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    UK and Ukraine Sign Strategic AI Deal to Develop Battlefield Technology

    By Art RyanAugust 25, 20260

    The United Kingdom and Ukraine are taking their technology partnership deeper into artificial intelligence. On…

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    Home » Tether Backs $81 Million Humanoid Robotics Project in Italy
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    Tether Backs $81 Million Humanoid Robotics Project in Italy

    Art RyanBy Art RyanDecember 9, 2025No Comments2 Mins Read
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    Italian robotics firm Generative Bionics has raised $81 million in new funding.

    The new funding round was one of the largest ever in Europe in the “humanoid robotics deep tech space,” Generative Bionics said in a Monday (Dec. 8) announcement.

    “Our mission is to build a future where intelligent humanoid robots collaborate daily with people, amplifying human cognitive and physical potential,” said Daniele Pucci, the company’s co-founder and CEO. “Our Physical AI enables us to design and manufacture human-inspired robots that create tangible value across multiple applications.”

    He pointed to analyses projecting that the humanoid robotics market will exceed 200 billion euros ($232 billion) by 2035 and could top $5 trillion by 2050.

    “This is an epochal transformation: our goal is to position Generative Bionics as a global leader in physical AI for human-centric humanoid ecosystems,” Pucci said.

    The round was led by CDP Venture Capital, with participation by investors that include Tether. The company says it will use the funding to boost product development, train physical artificial intelligence (AI) systems — what it calls the fusion of robotics and AI — and to construct its first production plant.

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    “The company is also finalizing its first industrial deployment contracts, which will be announced in early 2026, marking the introduction of humanoids into real production environments,” the announcement said.

    As PYMNTS wrote last month, physical AI has emerged as the next phase of robotics as new developments in sensing, perception and large AI models provide machines with capabilities that had never been supported by traditional automation.

    “Earlier robots followed fixed commands and worked only in predictable environments, struggling with the unpredictability found in everyday operations such as shifting layouts, varying item shapes, mixed lighting, and human movement,” that report said.

    “That is beginning to change as research groups show how simulation, digital twins and multimodal learning pipelines enable robots to learn adaptive behaviors and carry those behaviors into real facilities with minimal retraining.”

    An example of this technology in the day-to-day world is Amazon’s launch of its Vulcan robot earlier this year.

    Vulcan employs both vision and touch to pick and stow items in fulfillment centers, letting it handle flexible fabric storage pods and unpredictable product shapes. Amazon says the robot’s tactile systems allow it to respond to pressure, contact and motion in real time to carry out tasks that typically call for human dexterity.

    Source: https://www.pymnts.com/
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