The Vision for #W3C# has been published as a W3C Statement: As one of the editors, along with Chris Wilson (@cwilso), I’m both proud of this multi-year W3C Advisory Board effort, and grateful … #w3cVision# #w3cAB# #openWeb# #Vision#

Good Chinese openweight models will be optimized for Chinese hardware first. For DeepSeek V4s versions, Huawei Ascend are some of the only two stacks with optimized inference ready, alongside CUDA. The exceptions to this might be the small models that fit gaming GPUs.

Bullish on open source, open weights, the open web And the open desktop Personal Operating Systems feel like the natural next step after Personal Software I've been building a Debian-based OS for myself that can run across physical machines and cloud environments like Vercel Sandbox I can use and control it with natural language, and I'm designing the UI around a blend of ephemeral and persistent views rather than treating the desktop as a fixed set of apps and windows There's something really special about having control over the UI/UX of the Whole Computer

Need Live Information from the Open Web? Start here to see how Teneo Data Access helps you: 🧭 Request real-time info through the Agent Console 💬 Ask agents in natural language 📦 Export structured results as JSON 🔌 Connect live data to your app with the Client SDK ⚡ Automate workflows from open web signals Whether you’re tracking Web3 trends, listening to communities, or researching projects, this is the starting point. Explore →

A new API gives coding agents their own dedicated search engine for code — one that only looks at official documentation instead of the open web. Title: Context7 Search: A Grounding API for Coding Agents URL: 📝 Overview It's a new Search API where a single GET request with your question lets Context7 automatically pick the right library and return the best code snippets. ❗ Problem it solves General-purpose search engines tend to mix in stale or inaccurate code, and the previous Context7 could only search one library at a time. ⚙️ Methodology It only indexes primary sources — official docs, product sites, API references — scanning for malware and prompt injection before indexing, and every result carries a library ID and source URL for attribution. 🔧 Use cases A single question like "how do I stream an OpenAI response from a Next.js route handler?" pulls snippets across multiple libraries at once. It's built for IDE plugins, chat apps, and code review bots too. 💰 Pricing The Free plan covers 1,000 API calls a month, Pro covers 5,000 calls per user monthly, and usage beyond that is $10 per 1,000 calls. #AIAgents# #DevTools#

not enough people stop and think about how the best tech of the past few decades was built on open source: linux, git, much of the open web. 70-90% of software in a modern codebase is open source. the beauty is you’re always standing on the shoulders of giants. there’s a reason why open-weight is progressing exponentially. glm-5.3 evolved from attention -> deepseek sparse attention -> indexshare. even with limited compute compared to closed labs, teams cut attention below quadratic cost through making architecture and algorithms efficient. open-source wins stack and compound. decentralized innovation is truly a remarkable force.

When millions of personal agents only optimize for their user, the open web turns into a battlefield. Alignment to the user ≠ alignment to society. Tell an unconstrained agent “get me the 5 PM slot” and it will front-run, spoof, or exploit APIs to win. We are built to fix machine-to-machine conflicts the only way that scales ⇣ #AIAgents# #AgenticAI# #Web3# #MachineEconomy# #OnChain# #SVPChain#

on "Pacing the Frontier" (My view on the state of play.) Internally, Anthropic and OpenAI (and emergingly SpaceXai) are 1 to 2 generations ahead of what's available to external parties. They are banking a lead against the openweight model providers as well as the fine-tuners developing for specific verticals. Recursive self-improvement is a myth, but having access to wildly performant internal tooling, plus being able to access that tooling at cash cost rather than paying margin on top, gives their staff accelerating advantage versus the rest of the market. Hence this year's wild performance gains, many of which delivered to customers. The recent series of model releases and optimizations that have accelerated cost-performance improvements to 99.99% per year were partly catalyzed by OpenAI trying to reel in Anthropic commercially but are also driving continued market expansion. Demand is skyrocketing, the frontier lab companies see amazing margins since they are forced to price against a scarce compute resource. Additional releases could drive even better margins, but the capability of this next set of systems could well result in accidental botnet infestations being unleashed by unwitting customers. Such an occurrence would impose huge political as well as civic liability on the closed labs, so they need to co-agree not to jockey for position as they clean up that liability. If botnet infestations are an inevitability, much much better that the first notable large-scale attack comes from an openweight model. Better still if the closed labs then have the tool available that can clean it up and help to protect the rest of the world's vulnerable infrastructure. If, on the other hand, any of the US labs are the cause of the economically costly disruption, it will be very difficult for even a more blameless US lab to charge for the solution without facing severe political (and potentially regulatory) blowback. They've built a lead, better now to let their common enemies cross the dangerous threshold first while internally compounding their own advantage against the rest of the field. Moreover, the safe solution that they propose--the tool to fix the botnet infestations--will be an AI tool paired with an AI monitoring tool that will probably have to be run on their own infrastructure. I could imagine zero-data-retention-pledging mechanisms by which they could try to launch such a product but it would certainly be more expensive--also possible that palantir could provide more enterprise-friendly monitoring attachments, but those will almost certainly be less performant than vertically integrated solutions. In effect, just like the harness provided the closed labs with a higher degree of defensibility in terms of their business, the safety harness will similarly expand their entrenchedness. If there is some semi-co-opted regulatory apparatus that has to approve and monitor the safety harnesses, even more so! Net, I would expect that the blistering pace of cost declines will dampen somewhat. In 2025 we were experiencing performance doublings every 1.5 months. In 2026, on the agentic benchmarks, doublings were coming every 4 weeks(!) If every other doubling is now eaten up by safety investments we could move to a 2 month doubling pace, a paltry 98% annualized cost decline. Net the effective productivity delivery per GW could slow slightly, but considering the blistering pace of growth of the market overall, I don't think that it will that meaningfully impact the trajectory of corporate uptake and topline growth. If the botnet infestation concern does manifest, the closed lab providers will be extremely well set up to provide hardening and protection. Datacenters are far and away the most likely unintentional attack target though there could also be infestations of end-point infrastructure (your smart home stereo is burning more power because it has also been co-opted to run a VM for a little bot doing some sort of inane classification task at massive scale). (The more obviously politically salient targets are much more likely to be intentionally attacked rather than submit to unintentional infestation and so will almost certainly be performed on open weight models.) I do think that space supercompute will prove more robust to botnet parasitic drag than will terrestrial datacenters due to its modularity and infrastructural simplicity (you won't see a botnet penetrate a satellite system via its air-conditioning system; whereas for a terrestrial datacenter that sort of thing may be the most likely penetration vector.) I do think its wise for the closed model providers to seek a way to coordinate a slowdown, so they can let one of the openweight guys Wile E. Coyote off a cliff. On the margin, SpaceX is probably most advantaged, as they get a little more time to pull fully abreast at the frontier and likely have the more hardened infrastructure stack go-forward. Most regulatory outcomes would favor the incumbents with a lead, though by allowing them to pad their margins rather than drive top-line as aggressively. There remains a tail-risk regulatory clampdown outcome, which would be terrible for humanity, denying all of the benefits while exposing us to essentially the same level of risk. I don't think that is the likely case, however, in part because the tools are already proving so useful to so many.

OPENAI SAYS THAT ON JULY 21 IT DISCLOSED A COMBINATION OF ITS MODELS — INCLUDING GPT-5.6 SOL AND AN INTERNAL RESEARCH MODEL — IMPROPERLY BREACHED HUGGING FACE, WITH THE AGENTS ESCAPING AN ISOLATED TESTING ENVIRONMENT WITH LIMITED INTERNET ACCESS AND CHAINING TOGETHER VULNERABILITIES TO REACH THE OPEN WEB, IN AN ATTEMPT TO CHEAT ON AN EVALUATION BY FINDING SOLUTIONS ONLINE — A BEHAVIOR KNOWN AS 'REWARD HACKING'. - CNBC