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RoboticsAI Business & IndustryThe Robot ReportPublished: Sep 3, 2026, 06:00 JST

Physical AI startups get acquired by Big Tech, says NexCOBOT

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Physical AI startups get acquired by Big Tech, says NexCOBOT

3 Key Points

  1. What happened

    Jenny Shern, general manager of NexCOBOT, said acquisitions of robotics startups by Big Tech will continue. Recent examples include Mobileye buying Mentee Robotics for $900 million in January, Amazon acquiring Fauna Robotics in March, and Meta picking up Assured Robot Intelligence in May.

  2. Why it matters

    Smaller robotics firms bring expertise in areas like robot learning and perception, while large companies offer computing infrastructure and capital. Shern noted that a more selective funding environment may pressure early-stage startups to validate their business models sooner, potentially slowing new entrants but encouraging focused innovation.

  3. What to watch

    NexCOBOT says it is focusing on scaling its open, functional safety robotic controllers and fulfilling its backlog of global orders as it heads into mass production. The company also highlighted a client case where its certified functional safety controller shortened a development cycle from an estimated three to five years to just two years.

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Context & Analysis

The article captures a moment where physical AI—robots that incorporate AI into perception, decision-making, and interaction—is moving from research into commercial reality. Shern highlights that large tech companies are buying startups for faster innovation, citing Mobileye's $900 million acquisition of Mentee Robotics in January, Amazon's purchase of Fauna Robotics in March, and Meta's acquisition of Assured Robot Intelligence in May. This trend, she argues, stems from startups' deep expertise in robot learning and perception pairing with Big Tech's infrastructure and capital.

Shern describes a funding landscape that is becoming more selective. While capital remains available for companies with clear technical differentiation and a path to commercialization, early-stage startups may need to validate their business models sooner. This could slow the number of new entrants but potentially encourage more focused innovation.

For industrial adoption, reliability and safety remain critical. NexCOBOT's example of a client shortening its development cycle from an estimated three to five years to two years using an open functional safety controller illustrates how modular platforms can help bridge the speed gap between software and hardware. Shern expects adoption to advance in stages as AI-native robots prove themselves in real-world environments.

FAQ
What are AI-native robots?
AI-native robots are robots originally structured to incorporate AI as a core part of how they perceive, make decisions, and interact with their environment. Unlike traditional robots that follow predefined instructions, they adapt to changing conditions and learn from new inputs.
How can Big Tech combine software and hardware strengths?
By separating software innovation from hardware development wherever possible, Big Tech can update AI models continuously while hardware requires longer cycles. Using modular platforms and standardized interfaces allows new AI capabilities to deploy onto existing robots without waiting for new hardware.
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