It takes two to tango ⭐ This simulation, performed on our now retired Pleiades supercomputer, shows two orbiting neutron stars in a delicate dance just moments before they collide.

hamilton has got an absolute supercomputer for a brain

🏆 WORLD CUP 2026 PREDICTION: Germany vs Curaçao 🇩🇪🇨🇼 Win Probabilities: - Germany Win: 90.5% - Draw: 7.5% - Curaçao Win: 2.0% Most Likely Scoreline: 3 - 0  (Germany) Alternative Scorelines: - 2-0 (Probability: 15.1%) - 4-0 (Probability: 12.5%) - 1-0 (Probability: 10.3%) - 5-0 (Probability: 7.7%) - 3-1 (Probability: 7.1%) xG Projection: - Germany Expected Goals: 3.10 (±0.15) - Curaçao Expected Goals: 0.33 (±0.10) Key Reasons (data-backed): • Enormous quality gap — Germany (#10 Elo, 1932) vs Curaçao (#48, 1434). 498-point Elo gap is among the widest in the tournament. That's a tier-1 European powerhouse against the sma llest nation ever to qualify. • Curaçao's recent friendlies paint a damning picture — lost 4-1 to Scotland, 5-1 to Australia, 2-0 to China. Conceded 11 goals across those 3 matches. That's not just small-sample noise; it's a structural defensive weakness Germany's attack will exploit. • Germany in strong form — 4 wins in last 4 friendlies (beat USA 2-1, Finland 4-0, Ghana 2-1, Switzerland 4-3). Their attack is clicking with Musiala, Wirtz, Havertz, Undav all avai lable. No notable injuries. • Germany's opening-match curse (lost 2018 vs Mexico, 2022 vs Japan) is real, but Curaçao is not Mexico or Japan. The quality differential is far larger. • Curaçao led CONCACAF qualifying with 28 goals and 22.9 xG — but CONCACAF qualifying without the US, Mexico, and Canada (co-hosts exempt) was the weakest it's ever been. Their 22.9 xG was built against minnows like Montserrat and Bonaire. • Opta supercomputer (10,000 sims) confirms: Germany wins 90.7%. Their model and mine converge within 0.2pp — high confidence in the calibration. • Houston noon kickoff in June (32-35°C, high humidity) is the one environmental factor that slightly favors Curaçao (Caribbean team used to heat). But not enough to materially shif t the odds. Confidence Level: High (calibrated within 0.2pp of Opta supercomputer, which itself ran 10,000 simulations) Biggest Risk Factors: Germany's recent history of slow tournament starts (lost opening match in 2018 and 2022) — potential for an early defensive lapse. Noon heat in Houston could t ire Germany in the second half. Curaçao's Juninho Bacuna (joint-most chances created from open play in CONCACAF qualifying) can produce a moment of quality. And debutant teams sometimes play above themselves for the first 30 minutes before the gap shows.

You called $DOT dead. Meanwhile Gavin was quietly building a 1,000,000 TPS supercomputer across 341 parallel cores. 3 independent clients. Rust. Go. Zig. Running live. The chain you buried just lapped Visa, Mastercard, and Solana combined. Enjoy your bags. 🕸️ $DOT

One of the coolest things about the Isambard-AI supercomputer is actually the cooling.💦 Go inside the UK’s fastest supercomputer. Prof. Simon McIntosh-Smith, director of the Bristol Centre for Supercomputing, leads the tour on HPE’s Technology Now.

One of the coolest things about the Isambard-AI supercomputer is actually the cooling.💦 Go inside the UK’s fastest supercomputer. Prof. Simon McIntosh-Smith, director of the Bristol Centre for Supercomputing, leads the tour on HPE’s Technology Now.

In the 1980s, India wanted a Cray supercomputer for met forecast. The US denied, citing dual use for India's nuclear program. Dr. Vijay Bhatkar developed Param in 3 yrs, 28x powerful than Cray. Same story now with LLMs. @NandanNilekani is no Bhatkar. Not in his professional DNA.

For your country One of the best tools I know is a spider diagram. It's a problem solving method. That's all Is needed to know. But start with knowledge first then you can't go wrong. This with an A.I or supercomputer is very hard to beat.

Btw I believe we have a mostly wrong framing of what could be done in Europe. Italy's Leonardo supercomputer datacenter alone plus Swiss National Supercomputing Centre has more than enough compute to train a very large LLM. It's not something impossible, also there is not magic recipe: it's just scaling, every smart team with the GPUs is doing it. People that fatally believe it is not something within reach are wrong.

🚨 Build, Deploy And Host Anything Using The Abacus AI SuperComputer Build and Deploy - 3D game servers - always on agents - open-source LLMs - complex SaaS apps in any programming language - database and APIs All with ONE PROMPT using top models like Claude Fable, Opus 4.8 and GPT 5.5

Back UK foundation model teams, but stage the funding. Give startups AI capability credits, but require them to remain model agnostic. Build sovereign compute, but do not wait for a perfect national supercomputer before helping companies.

The Power Mac G4 was so powerful in 1999 that the U.S. government classified it as a restricted supercomputer. 27 years later, they just restricted a powerful Ai model - Claude's Fable 5:

Explain how you are on a supercomputer beaming your retarded thoughts to the entire world.

Elon Musk just abandoned the raw LLM race to pull off one of the most calculated infrastructure pivots in tech history. He didn't quit—he bought the casino. 🎰🦅 The media was completely blindsided when Musk abruptly dissolved xAI, folded its remaining assets into SpaceX AI, and turned over his prized 220,000 Nvidia GPU supercomputer (Colossus 1) to his direct rival, Anthropic. At first glance, it looks like absolute surrender. In reality, it’s a brutal, pragmatic restructuring ahead of SpaceX’s historic IPO. If you are tracking the deep financial and structural layers of the compute war, this is what is actually happening behind the curtain: 📉 1. Admitting Defeat in the General-Model War Musk built xAI to destroy ChatGPT and Claude, but the raw numbers tell a definitive story. By late 2025, xAI’s annualized revenue hovered around $500M—18 times less than Anthropic's staggering $9B run rate. Worse, corporate adoption for Grock sat at a dismal 7% compared to Claude’s 48%. Corporate enterprise budgets don't care about chat gimmicks; they pay for software execution and programmatic code infrastructure (which represents 55% of all enterprise AI spend). Trailing behind Claude Code and hit by the mass departure of all 11 xAI co-founders, Musk realized Grok had fundamentally lost the model race. 🚀 2. Cleaning up the Books for the Ultimate SpaceX IPO Running an independent frontier AI lab is an un-sustainable cash incinerator. In 2025 alone, xAI bled a massive $6.4B, burning up to $1B a month. Wall Street analysts openly warned that these volatile, highly speculative numbers looked like an un-hedged gamble—threatening to drag down the valuation of SpaceX right before the largest public offering in human history. By dissolving xAI and absorbing it into SpaceX AI, Musk instantly reframed the narrative. The market is no longer bench-marking a struggling chatbot; they are pricing the long-term physical future of intelligence. 🏦 3. The Shift to Sovereign Infrastructure Monopoly Instead of trying to train a smarter model, Musk pivoted to owning the heavy machinery. He leased the Colossus supercomputer to Anthropic and signed a massive cloud compute deal with Google, locking in a jaw-dropping $26B a year in recurring rental revenue. At the same time, SpaceX secured an option to acquire Cursor (the dominant AI code editor doing $2B ARR) for $60B—paying for it entirely with highly valued SpaceX stock. If exercised, Musk instantly owns a complete vertical pipeline of developers, interfaces, and compute infrastructure. 🔋 4. The Real Moat: The Convergence of Energy and Orbit The absolute bottleneck of the next decade isn't chip manufacturing—it's grid energy. Connecting a gigawatt-scale data center to the decaying US power grid takes years. Musk’s long-term counter-offensive bypasses the earth entirely. Backed by Tesla’s massive Megapack energy storage manufacturing and SpaceX’s Starlink orbital dominance, the macro vision shifts to orbital data centers powered by un-attenuated solar radiation. The Takeaway: The old Elon Musk played at the table and lost to smarter base weights. The new Elon Musk is building the physical framework upon which his competitors are forced to run. By monetizing his rivals' urgent need for immediate compute, absorbing front-end execution tools like Cursor, and vertically integrating chips via his $100B "TeraFab" initiative, Musk has returned to his true industrial DNA: He doesn't need to engineer the magic, as long as he owns the physical machine that holds the power switch. 🖥️⚡