Research firm BMI’s new Metals And Mining Megatrends To 2050: Navigating A New Era Of Technology, Geopolitics And Green Transformation argues that over the next quarter century, the mining industry will increasingly venture north of the 60th parallel, kilometres below the ocean surface and, eventually, beyond Earth’s orbit. The pull towards the arctic, the seafloor and ultimately space has many drivers. Historic reserves are maturing, ore grades are declining and the energy transition and the trillion dollar data center build-out are creating supply bottlenecks from specialty materials like indium phosphide and samarium-cobalt through to everyday essentials like copper. Robotics will be next decade’s metals chokepoint (look for a tipping point once humanoids start building humanoids) but physical AI and autonomy are already making it cheaper to operate and explore safely in harsh and high-cost environments. AI and subsurface intelligence are helping miners deal with deeper deposits, lower grades and long development timelines, with one example showing how AI-supported geoscience can reduce uncertainty and improve permitting confidence...

Here's a question. Why are these supposed aliens humanoids? Why are they so morphologically similar to us? Could it be that people are just anthropomorphically projecting our species characteristics?

Consumer humanoids are becoming a real category. @UBTECHRobotics unveiled 'U1 Pro', a full-size humanoid designed for home companionship. 1,943 pre-orders ahead of its June 30 launch, making it one of the first large-scale tests of consumer demand for highly human-like robots.

Elon Musk reveals SpaceX is building a 30,000-robot academy where humanoids learn from each other. Cars were easy. Tesla had ten million on the road, beaming back driving data every second. But humanoid robots? There weren't ten million Optimi yet. There weren't ten. Robotics had run data-starved for decades. Tesla decided to fix it. You couldn't train a humanoid that had never been deployed. So Musk built a school for them instead. "We can have at least 10,000 Optimus robots, maybe 20-30,000, that are doing self-play and testing different tasks." Tesla called it the Optimus Academy. Picture a warehouse the size of a chip fab. Thirty thousand humanoid robots inside. Picking things up. Folding clothes. Walking. Tripping. Catching themselves. Failing in ways no human roboticist had thought to script. Each watching the others, learning what the human body shouldn't have made look easy. Every move generated a data point. Every failure generated a sample. Every robot taught every other robot. In simulation, Tesla could spin up a million robots overnight. But simulated physics lied about friction, slip, and drift. Real physics didn't. Cars learned from drivers. Optimi learned from each other. Each generation made the next one cheaper, faster, smarter. By the tenth generation, no human would recognize the curriculum. Recursive learning at electromechanical scale. Musk, on closing the loop: "You use the tens of thousands of robots in the real world to close the simulation to reality gap." Whoever opened the academy first owned the species. P.S. I made a playbook breaking down 100 most powerful decision making mental models used by history's greatest thinkers. 5,000 downloads. 113 five-star reviews. Grab a free copy here: besuperhuman.gumroad.com/l/m… If you're new here, follow @GeniusGTX for content on the greatest minds in economics, psychology, and history. — Elon Musk ( @elonmusk ), CEO of Tesla and SpaceX, on Dwarkesh Patel's ( @dwarkesh_sp ) podcast

China Accelerates Deployment of Humanoid Robots in Real Scenarios. 🇨🇳 China is pushing humanoids and embodied AI into factories, logistics, retail, healthcare, safety, emergency response, and disaster prevention. The key is the real-robot data loop: train in real sites, collect task data, then use it to improve models, hardware components, safety, and deployment. The 2026 target is clear: 100 high-value scenarios and the capability for 10,000-unit-scale rollout. For humanoids, this is the shift that matters: fewer staged moves, more useful work.

Do female humanoids not know that this gay larp is extremely unattractive. "Let's emulate the group of men that are incapable of getting a girlfriend". Girls should like flowers and dresses and birds and stuff.

If you think humanoids are people...

🤖 The Humanoid Robot Race Is Accelerating Faster Than Most Investors Realize Just as the AI boom created trillion-dollar opportunities in chips and cloud computing, the next wave may be physical AI. China’s leading humanoid robot companies are now rushing toward IPOs in Shanghai and Hong Kong, signaling that the industry is moving from research labs to mass production. Some of the names to watch include: 🔹 Unitree Robotics – Global leader in quadruped and humanoid robot deliveries, reportedly targeting a valuation of around $7 billion. 🔹 DEEP Robotics – Industrial quadrupeds and next-generation autonomous robots. 🔹 Leju Robotics – Already mass producing Kuavo humanoid robots. 🔹 EngineAI – Preparing for a Hong Kong listing with a focus on intelligent humanoid systems. 🔹 Agibot – Expected to manufacture 20,000 humanoids in 2026, one of the largest production targets announced so far. 🔹 Galbot – Already deploying robots in unmanned retail stores. 🔹 PUDU Robotics – Expanding from service robots into industrial automation. What does this mean for U.S. investors? The biggest winners may not be the robot manufacturers themselves, but the companies supplying the brains, eyes, and muscles. U.S. stocks I’m watching 🤖 $NVDA – AI computing platform powering physical AI and robotics. 🤖 $TSLA – Optimus could become one of the world’s largest humanoid robot platforms. 🤖 $AVGO – High-speed networking connecting millions of intelligent machines. 🤖 $AMBA – Edge AI vision chips that allow robots to see and understand their environment. 🤖 $SYM – Warehouse robotics already operating at commercial scale. 🤖 $TER – Through Universal Robots, a leader in collaborative robotics. Long-term investment thesis The first AI revolution taught computers to think. The next revolution will teach machines to walk, see, pick up objects, deliver packages, work in factories, stock shelves, and assist people in everyday life. We’re moving from digital AI to embodied AI. The companies building this ecosystem today could become the infrastructure leaders of the next decade. The AI race is no longer happening only inside data centers—it’s stepping into the real world. 🤖🚀

"all of them have two arms and two legs" "look like a guy from sweden except seven feet tall" So the generic alien media of humanoids everywhere is actually accurate...

$USAR --- On June 11, 2026, $USAR formally signed a definitive agreement with the U.S. Department of Commerce, securing a $1.6 billion funding package under the CHIPS and Science Act (including direct grants and guaranteed loan capacity). This capital directly accelerates Round Top mine development and expansion of refining and magnet manufacturing facilities in Oklahoma and South Carolina. Most importantly, the U.S. government becomes a strategic partner through equity and warrants, providing the strongest possible political endorsement. Beyond domestic development, $USAR is accelerating acquisition of Brazil's Serra Verde rare earth project and leveraging its UK subsidiary for international market access, targeting 10,000 metric tons annual rare earth magnet production capacity by the early 2030s. 1.The Invisible Arms Dealer for AI Compute and Humanoid Robotics Market focus on AI has expanded beyond software and optics to the deepest physical hardware layers. AI Data Centers: Massive compute scaling creates extreme thermal management demands. High-performance liquid cooling systems, high-power server fans, and next-generation clean power (SMR modular nuclear reactors) all require massive quantities of high-performance rare earth permanent magnets. Humanoid Robotics: Whether Tesla's Optimus or other leading humanoids, the core joint components – brushless and servo motors – require exponentially growing volumes of high-coercivity, lightweight neodymium magnets. 2.Geopolitical Re-Rating – Ex-China Supply Chain Premium Virtually the entire global rare earth and magnet supply chain is currently concentrated in China. Amid current geopolitical tensions, urgency for ex-China supply chains across U.S. defense, semiconductors, and clean energy has reached unprecedented levels. As one of the very few companies capable of domestic "mining-refining-magnet manufacturing" vertical integration, USAR commands an extreme sovereignty premium. 3. Financial Optionality and Fundamental Turnaround Analysts project explosive revenue growth as capacity comes online. Wall Street Consensus: Revenue is expected to scale from current single-digit millions to hundreds of millions – potentially reaching $1.5 billion by 2029-2030. Once profitability inflects around 2028-2029 (EPS projected to turn positive from current losses to over $0.20), the stock is poised for a classic tech-style "double upgrade" re-rating.

Something always confused me about first encounter with Allen... Why didn't Allen immediately know Nolan was a viltrumite? Are earthing looking humanoids that common in the galaxy? Is Allen just ultra open-minded or extremely stupid? #invincible

Watch: Humanoid Warbot Live-Fires Mortars at Vegas Test Range. Launching mortars and soon breaching doors have become near-term proofs of humanoids moving from logistics to kinetic engagements. zerohedge.com/military/watch…

Wheeled humanoids are more efficient, cost-effective and ready to ship than bipedal humanoids today. Most industrial floors are flat anyways so the terrain problem that legs solve barely exists. Legs will matter eventually but the first real commercial wave of humanoid ROI is going to roll, not walk.

There was a multi-part episode of TNG that actually provided a very logical explanation for this: a dying alien race, in an attempt to keep their uniqueness alive, seeded multiple developing planets of the galaxy. Therefore, all of the separate "races" of humanoids were related.