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OpenAI recently announced the launch of its robot project to further explore the development of robotics technology. On January 11, Caitlin Kalinowski, the director of OpenAI's hardware department, revealed on social media that OpenAI would begin developing robots equipped with custom sensors and published related job openings on its official website. This recruitment covers three key positions: Electronic Perception Engineer, Robotics Mechanical Design Engineer, and Technical Project Manager. The primary responsibility of the Electronic Perception Engineer is to design and develop...

On Thanksgiving, Tesla's Optimus robot has once again redefined our imagination of robotic technology. In the latest demonstration video, this humanoid robot showcased its astonishing hand operation ability by effortlessly catching thrown tennis balls. This is not just a simple catching performance. Optimus's new hands and forearms integrate several revolutionary technologies. Its hands have 22 degrees of freedom, while the wrists and forearms add an additional 3 degrees of freedom, bringing its dexterity close to the human hand's 27 degrees of freedom. This means the robot is performing with astonishing capability.

Innovative design approach: using machine learning algorithms to optimize the parameter design of tactile sensors, achieving an organic combination of design and algorithms. Technical highlights: support vector machine algorithms optimize design parameters for accurate recognition of various touch patterns. Application prospects: shorten the R&D cycle, reduce costs, and expand human-computer interaction applications.

Researchers at Penn State University have recently developed graphene-based electronic sensors that can simulate human taste. This innovation holds potential for applications in smart dietary recommendations and personalized dining experiences. The research team plans to integrate the electronic 'tongue' and electronic 'taste cortex' onto a single chip to further streamline the system. This research brings new ideas to artificial emotional intelligence and enhances the intelligence level of AI systems.

Toyota Research Institute uses generative artificial intelligence to train robots to make breakfast without coding. The robots learn over 60 challenging skills through tactile perception, such as pouring liquids, using tools, and manipulating deformable objects. The goal is to expand to 1,000 new skills by the end of 2024, enabling robots to observe, learn, and perform tasks they have not been explicitly taught. Tactile sensors provide the robots with perception capabilities, increasing efficiency in performing complex tasks. Toyota is collaborating with other companies to research AI robot training, aiming for a future where tasks can be executed without detailed instructions.

US startup Dryad Networks has developed a solar-powered AI gas sensor that can detect wildfires in advance. The sensor utilizes machine learning technology to reduce false alarm rates. It has been deployed in some regions of Europe and North America, and is expected to help firefighters with early warnings and reduce fire-related losses.