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Meta returns to open source with Muse Glimmer, an Apache 2.0 licensed 30B parameter AI model optimized for agents — available now
Meta today released Muse Glimmer, a 30-billion-parameter open-weight model designed to run autonomous AI agents directly on consumer hardware — pushing agentic workloads that normally depend on cloud infrastructure onto high-end Macs and PCs.Just as notable as what the model does is how it s licensed. Glimmer arrives under the permissive, industry-standard Apache 2.0 open source license — the company s first fully open release since it succeeded its open-weight Llama family in April with the proprietary Muse Spark.In fact, Muse Glimmer launches today with a more permissive license than Llama ever carried. Llama s bespoke community license drew years of criticism for restrictions like its 700-million-monthly-user cutoff; Apache 2.0 has no such strings, permitting unrestricted commercial use, modification and redistribution.The weights are available on Hugging Face now. Wang said support is rolling out this week through Ollama, LM Studio, vLLM, SGLang, Together AI, Fireworks AI and OpenR
Meta’s new Glimmer AI model offers a hint at Zuckerberg’s personal intelligence vision
Meta’s new open-weight Muse Glimmer model offers a glimpse of Mark Zuckerberg’s personal superintelligence vision, as well as the emerging divide between AI users can own and access.
The Tragedy of the Cognitive Commons
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Sila lands $1.4B Pentagon loan as militaries demand more batteries
Battery materials startup Sila will use a $1.4 billion loan from the U.S. Department of Defense to scale production at its factory in Washington State.
Four takeaways from Mark Zuckerberg’s massive AI manifesto
Meta CEO Mark Zuckerberg has a lot to say about the idealized future he now envisions for humanity co-existing with artificial intelligence - his latest essay spans more than 6,500 words on the matter. The lengthy manifesto Zuckerberg published on Monday, titled "The Future is for Everyone," broadly lays out his beliefs about how the technology should be developed, expanded, and regulated, and how Meta is positioning itself to enable those goals. Some points echo a similar (albeit, much shorter) public letter that Zuckerberg put out last year, heralding the importance of public access to superintelligent AI - a term for artificial general i … Read the full story at The Verge.
Apple will stream Friday Night Baseball live in Vision Pro
Starting on Friday, August 28th, Apple will begin streaming Friday Night Baseball in immersive video on Apple Vision Pro. The stream will feature commentary from various analysts and reporters, and live graphics will be anchored around the viewers space during the game. After the games conclude, replays will be made available in the Apple TV app. Last year, Apple streamed a selection of live Lakers NBA games to the headset, hoping to entice basketball fans. Baseball adds to its library of immersive content users are able to access on Vision Pro, which also includes immersive content like parkour across Paris and an Alicia Keys rehearsal. … Read the full story at The Verge.
Token-maxxing is dead. Agentic memory is what comes next.
Presented by MongoDB We have been building databases as an industry for roughly 60 years. We have been building AI agents, in the form most people mean when they say the word today, for about 18 months.Sit with that ratio for a second, because it explains almost everything about the state of agentic development right now. Six decades versus a year and a half. We are not in the middle of this learning curve. We are standing at the very bottom of it, squinting up.There is no LAMP stack for agents yet. There is no settled, boring, default set of choices that lets a team stop re-litigating architecture and just ship.One of the earliest lessons came from the industry’s brief obsession with token-maxxing. For a stretch in early 2026, token consumption became a vanity metric. The backlash was fast. Token volume measures activity, not outcomes.But the interesting part of the token-maxxing story was never the workplace theater. It was the architectural lesson hiding underneath it.The context wi
A data breach at shipping giant Ceva Logistics is rippling across banks, retailers, Steam gamers, and beyond
Companies that rely on Ceva Logistics for shipping their physical goods to customers say their personal data was taken during a recent cyberattack.
Mark Zuckerberg attacks 'closed' AI rivals as Meta returns to open models
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Mistral Patent for "Code implemented tool calls"
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Steam hardware shipper breach leaks customer data, including names and addresses
Valve says a data breach may have exposed the personal information of customers who ordered its Steam hardware in Europe. In an email sent to users, Valve says its European shipping partner, CEVA Logistics, suffered a data breach that may have included customer names, addresses, phone numbers, and email addresses. The breach at CEVA occurred between July 29th and August 1st, weeks after Valve began taking reservations for its new Steam Machine and Steam Controller. Valve adds that European customer data "was likely compromised" as part of the breach, as CEVA stores "delivery-related information" for up to 90 days after orders. … Read the full story at The Verge.
Your agent didn’t hallucinate; it exceeded its authority
Content filters can block unsafe output. They cannot tell you whether an agent was authorized to issue that refund, touch that production system, or commit the company to an external action. Those are different problems, and most enterprises are only solving the first one.An AI agent can follow its instructions perfectly and still take an action the business never sanctioned.In commerce environments, I have seen this pattern emerge in practical ways. A service workflow calculates the correct refund amount but lacks a boundary preventing credits above what the business approved for autonomous action. An order agent correctly applies a requested change but overlooks a financing or fulfillment condition. A procurement agent identifies the lowest-cost supplier, but nobody has defined whether it can accept contractual terms or only recommend the option.The agent keeps working. The problem may not surface until something downstream breaks.These are not necessarily AI reasoning failures. They