Jeff Bezos’ startup Prometheus is focused on “physical AI”: systems meant to help engineers design and build complex real-world products. The company is not alone in this area, but it stands out because of its unusually large funding and Bezos’ direct involvement. Its ambitions point beyond chatbots toward AI-assisted manufacturing, robotics, aerospace, drug design, and other engineering-heavy industries.
Jeff Bezos’ AI startup Prometheus is aiming to develop what he calls an “artificial general engineer.” The company wants to build AI-powered tools that help design physical products, with possible applications in robotics, drug design, manufacturing, and complex hardware. The Verge reports that Prometheus has raised $12 billion, reached a $41 billion valuation, employs about 150 people, and is led by Bezos and Vik Bajaj.
Prometheus, a physical AI startup associated with Jeff Bezos, has raised a new $12 billion funding round. The round values the company at $41 billion, according to TechCrunch. The startup aims to build an “artificial general engineer” for the physical world, with ambitions including heavy engineering automation and drug design.
German humanoid robotics startup Neura Robotics completed a Series C round reportedly worth up to $1.4 billion. Investors mentioned include Tether, NVIDIA, Amazon, and Qualcomm. The funding will support global deployment and expanded production capacity, underscoring continued investor interest in physical AI and humanoid robotics commercialization.
Google DeepMind has unveiled a strategic initiative to power the future of robotics in Europe. The program focuses on advancing Embodied AI and physical AI through deep collaborations with European academic institutions and industry partners. By combining DeepMind's AI expertise with Europe's strong engineering foundation, the initiative aims to accelerate breakthroughs in robotic generalization and safety.
NVIDIA and LG Group announced an AI factory collaboration spanning robotics, autonomous driving, data center technologies and GPU cloud services. The effort connects NVIDIA Isaac, Cosmos, DRIVE, DSX, Blackwell GPUs, NeMo and TensorRT-LLM with LG’s manufacturing, robotics, mobility and infrastructure businesses. The partnership also supports LG’s EXAONE sovereign AI model work and broader enterprise AI adoption across the group.
NVIDIA and LG Group are collaborating on an AI factory to support LG’s AI-driven businesses across robotics, autonomous driving, data center technologies and GPU cloud services. The effort connects NVIDIA’s AI factory platform with LG’s manufacturing, mobility, robotics and infrastructure capabilities. It also covers Isaac, Cosmos, DRIVE, DSX and EXAONE-related work using Blackwell GPUs, NeMo, Nemotron datasets and TensorRT-LLM.
NVIDIA and Doosan Group are expanding their partnership across physical AI, robotics and AI factory infrastructure. The collaboration connects NVIDIA’s accelerated computing stack, DSX, MGX and physical AI tools with Doosan’s industrial automation, power generation and electronics materials capabilities. Key areas include smarter industrial robots, autonomous equipment, AI data center power systems and advanced PCB materials for high-performance servers and networking.
Hello Robot has released Stretch 4, the fourth generation of its home assistance robot. The company is taking a cautious, deployment-first approach, using a wheeled base, telescoping arm, sensors, and human-in-the-loop control rather than promising a general-purpose humanoid. TechCrunch frames Stretch as a practical bet on real household data, assistive use cases, and safer hardware for people with mobility challenges.
Cooler Master is working with Spingence to adopt NVIDIA’s physical AI three-computer architecture across its global operations. The implementation combines AI visual inspection, digital twins, and knowledge systems to connect R&D, production, and simulation. The report frames AI as a core enterprise capability for global manufacturing collaboration, though it does not provide quantified deployment results or performance gains.
Human Archive, founded by Berkeley and Stanford researchers, is using India’s gig economy to gather physical-world AI data. Workers are paid to wear camera-equipped caps and sensor devices while moving through real environments. The company is targeting the growing demand from AI and robotics labs for real-world training data needed to develop physical AI systems.