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24-YEAR-OLD KID IN CHINA JUST INVENTED A BACKPACK THAT PRINTS MONEY ON AUTOPILOT He throws on a custom rig loaded with cameras, walks into any hotel, apartment, or shop, and in only 20 minutes creates mind-blowing 3D virtual tours. They’re so realistic you can walk around every room on your phone like you’re physically there. No more guessing. No more bad surprises. Guests see exactly what they’re booking. Property owners are going crazy for it: - cancellations drop hard - bookings skyrocket - reviews get significantly better He charges $400 per scan, plus $99/month for hosting. Do the work once → get paid every month forever. This isn’t a prototype. It’s live, profitable, and scaling right now using 3D Gaussian splatting + Luma AI. He basically turned boring property listings into addictive, video-game-style experiences, and he’s cashing in big time with one backpack. The smartest hustle of 2026? This kid didn’t chase the future, he built it and started printing money. Who else wants to copy this model?

The Ultimate Reality Check: Isomorphic Labs Prepares AI-Designed Drugs for Human Trials DeepMind spinoff Isomorphic Labs is on the verge of launching human clinical trials for drugs designed entirely by artificial intelligence. Moving beyond basic target identification or lab demonstrations, this milestone marks a shift from computational predictions to real-world patient outcomes. Built on Nobel Prize–winning AlphaFold breakthroughs, these novel molecules will target cancer and immune-driven diseases. If successful, they could fundamentally rewrite the drug R&D playbook. Key Milestones & Capabilities - End-to-End Design: Isomorphic Labs has built a diverse pipeline of new medicines by combining AlphaFold 3–class structural biology with its proprietary IsoDDE design and optimization engine. - Transition to Patients: Speaking at WIRED Health London in April 2026, President Max Jaderberg confirmed the company is gearing up for clinical trials to test real-world efficacy. - Precision Engineering: Rather than merely speeding up screening, the AI models how proteins, ligands, and nucleic acids fit—and flex—together. This lets scientists design candidates upfront for potency, selectivity, and safety, theoretically enabling lower doses and fewer late-stage trial failures. - High-Stakes Focus: The initial pipeline targets oncology and immunology, where high selectivity is crucial to avoiding toxic side effects. High-profile partnerships with Eli Lilly and Novartis have already produced strong preclinical candidates moving toward human testing. The Shift This marks the evolution of AlphaFold’s legacy—from asking, “What does the target look like?” to tackling the ultimate question: “What molecule should exist, and how do we optimize it for humans?” What This Means for the Future of Medicine Traditional drug discovery is notoriously slow and high-risk, often taking 10–15 years and billions of dollars, with most candidates failing in clinical trials. By autonomously exploring vast chemical spaces, predicting binding success, and iterating rapidly, AI flips this paradigm. If these upcoming trials succeed, it could compress development timelines, unlock previously “undruggable” targets, and accelerate the delivery of life-saving treatments to patients.