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  1. 1
    Continuous artificial muscle enables dexterous soft-robot motionโ—A continuous artificial muscle unlocks dexterous soft-robot motionโœ‰newsTechnologyRobotics6 min ago

    Researchers have developed a continuous artificial muscle that allows soft robots to move with far greater dexterity than before. The design, reported by Tech Xplore, is described as unlocking more fluid and precise motion in soft robotics. Details of the team, the materials involved and the institutions behind the work were not provided, so the technical scope and stage of development remain unclear.

  2. 2
    Columbia spinoff Tangent Robotics raises $4.5 millionโ—Columbia spinoff Tangent Robotics raises $4.5M for robot dexterityโœ‰newsTechnologyRobotics6 min ago

    Tangent Robotics, a startup spun out of Columbia University, has raised $4.5 million to develop robotic dexterity technology. The funding will support the company's work on robots capable of fine, human-like manipulation, a key challenge in robotics. The early-stage round signals continued investor interest in academic spinoffs advancing robot manipulation for industrial and research applications.

  3. 3
    Tangent Robotics Raises $4.5M in Pre-seed Fundingโ—Tangent Robotics Raises 4.5M in Pre-seed Funding to Advance Fine Motor Skills for Robot Dexterityโœ‰newsTechnologyRobotics6 min ago

    Tangent Robotics has raised $4.5 million in pre-seed funding to advance fine motor skills for robot dexterity. The funding will support the company's work on enabling robots to perform delicate, precise movements, an area seen as a key step toward more capable and adaptable robotic systems.

  4. 4
    Startup to pay prosthetic users to train robotsโ—Exclusive / Solving for the hand: Startup wants to pay prosthetic users to teach robotsโœ‰newsBusinessStartups19 min ago

    A startup is launching a programme that will pay people who use prosthetic hands to help teach robots dexterous manipulation, according to a Semafor exclusive. The idea is that prosthetic users' firsthand understanding of hand control and grip could improve how robots learn fine motor tasks. It highlights a growing push in robotics to source human expertise for training data.