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A Tesla driver using the new Full Self-Driving (FSD) Beta v12 software managed to showcase a new behavior: FSD Beta autonomously looking for a parking spot.

The Tesla v12 software update is expected to introduce what CEO Elon Musk has been calling “end-to-end neural nets”. The biggest difference with previous FSD updates is that the vehicle’s controls would now be handled by neural nets rather than being coded by programmers.

It is being touted as the difference maker.

Figure AI eyes a $1.9 billion valuation as Microsoft and OpenAI show interest in its life-saving robots

Figure AI, a startup developing human-like robots, is in talks to secure up to $500 million in a funding round potentially led by Microsoft and OpenAI.

The company is looking to attract additional investors, with Microsoft potentially investing $95 million and OpenAI contributing $5 million. The deal could value Figure AI at $1.9 billion before pre-financing.

We developed Significant Latent Factor Interaction Discovery and Exploration (SLIDE), an interpretable machine learning approach that can infer hidden states (latent factors) underlying biological outcomes. These states capture the complex interplay between factors derived from multiscale, multiomic datasets across biological contexts and scales of resolution.

Summary: Researchers unveiled a pioneering technology capable of real-time human emotion recognition, promising transformative applications in wearable devices and digital services.

The system, known as the personalized skin-integrated facial interface (PSiFI), combines verbal and non-verbal cues through a self-powered, stretchable sensor, efficiently processing data for wireless communication.

This breakthrough, supported by machine learning, accurately identifies emotions even under mask-wearing conditions and has been applied in a VR “digital concierge” scenario, showcasing its potential to personalize user experiences in smart environments. The development is a significant stride towards enhancing human-machine interactions by integrating complex emotional data.

Soft robots inspired by animals can help to tackle real-world problems in efficient and innovative ways. Roboticists have been working to continuously broaden and improve these robots’ capabilities, as this could open new avenues for the automation of tasks in various settings.

Researchers at Nagoya University and Tokyo Institute of Technology recently introduced a soft robot inspired by inchworms that can carry loads of more than 100 g at a speed of approximately 9 mm per second. This robot, introduced in Biomimetic Intelligence and Robotics, could be used to transport objects and place them in precise locations.

“Previous research in the field provided foundational insights but also highlighted limitations, such as the slow transportation speeds and low load capacities of inchworm-inspired robots,” Yanhong Peng told Tech Xplore. “For example, existing models demonstrated capabilities for transporting objects at speeds significantly lower than the 8.54 mm/s achieved in this study, with limited ability to handle loads above 40 grams.”