#OVCEnterprise# WAYTOUS has developed an autonomous #hauling# #robot# supporting #AutonomousDriving#, remote driving, and close-range remote control. It can autonomously complete loading, driving, unloading, and return operations, with multi-sensor fusion for complex conditions.

Had the privilege of visiting the headquarters of Baidu, a remarkable center of innovation and technological leadership. The organization’s culture reflects a clear vision for the future, supported by exceptional talent, ambitious thinking, and a relentless focus on advancing the frontiers of technology. It was particularly insightful to engage with teams driving transformative initiatives across multiple domains and to gain a deeper understanding of how innovation is translated into real-world impact at scale. Experiencing a ride in an autonomous vehicle was especially compelling, providing a firsthand perspective on the maturity of the technology and its potential to redefine mobility in the years ahead. Grateful for the opportunity to learn from one of the world’s leading technology companies and to witness the innovation shaping the future of the digital economy. #Baidu# #Innovation# #FutureTech# #Technology# #DigitalTransformation# #AutonomousDriving#

Today we're releasing @nvidia AlpaGym, our new open-source reinforcement learning (RL) framework for end-to-end autonomous driving. A key challenge for #Physical# #AI# is enabling policies to learn from the consequences of their actions. While supervised learning can teach a model to imitate behavior, robust autonomy ultimately requires learning through interaction with the environment. AlpaGym enables exactly that. Built on top of: - AlpaSim: our high-fidelity closed-loop autonomous driving simulator - Cosmos-RL: NVIDIA's distributed RL training and rollout infrastructure AlpaGym provides the glue that connects simulation, training, and driving policies into a scalable framework for post-training autonomous vehicle models in closed loop. With AlpaGym, researchers and developers can: ✅ Train end-to-end driving policies using reinforcement learning ✅ Run large-scale closed-loop simulations ✅ Experiment with new reward functions, policy architectures, and training strategies ✅ Benchmark models on public leaderboards 📖 Learn how it works: 💻 GitHub: 🏆 Open Challenges: - AlpaSim Closed-Loop E2E Driving Challenge: - Physical AI AV Reasoning Challenge: Learn more about the #Alpamayo# open platform: #PhysicalAI# #AutonomousDriving# #ReinforcementLearning# #Robotics# #OpenSource# #NVIDIA# #MachineLearning# @NVIDIADRIVE @NVIDIAAI

Momenta — the “First Physical AI Stock” Officially Lists Today, the “first Physical AI stock” Momenta officially listed on the Hong Kong Stock Exchange. Its opening share price rose more than 6%, making it one of the most talked-about tech IPOs in the Hong Kong market this year. My first reaction was to check its cornerstone investor lineup: 14 institutions joined forces to underwrite it, with total cornerstone subscriptions of approximately HK$3 billion (about US$376 million). The quality of this lineup is rare among recent Hong Kong IPOs. What is “Physical AI”?
Momenta’s core weapon is its world model — the R7 world model, which entered mass production for the first time in April this year. It supports scaled deployment in passenger cars, Robotaxi, and Robovan, and will later expand into Robotruck and embodied intelligence. Simply put: digital AI (such as GPT) competes in text and images, while Physical AI competes in the physical laws of the real world — and this race has only just begun. Supporting this narrative are solid scale metrics: mass-produced vehicles have surpassed 1 million units, with the fastest delivery of 100,000 units completed in under 40 days. The “flywheel effect” is already in motion. Tech companies are often criticized for “high R&D and difficulty in turning a profit,” but Momenta has achieved explosive revenue growth this time, with cash reserves exceeding RMB 10 billion on its books. This breaks the curse and gives it the confidence to meet the allocation standards of top-tier long-term capital. On the capital side: How crazy was this round of subscription?
Both the public offering and international offering saw oversubscription. In the cornerstone list, GIC and Fidelity International led strongly, each investing US$100 million; BlackRock, Oaktree Capital, and Franklin Templeton followed — with Franklin Templeton appearing on a Hong Kong cornerstone list for the first time in history. On the industrial side it is even more solid, with Mercedes-Benz and BYD both increasing their stakes. The domestic camp includes top players such as Gaoyi, Boyu, China Asset Management, GF Fund, and Pacific Insurance, all of which participated. Long-term capital is famously selective in its taste — it wants hard assets that can ride through cycles and have proven commercial models. So many top institutions betting on one company at the same time shows that the market already regards Momenta as a core, unavoidable target in the AI track. In closing
It is uncommon in the Hong Kong market for a company to simultaneously win the unanimous endorsement of sovereign funds, global top asset managers, industrial giants, and Chinese private equity, mutual funds, and insurance capital. Whether the “GPT moment” of Physical AI will truly arrive still needs time to verify, but at least from the capital reaction to this IPO, the market has already cast its judgment with real money. I’ll end by borrowing a line from inside Momenta: “We hope to write the Eastern Silicon Valley legend together with all Chinese AI companies, embrace the world, and let the world embrace China’s technology.” Wishing Momenta — and all friends following this track — the same luck as its stock code: 688, smooth and prosperous! #PhysicalAI# #HongKongIPO# #AutonomousDriving# #Momenta# #EmbodiedIntelligence#

Autonomous driving is amazing but the true dream will be when the car drops me off right where I’m going and goes off to deal with parking on its own, and then comes back and picks me up when I’m ready to leave