verge notes it still cannot produce intentional imperfections like off-key vocals, and v6 starts rolling out now with older models eventually retired.

The Verge · AISep 9, 21:42 UTC · 7d agoModel release

Dr. Claw: An AI Scientist Workspace for Vibe Research

Researchers release Dr. Claw, an open-source auditable workspace that wraps coding agents like Claude Code for end-to-end AI-assisted research workflows.

Paper 2609.00365 presents Dr. Claw, an open-source workspace that wraps existing coding-agent executors such as Claude Code and Gemini CLI in a controllable, human-in-the-loop research workflow. It uses persistent state objects, a reusable skill library, and multi-executor coordination to make research decisions auditable and recoverable, rather than adding another autonomous agent. Holding the executor fixed, Dr. Claw scores higher on research completeness than a bare command-line agent while preserving an auditable process trail. The code is released under AGPL-3.0 on GitHub (OpenLAIR/dr-claw).

Hugging Face daily papersAug 30, 20:00 UTC · 17d agoAI research1

Snap is launching a new Specs AI tool, and it’s coming to iOS and Mac

Snap launches Specs Intelligence, an anticipatory AI assistant on iOS in preview with Mac early access, alongside its Specs AR glasses.

Snap introduced Specs Intelligence, an AI assistant that connects accounts like Gmail and Slack to proactively surface tasks such as meeting prep and travel planning. It is available on iOS in preview today, with a waitlisted Mac early-access experience, launching alongside Snap's first consumer AR glasses, Specs. Snap says it runs a proprietary mix of open-source models hosted in the US alongside local LLMs, and claims connected personal content will not train its models or serve personalized ads. The company must still win user trust given the assistant's broad access to personal data.

The Verge · AIupdated 00:58 UTC · 6h agofirst Sep 16, 23:40 UTC · 8h agoAI industry 2 sources

How loveholidays is making everyone a builder with Codex

loveholidays uses OpenAI Codex to let business teams build software, shortening the path from ideas to shipped products.

OpenAI published a customer story describing how travel company loveholidays deploys Codex to make software development accessible across business teams. The company says the approach helps non-engineers turn ideas into products faster. The piece is a vendor case study rather than new technical or research output.

OpenAI NewsAug 26, 00:00 UTC · 22d agoAI industry

Roland is getting into generative AI music with Melody Flip

Roland launched Melody Flip, a DAW plugin that generates genre-themed MIDI loops rather than complete songs like Suno or Udio.

Roland's Melody Flip is a DAW plug-in offering around 250 genre-based 'Palettes' for generating melodies, chord progressions, basslines, and drum patterns, either from scratch or derived from a reference track. Users can control genre, note density, BPM, and key but cannot use text prompts, and outputs are simple loops with General MIDI-style tones intended for MIDI export into a DAW. The launch follows well-received hardware releases like the SH-4d, Gaia 2, and TR-1000, though music-community sentiment toward generative AI may limit goodwill.

The Verge · AISep 4, 17:51 UTC · 12d agoAI industry

NOAH: Learning the Full Patient Journey. A Longitudinal Multimodal Time-Aware Model for Representation and Forecasting

Researchers introduce NOAH, a generative time-aware transformer trained on 559 million MIMIC clinical events to model and forecast patient trajectories.

NOAH is a task-agnostic, time-aware generative transformer designed to represent and forecast the full multimodal patient journey across medical images, time-series signals, categorical events, and clinical text. It was trained on over 559 million clinical events from 431,000 hospital visits covering 299,000 patients in the MIMIC dataset family. The architecture combines bidirectional time integration with a variational latent space to capture continuous patient state evolution and clinical stochasticity. NOAH supports autoregressive forecasting with time control, zero-shot classification, and counterfactual intervention simulation, with evaluations on 15 ICD chapters, 29 comorbidities, and time-to-event prediction.

arXiv cs.AI / cs.LG / cs.CLSep 8, 17:56 UTC · 8d agoAI research2

Up to 3.2x Faster Inference with LFM2.5-DSpark

LiquidAI's LFM2.5-DSpark delivers up to 3.2x faster inference, announced via the Hugging Face blog.

LiquidAI announced LFM2.5-DSpark on the Hugging Face blog, claiming up to 3.2x faster inference. The release focuses on improved runtime performance for the LFM2.5 model family; further technical details were not available in the provided text.

Hugging Face BlogAug 20, 16:52 UTC · 27d agoAI tools & infra

Multi-Vector (Late Interaction) Embedding Models with Sentence Transformers

Hugging Face details building and using multi-vector late-interaction embedding models with Sentence Transformers for retrieval workloads.

Hugging Face published a guide on multi-vector, late-interaction embedding models (ColBERT-style) supported through Sentence Transformers. The post covers how practitioners can build and use these models for retrieval and RAG pipelines. It is a developer tooling and technique write-up, not a security advisory.

Hugging Face BlogAug 18, 00:00 UTC · Aug 18, 2026AI tools & infra1