Alibaba Qwen3.7-Max climbs to No. 2 in global AI coding rankings
Qwen3.7-Max ranked among the top four models overall, breaking what had been a prolonged dominance by Claude-Opus-4.7 and Claude-Opus-4.6.
Qwen3.7-Max ranked among the top four models overall, breaking what had been a prolonged dominance by Claude-Opus-4.7 and Claude-Opus-4.6.
Investor interest in world-model-based embodied AI has accelerated in recent months as startups pursue alternatives to data-intensive robotics training approaches.
Repeated filings have highlighted challenges such as Hong Kong’s six-month IPO validity rule, the company’s persistent losses and low margins, and regulatory concerns over its heavy reliance on Geely.
In 2015, at age 31, Cao Matao launched Tao Motor with 28.5 million yuan ($4.2 million) in startup capital from his grandfather, focusing on electric golf carts and scooters.
The company announced the milestone on May 26 at its AI payment ecosystem conference, describing the platform as the world’s first large-scale commercial AI-native payment infrastructure.
Selected companies span sectors including general AI, brain-inspired computing, synthetic biology, low-altitude aviation and frontier chip technologies.
The system combines computer vision and language-based reasoning to detect traffic incidents including debris, illegally parked vehicles and pedestrians entering highways.
The latest order signals a clearer pivot: after consolidating its position in AMRs, Guozi is accelerating its push into humanoid robotics, a field still in early commercial development.
The company framed the shift as part of a broader industry transition from model training to inference-driven applications.
Fracture treatment for complex breaks has relied for more than a century on metal fixation devices such as plates and screws.