Google DeepMind’s recent appointment of Aaron Saunders as vice president of hardware engineering highlights a bold new phase in its robotics efforts.
Known for leading Boston Dynamics’ most groundbreaking projects, Saunders brings deep expertise to DeepMind’s quest to turn its Gemini AI model into a universal platform for robotics.
Announced this week, the move positions DeepMind to rival some of the biggest players in AI-driven robotics.
With Saunders' background and the resources of Google DeepMind Finance: Alphabet Inc., the company aims to do for physical robots what Android did for smartphones: provide a flexible, widely adopted intelligence layer for manufacturers worldwide.
Why did DeepMind hire Aaron Saunders from Boston Dynamics?
Aaron Saunders’ reputation in robotics is built on over two decades at Boston Dynamics, where he played a pivotal role in developing robots like Atlas and Spot.
Most recently, he served as chief technology officer, steering the company through major technological leaps.
DeepMind’s interest in merging sophisticated AI with real-world robotics required someone versed in both large-scale hardware operations and bleeding-edge robotic design.
On joining DeepMind in November 2025, Saunders was tasked with building dedicated teams focused on integrating the Gemini AI system into a broad range of robot bodies.
DeepMind’s CEO, Demis Hassabis, stated that hiring Saunders was essential for “making the Android of robots a reality” and closing the gap between advanced AI models and practical robotics deployments.
Did you know?
Boston Dynamics’ Atlas robot executed its first backflip in 2017, a feat that stunned both robotics engineers and the public worldwide.
How will Gemini AI change the robotics landscape?
Gemini AI builds on DeepMind’s years of research in large language and multimodal models, now extended to embodied intelligence.
Demonstrations in 2025 showed Gemini Robotics-ER 1.5 executing complex commands, multi-step planning, and even accessing the internet for instruction, all in real-world robots.
An offline-capable version provided robust performance across typical home chores without needing a live internet connection.
By pushing Gemini as a common control system, DeepMind aims to simplify robotics for manufacturers, researchers, and end users.
Instead of building custom brains for each robot, Gemini seeks to become the “universal translator,” enabling any compatible machine to leverage the same intelligence and skills library for physical tasks.
What makes the universal robotics platform vision different?
Rather than manufacturing robots itself, DeepMind is pursuing a software-first strategy mirroring Google’s approach to Android in mobile phones.
The goal, according to Hassabis, is to let third-party manufacturers deploy robots powered by Gemini, whether for warehouses, hospitals, homes, or autonomous vehicles.
This approach promises faster industry growth by eliminating the need for each company to develop its own advanced AI stack.
Saunders’ arrival is meant to bridge longstanding gaps between AI software development and the practicalities of robotics hardware integration.
The outcome could be a new ecosystem, where Gemini compatibility becomes as essential as USB standards or operating systems in modern devices.
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Who else is competing for dominance in AI-driven robotics?
The competition in robotics AI has intensified dramatically through 2025. Tesla finance: Tesla, Inc. revealed plans to manufacture a million Optimus humanoids this decade, aiming for consumer price points under $30,000.
NVIDIA Corporation is marketing the Isaac GR00T and Newton engines as foundational robotics AI infrastructure, some of which are being co-developed with DeepMind.
Meanwhile, Boston Dynamics continues to invest heavily in advanced machine behavior, demonstrating Atlas and Spot robots capable of learning from human demonstrations.
These efforts, in partnership with industry players like Toyota Research Institute Finance and Toyota Motor Corporation, point to an arms race not just in hardware but also in the AI approaches powering each robot.
What comes next for DeepMind’s robotics ambitions?
With a major industry figure like Aaron Saunders now at the helm of hardware engineering, DeepMind is preparing for scaled beta deployments and deeper partnerships with robot makers worldwide.
The company is expected to unveil further demonstrations of Gemini-powered machines performing diverse and complex real-world tasks in 2026 and beyond.
Hassabis is bullish on the prospects of “breakthrough moments” within a few years, emphasizing that the real challenge is robustly linking sophisticated AI models to the messy realities of physical environments.
As labor shortages and automation needs grow globally, DeepMind’s approach of separating the “brain” from the “body” could usher in a new era where robots become as ubiquitous as smartphones.
Advances in universal robot control platforms could determine who leads the next technological revolution, with DeepMind staking its claim at the intersection of intelligence, hardware, and global manufacturing.
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