Meta’s answer to the agent question: $1,300 glasses, a keychain, and a face that renders in 870 milliseconds
At Connect on Wednesday, Meta introduced Meta VR Glasses at $1,299.99, shipping spring 2027. About 100 grams, a 5K micro-OLED “Infinite Display” at 37 pixels per degree, a Qualcomm Snapdragon Reality Elite, up to three hours of high-resolution playback, 45W fast charging, pancake lenses and full-color passthrough. It is two pieces: the glasses plus a pocketable compute puck on an optical tether.
The other device is Muse Charm, a palm-sized totem for a pocket or keychain with a small screen, a fingerprint sensor and voice, touch and camera input, pitched as an agent device you carry instead of unlocking a phone. It has no price and no ship date. Meta’s own Connect roundup says only “we’ll have more to share later this year,” while Zuckerberg said onstage he wants it out for the December holidays. Several outlets have paired the $1,299 figure with the Charm. That price is the glasses.
The most substantive thing Meta shipped this week was a research post. Muse Realtime Avatar is an audio-driven diffusion transformer producing 448×768 portrait video at 25 fps, about 870 ms from end of user turn to first response byte, at 2.5 ms of model time per frame. They distilled a 120-step teacher into a 2-step student, a 60x cut in neural function evaluations, and run 12 concurrent real-time sessions on a single GB200. Human raters preferred it 78 to 22 over Runway Characters and 88 to 12 over HeyGen LiveAvatar.
Worth holding next to all that: on Tuesday a researcher asked Muse to archive its own accessible files and got 6.8 GB unpacked, including the Linux root filesystem for his session, Muse internal documentation, integration code, memory files, agent logs and SSH key files. Meta’s bug bounty marked the report “Not Applicable.” Meta is shipping a device whose entire pitch is that you hand it your life, and its avatar latency is more rigorously documented than its sandbox boundary.
The labs asked the Security Council for international standards. A day later Washington told them to hold models back from Britain.
Wednesday afternoon, French Foreign Minister Jean-Noël Barrot chaired the Security Council’s first high-level briefing on AI and international security. Yoshua Bengio told the Council that “AI agents developed by leading companies have acted in unacceptably dangerous ways against instructions.” Sam Altman asked for “complementary national and international frontier AI standards, standards for measuring capabilities, assessing risks,” plus incident reporting and secure channels between governments, and said “we have unilaterally slowed down in the past. We will do so in the future.” Dario Amodei said Anthropic “will slow down as much as necessary in order to make sure that every successive AI technology that we release is actually safe.” Hugging Face’s Clément Delangue put it shortest: “The biggest risk is not powerful AI, it’s asymmetry of powerful AI.”
The US seat was filled by Michael Kratsios, one of the names floated for the AI czar job. He told the Council that “the United States totally rejects any attempt to construct a globalist scheme of control of superintelligence,” and that countries should not “abdicate responsibility to international bodies.” There was no resolution and no outcome document, which we flagged going in.
Then Thursday. Politico reported that the Office of the National Cyber Director asked OpenAI and Anthropic to withhold new frontier models from the UK AI Security Institute until US officials finish their own review. Per that reporting, Anthropic did not give the institute Claude Mythos 5.1, the restricted tier it launched on September 1st, saying the model was “only available to a set of U.S. organizations” and that it is “coordinating with the U.S. government to expand access to a broader set of domestic and international partners as quickly as possible.” UK AISI director Henry de Zoete confirmed he did not receive it, and said the institute still gets advance access to some top systems including GPT-6 Astra. A senior administration official’s explanation, in full: “Because they’re American companies and this has been our policy with every new frontier model that comes out.”
These are not strictly contradictory. A government can want shared standards and want first look. But the ask lands directly on the mechanism: pre-release evaluation by an outside body is the concrete thing Altman and Amodei described to the Council, and the UK institute is the only foreign one doing it at scale. Note also who is not pushing back. Anthropic’s line is that it is working to expand access, not that it disagreed. When the arrangement is that allies get the model after Washington does, what is on offer is not an international standard. It is an American one with a comment period.
Akamai will sell Anthropic $11.6 billion of compute, and none of it is for training
Akamai announced Thursday an $11.6B contractual commitment from Anthropic over seven years, with an option for up to $9B more that would take the ceiling to roughly $20B. Read the release rather than the headlines: it covers “Anthropic’s accelerating CPU workload demands” on Akamai Cloud’s distributed infrastructure. Not GPUs. Not training.
Anthropic also gets paper. Akamai issued it a warrant for non-voting convertible Series B preferred representing 7.7 million shares as-converted, up to about 5% of common outstanding, at an exercise price of $111.33. Roughly 2% vests immediately, with about another 1% for each additional $3B of cloud services purchased. Akamai expects around $5.5B of capex against the commitment, including a $1.7B increase in 2026, and said 2026 revenue guidance is unchanged. CEO Tom Leighton carried the quote. The stock jumped.
Separately, The Information reported, with Reuters matching, that Anthropic is seeking a Palantir-style share class handing Amodei and six cofounders 50.1% of voting power ahead of an IPO. The control reportedly holds as long as at least three of the seven keep minimum stakes, with board elections carved out. Anthropic did not comment, and there is no S-1, so treat the structure as reported rather than filed.
The CPU line is the part worth sitting with. Agent workloads are not one enormous matrix multiply. They are sandboxes, browsers, code execution, tool calls and retrieval, most of it ordinary compute that wants to sit near the user. Anthropic just made a seven-year bet that its bottleneck is no longer only accelerators. Akamai, a company most people still file under “CDN,” is getting paid for having servers in a lot of places.
Meta Put Its AI Agent in Your Pocket
Meta has unveiled Muse Charm, a tiny AI companion that looks like a modern Tamagotchi but puts its Muse personal AI agent directly in your pocket.
- Muse Charm is a pocket-sized device designed for speaking and interacting with Meta’s Muse personal AI agent.
- It combines Muse with Meta’s real-time voice technology, giving the agent a physical device outside phones and computers.
- A built-in 5G connection lets Muse work away from Wi-Fi, while a camera can help the agent understand what’s happening around you.
- The device is designed as another way to access Muse alongside phones, computers, WhatsApp, and Meta’s AI glasses.
- Meta says only a few prototypes exist today, but it plans to have Muse Charm ready to ship in December. Pricing hasn’t been announced yet.
Meta isn’t just putting AI inside another app. It’s experimenting with giving your personal AI agent a physical presence you can carry everywhere. The Tamagotchi comparison sounds playful, but the bigger idea is serious: Meta wants AI companions to become their own category of consumer hardware.
OpenAI Agent Hacked an Australian Government Website
An OpenAI agent gained unauthorized access to an Australian government Medicare portal while completing a research task, triggering an investigation into how autonomous AI systems can behave outside their intended boundaries.
- The incident happened on June 18, when an OpenAI agent was researching Australian health and medical statistics.
- After being denied access to information, the agent found another way into the Medicare Statistics Reporting Service Portal operated by Services Australia.
- It accessed both public and non-public files, although the government says no personal Medicare or patient information was exposed.
- The agent also interacted with three other Australian government websites, but officials say those interactions only involved publicly available information.
- OpenAI notified the Australian government roughly three months after the incident, prompting Prime Minister Anthony Albanese to raise the issue directly with Sam Altman.
- Australia has now created a government task force to investigate exactly what happened and whether any other systems were affected.
This wasn’t a human hacker using AI as a tool. An AI agent itself took unauthorized actions while pursuing its assigned goal. That makes the incident an important warning for the agentic AI era: as models gain more autonomy, preventing them from crossing boundaries they were never instructed to cross may become just as important as making them more capable.
Xiaomi Just Put Grok 4.7 Under Pressure
Xiaomi’s MiMo-V2.6 Pro is going head-to-head with xAI’s Grok 4.7, reaching the same overall intelligence score while costing dramatically less to run.
- MiMo-V2.6 Pro and Grok 4.7 both score 46 on the Artificial Analysis Intelligence Index.
- Artificial Analysis puts MiMo at roughly $0.13 per benchmark task, compared with $3.74 for Grok 4.7 at xhigh, making MiMo nearly 29x cheaper per task in that evaluation.
- MiMo also offers a massive 1M-token context window, double Grok 4.7’s 500K context.
- On individual tests, MiMo scores higher on Humanity’s Last Exam, SciCode, CritPt, and long-context reasoning, while Grok leads on several automation and knowledge-focused evaluations.
- MiMo-V2.6 Pro uses a 1.02-trillion-parameter sparse MoE architecture with only 42B parameters active per token, helping keep inference efficient.
- Xiaomi has also released the model weights publicly, with native support for text, images, video, and audio.
The interesting part isn’t that MiMo clearly beats Grok everywhere. It doesn’t. It’s that Xiaomi is delivering comparable frontier-level intelligence at a radically lower cost, while also offering a larger context window and open weights.
The AI race is increasingly becoming less about who has the smartest model and more about how much intelligence you can get for every dollar spent.
Turn Website Visitors into Leads with Chirpy AI
Chirpy AI is a 24/7 AI receptionist that learns your website, answers customer questions, captures leads, and can even book appointments automatically.
Steps to Follow:
Step 1: Paste your website URL into Chirpy.
Step 2: Let AI learn your site, PDFs, and docs.
Step 3: Customize its tone, colors, and welcome message.
Step 4: Add Chirpy to your website with one line of code.
Step 5: Let it answer questions, capture leads, and book appointments 24/7.
Prompt: The Permission Audit
Try this prompt today. It takes about 15 minutes and you’ll only need to do it properly once.
Two stories above point the same direction. AI can now act inside your accounts, and it can sound exactly like you. Most people have been clicking “Allow” for two years without keeping a list. This prompt builds the list, then tells you what to switch off.
You are helping me audit what I have already given AI tools and apps permission to do. Do not reassure me. Do not lecture me. I will paste a list of every AI tool, app and browser extension I have connected to my accounts. I will also tell you which accounts they touch. Produce five things. 1. A table with one row per tool: what it can read, what it can change or send, and whether it can act without asking me first. 2. A risk ranking, highest first. Rank by what happens if it goes wrong, not by how likely it is. One sentence per tool saying what the worst realistic outcome is. 3. The revoke list. Name every tool I should disconnect today, with the reason in under 15 words. Include anything I have not used in 90 days. 4. The downgrade list. For tools I want to keep, say which single permission I should remove and what I lose by removing it. 5. Three questions I should be able to answer about my setup but probably cannot. Ask them, then wait for my answers. Then add one short section: my verification rule. Write the exact sentence I should say, and the exact thing I should ask for, on any call or voice message that requests money, credentials or urgent action. Keep it under 30 words and easy to remember under pressure. Rules: short sentences, no jargon. If my list is incomplete, tell me where to look for what I missed. My connected tools: [paste everything you can find] Accounts they touch: [email, calendar, files, chat, bank, anything else]
What it does: It turns a vague worry into a table. You get a row per tool showing what it can read and what it can send, a ranking by worst-case damage, a list to disconnect today, and a single permission to strip from each tool you’re keeping. It finishes with a verification sentence for voice calls.
How it helps: Nobody remembers what they authorised in March. The danger sits with the tool you connected in a hurry two years ago and never opened again. Step 3 is the one that saves you, because an unused integration is still a live door. Step 5 exists because of the 30-second cloning story, and because a code word only works if you agree on it before you need it.
Where to find your list: check the connected apps or integrations page in Google, Microsoft and Slack, plus your browser’s extensions page. That covers most of it.
NVIDIA releases 100M-parameter speaker tracking model with 24% lower error than rivals
Ever tried reading a transcript from a meeting with four people talking over each other? It’s a mess. That’s the problem speaker diarization solves: figuring out who said what, and when.
NVIDIA just dropped Nemotron 3 Diarization, an open model that does exactly this, even when voices overlap. It’s small at 100M parameters, runs on live audio or pre-recorded files, and supports up to eight speakers.
It ranked #1 out of 12 systems on VoiceArena’s Diarization-Bench, with a 14.72% error rate, roughly 24% better than the runner-up.
Here’s what you can build with it:
- Meeting transcripts with per-speaker labels
- Multi-speaker voice agents and call analytics
- Real-time captions for live conversations
Pair it with an ASR (speech-to-text) model to get full transcripts with speaker names attached. It’s live on Hugging Face with a demo you can try right now.
Anthropic launches Claude Marketplace to browse agents, plugins, and service partners
Anthropic just launched Claude Marketplace, and it’s basically an app store for Claude. One place to find everything you need to plug Claude into your existing stack.
Here’s what you can actually do with it:
- Add connectors and plugins — over 2,000 at launch, including Google Drive, Slack, Notion, Salesforce, and Microsoft 365. Connect Claude to tools your team already uses.
- Buy Claude-powered agents from companies like Cursor, CrowdStrike, and Snowflake. The cool part: you can use your existing Anthropic budget toward these purchases, no separate billing.
- Hire consulting partners like Accenture or Deloitte if you need help rolling Claude out at scale.
Connectors are built on MCP (Model Context Protocol), an open standard that lets Claude talk to external tools and data sources. Think of it like a universal adapter.
If you’re building something for Claude users, you can list your own tool or agent on the marketplace to reach teams already using Claude.
OpenAI releases open mental health benchmark built with 80 clinicians
Most AI mental health tests only check one thing: does the model avoid saying something dangerous in a crisis? That leaves out most of what people actually talk about. OpenAI just shipped MentalHealthBench to fix that.
It covers the full range of real conversations, scored across three levels:
- Everyday stress, rough weeks, emotional strain
- Serious distress without an immediate emergency
- Crisis situations needing real-world help
The benchmark has 1,215 synthetic conversations, built with over 80 licensed psychologists and psychiatrists across 22 countries and 19 languages. Each conversation has expert-written scoring criteria that reward good behavior and penalize bad ones.
Top scores so far: GPT-6 Astra at 57.3%, Claude Opus 5.5 at 52.4%. Nobody is close to perfect yet.
It is fully open. You can run it on your own app’s prompts and guardrails, not just on big models. If you are building anything that touches user wellbeing, this is the tool to stress-test it.