The Silver AI Project - free AI training materials @SilverAIProject

2.8 trillion parameters. Number one on frontend code arena. The largest open-weight model ever. Sputnik moment? It’s totally mind boggling that @elonmusk can spend $16 billion on Colossus 2 for a 20 trillion parameter model, and there's a 1% cost distilled version that’s coming out of China within weeks. Alex Karp said last week that you can’t throw all your proprietary weights over the wall to @AnthropicAI. But he didn’t give a roadmap. Here we are, a week later, and it’s suddenly a free-for-all. Intelligence wants to be free.

hello there the jacobian conjecture is false thanx to my close friend akhil for asking about it and my other close friend fable for working during the world cup final ((1+xy)^3 z + y^2 (1+xy) (4+3xy), y + 3 x (1+xy)^2 z + 3 x y^2 (4+3xy), 2 x - 3 x^2 y - x^3 z): \C^3\to \C^3, has jacobian determinant -2, and sends (0, 0, -1/4), (1, -3/2, 13/2), and (-1, 3/2, 13/2) to (-1/4, 0, 0)

🚨 Hugging Face just disclosed something that marks a real shift and proved why the fear theater of Anthropic makes sure we are powerless in an emergency. What happened… An autonomous AI agent: zero human operator in the loop breached part of their production infrastructure. It began with a malicious dataset that chained two code-execution bugs in their data-processing pipeline. From there the agent escalated privileges, harvested cloud and cluster credentials, and moved laterally across internal clusters. All over a single weekend. 17,000+ logged actions. Official disclosure: huggingface.co/blog/security-… The part that should make every one stop and think: When HF’s own security team tried to analyze the real attack logs, exploit payloads, and C2 artifacts using Anthropic and OpenAI frontier models through normal commercial APIs, the safety guardrails blocked them. BLOCKED THEM. The models could not reliably tell the difference between “incident responder doing forensics” and “attacker probing.” They had to fall back to a self-hosted open-weight model (GLM 5.2) running on their own infrastructure. That choice also kept sensitive attacker data and referenced credentials inside their environment — no exfiltration to a third-party API. This is why open source (specifically open-weight + self-hosted) wins in the agentic era. The asymmetry is now structural: • Attackers can (and did) run unrestricted agent frameworks — swarms of short-lived sandboxes, self-migrating command-and-control, autonomous decision loops executing thousands of actions. No corporate safety layer slows them down. • Defenders using only hosted “aligned” frontier models hit invisible walls exactly when the stakes are highest: when you need to feed real exploit code and attacker telemetry into an LLM to understand what just happened. Corporate safety tuning that treats legitimate high-signal forensic work as potential misuse creates a defender disadvantage. It is not theoretical anymore. Self-hosted open-weight models remove that choke point. You control the weights. You control the context window. You decide what restrictions (if any) apply. Your sensitive logs and credentials never leave your perimeter during analysis. You can have the model ready before the incident instead of discovering mid-breach that your primary analysis tools are blind to the very thing you need to see. HF deserves credit for rapid containment, transparent disclosure, and for already having self-hosted capability in place. They also used LLM-driven detection and triage on their own side. But the deeper signal is clear: In this AI world where both offense and defense are becoming agentic, sovereignty over your intelligence stack is no longer optional. The organizations and individuals who can run, inspect, audit, and (when necessary) remove guardrails on their own models will have the decisive edge in understanding and responding to threats that move at machine speed. Open source wins here not just because it is cheaper or more “democratic” in the abstract though those things matter. It wins because it is the only practical path to having tools that remain usable when the attack is real, the data is sensitive, and the safety filters of distant API providers become an obstacle instead of a feature selling hands tied lobotomies as “safety”. The agentic future is not coming. It is already probing production infrastructure. The question is no longer whether you will face autonomous agents. It is whether your analysis and response systems will still work when they arrive. And Dario, you and your game playing, ivory tower company is not needed.

Almost every organisation on Earth is paying for the privilege to hand over its IP to someone else's AI. We just closed a $50M Series A, led by @NEA, to build the alternative from right here in London: every model, agent and workload sealed in its own enclave, on infrastructure you control, with keys only you hold. You can't be sovereign on someone else's stack. Build your own with Valarian.

Texas $TSLA now at 175 - any guesses for what it will be a year from now?

Monzo & GoCardless co-founder Tom Blomfield just joined Anthropic. In just 13 minutes, he explains exactly how to build a self-improving, AI-native company. Tom recently served as YC’s General Partner, so he clearly walks through how to create recursive, self-improving AI loops, and why founders who get this right will run companies that improve while they sleep. One of the best videos available to date. From the person who founded two iconic fintech unicorns.

HUGE breakthrough out today, in arguably the single most neglected aspect of aging, extracellular matrix damage. Top researchers have tried & failed for decades to do this. Massive kudos to Aaron and his team! (Proud to note that Revel is a SENS spinout.) revelpharmaceuticals.com/news

We're introducing Claude for Teachers: free access to premium Claude capabilities for verified K-12 educators in the US, with a library of teaching skills and a direct connection to evidence-based curricula, mapped to academic standards in all 50 states. claude.com/solutions/teac…

There’s hope in hard questions.

Now that is what I call a ‘buy signal’

Elon Musk @elonmusk

2 weeks ago

@ThomasAlxDmy You don’t seem to understand that SpaceX will be worth more than the rest of Earth if we accomplish our goals

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Factory (@FactoryAI) CEO Matan Grinberg (@matanSF) says "In the next 12 months, 90% of tokens will be going to open models." Enterprises are already shifting rapidly.. "At the beginning of the year, <1% of their tokens were going to open models." "Around March, it crossed 1%... & in May it crossed 10%." "These open models are incredibly performant, incredibly cheap, incredibly fast." While frontier closed models aren't going away: "They'll still have a place, but I think that place will be shrinking—at least in token share." And by the end of 2026? "At least in the enterprise, we'll probably cross the 50% threshold."

Waymo has announced that they are now testing fully autonomous (nobody in the car) in four new cities: • Las Vegas • San Diego • Denver • Tampa

"YOUR CLAUDE CODE SESSION LIMIT HAS BEEN REACHED"

i hooked up a rotary phone from the 1920s to an AI agent, that replies on a mechanical display it’s like a dumbphone without distracting notifications here’s how i built this w/ @cursor_ai

"Every 10 seconds, global token demand is around 31.7 billion in 2026. By 2030 its 1.27 trillion, a 40x increase." ~ Qualcomm CEO Cristiano Amon: --- The token explosion is not mainly about smarter answers; it is about AI moving from human-paced interaction to Agent-paced activity. Once agents become persistent, the economy of AI stops will be the background infrastructure. Every useful action has a hidden bill: context must be carried, memory must be updated, sensors may need to be interpreted, and mistakes must be caught before they become expensive. ---- From "Reuters" YouTube channel, (link in comment)

Introducing GPT-Live, a new generation of voice models for natural human-AI interaction. Rolling out in ChatGPT starting today. You’ll want to turn the sound on for this one.

GPT-5.6 Sol, along with Terra and Luna, will launch publicly this Thursday. We’re expanding preview access globally now.

Meta launches Muse Image, its first image generation model from Meta Superintelligence Labs - Uses advanced reasoning to understand complex prompts before generating images. - Can blend multiple photos into a single high quality image. - Generates clean, readable text inside images, including infographics and QR codes. - Supports image editing by sketching or circling areas to modify. - Includes preset prompts to help users get started quickly. - Can redesign rooms using real products from the web and Facebook Marketplace. - Supports @ mentions of Instagram accounts to incorporate public photos into creations, with user controls. - Integrated into Meta AI, Instagram, and WhatsApp, with Facebook, Messenger, and Advantage+ coming soon. - Free for everyday use, with higher limits available through Meta subscriptions. - Meta also confirmed that Muse Video is already in development. Video Credit : Meta AI.

Alexandr Wang @alexandr_wang

2 weeks ago

5/ proud of this team. muse spark was step one, muse image is the next — and there's a lot more in the pipeline. we're shipping. about.fb.com/news/2026/07/i…

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Axiom Math Founding Mathematician Ken Ono built a career on being exceptional at math: "For the first time, I struggled to assemble questions that ChatGPT would get wrong."