Toyota Successfully Trains AI Robots to Make Breakfast, Breakthrough in Tactile Learning Technology


Recently, X-ORIGIN-AI announced the successful completion of hundreds of millions of RMB in angel round financing, led by Alpha Community, with multiple industry investors participating in the follow-up investment, and Ren Chen Capital serving as the exclusive financial advisor. The funds raised will mainly be used for technology research and development, talent recruitment, and market expansion, aiming to further advance the development and implementation of its all-scenario consumer-grade AI robot products. Image source note: Image generated by AI, image authorized by service provider Midjourney. X-ORIGIN-AI focuses on developing companion robots.
The Toyota Research Institute has partnered with Stanford University to incorporate artificial intelligence into two Toyota Supra sports cars, enabling synchronized driving similar to Formula drifting. This innovation not only showcases an impressive performance but also marks a milestone in the development of safety systems for passenger vehicles. Through the AI system, the two cars can assist drivers in better controlling their vehicles under extreme conditions, solving and analyzing problems up to 50 times per second, and quickly deciding on the most appropriate steering, throttle, and brake commands. During track tests, this system achieves precision through real-time communication.
Baidu has launched an AI robot job assistant that provides services such as interview guidance and salary negotiation to help job seekers improve their job search experience. It offers personalized career recommendations and negotiation strategies throughout the application process, making it easier to secure a desired offer during the autumn recruitment season. The dedicated autumn recruitment section has been launched in the Baidu app.
["MIT research found that multi-agent debates can significantly improve the accuracy and reasoning abilities of AI models.", "The debate method reduces hallucinations and helps improve the model's responsiveness.", "Multiple AI systems debating answers to problems are more accurate than a single system.", "This method can be used for collaborative work among different language models to improve output.", "These research findings provide new insights for the AI field, enhancing the authenticity and reasoning capabilities of language models."]
The robotics research team at Google DeepMind recently released a robotics project called RT-2. This project took 7 months to develop and uses a large model for training. RT-2 has capabilities such as symbol understanding, reasoning, and human recognition, and can think and complete tasks based on human instructions. By combining the large model with the robot's operational capabilities, RT-2 can accomplish tasks that involve logical leaps, such as from 'extinct animals' to 'plastic dinosaurs'. The results of this project performed well in various sub - category tests, with performance up to three times that of the previous generation of robot models. This research result demonstrates the potential of large models in robotics research and is expected to drive the development of robots in the future.