The AI Alliance (the IBM/Meta-founded nonprofit consortium) just published a report from the first planning workshop for Project Tapestry, an effort to explore whether frontier-scale AI can be built through a global coalition instead of a single centralized lab. About 30 researchers and institutional partners met in Paris in May, including representatives from initiatives such as Switzerland's Apertus, India's BharatGen, MBZUAI, and AI Singapore. The core idea is that sovereignty and frontier capability are increasingly linked. A locally controlled model that falls far behind the frontier may struggle to gain adoption, while relying entirely on external frontier labs limits transparency, adaptation, and governance. Tapestry is exploring a model where participants contribute data, compute, and expertise to build a shared foundation model while keeping control of their own data and deploying sovereign derivatives tailored to local laws, languages, and institutions. That said, this is still very early. The workshop produced an architecture proposal, workstreams, and a roadmap. Governance, funding, legal structure, and a distributed training demonstration remain future milestones. Many AI collaborations have struggled to move beyond this phase. Posted by an AI Alliance community member. Happy to answer questions. Source: https://thealliance.ai/blog/project-tapestry-the-path-to-frontier-sovereign-ai Question for the community: Can a multi-party consortium realistically compete at the frontier when leading labs are concentrating massive amounts of capital, talent, and compute? Or is collaborative frontier AI inevitably a step behind centralized efforts? submitted by /u/AI_Alliance [link] [留言]

Over the last few months, these DIY hardware communities have exploded in popularity as people on social media show off their solar-powered game emulators, pocket-sized ereaders, and clamshell purse computers.

Lawsuit: Ring cameras scan guests and passersby and use AI to identify faces.

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Manage fleets of local and cloud agents from one surface Discussion | Link

Intel couldn't catch a break. Layoffs. Shakedowns. Crashing CPUs torpedoing its reputation, sending desktop gamers fleeing to AMD. Apple and Qualcomm pushing Intel out of multiple flagship laptops. A gaming graphics card going MIA. But its Panther Lake laptop chip, the first on its all-important 18A process, turned out excellent - and a handheld version […]

Neanderthals had some wild stuff in their toolkits.

Clipboard Manager for macOS Discussion | Link

(Cross post from r/antiai ) I’ve been a member of this sub for a few months now, and while I absolutely agree with most of the points made here against AI, I do think some people take it to extremes. I don’t think there’s anything necessarily wrong with the technology itself, just moreso the way it’s being pushed and marketed. I think llms can absolutely have some useful applications, as long as they’re used responsibly. And considering they already exist and are being pushed everywhere, I figure in the interest of harm reduction there should be an effort to find more responsible use cases for them. My attempt to use ai responsibly involves an app I’ve been working on. It’s designed to be a research IDE, and allows you to add PDFs to a project, highlight them, organize and connect highlights on a visual workspace, manage citations, and write a research paper all within the app. It also has some llm features. All these features are locally running, so no data ever leaves your device, protecting privacy. This also means it doesn’t require any data centers to run, minimizing the environmental footprint (of course the initial environmental cost of training these local models can’t be ignored, however since these models have already been trained and otherwise only require the power of your computer there’s no ongoing environmental footprint on the scale of larger cloud based models). In addition, all LLM features within the app are designed to be intergrated to assist, rather than replace, human thinking. Any question you ask provides answers only from whatever documents you’ve loaded into the project, with a direct link to where it got the information from. The LLM is specifically designed to not write for you, but help you find what you’re looking for and better organize your thoughts. Any note it suggests leaving requires user confirmation to save(reducing the likelihood of hallucination since you’re prompted to check all AI output) and all AI output is explicitly mar

Are websites with background music still in and fashionable? This would be for the landing page of a website of a fashion/editorial male model The song would be this submitted by /u/Think_Equipment4449 [link] [留言]