MIPS is launching its Atlas chip designs for physical AI platforms such as industrial robots and autonomous cars.
The aim is to drive real-time intelligence into physical AI, said Sameer Wasson, CEO of MIPS, in an interview with GamesBeat.
The new MIPS Atlas product suite delivers compute subsystems that empower autonomous edge solutions to sense, think and act with precision, driving innovation across the growing physical AI opportunity in industrial robotics and autonomous platform markets.
San Jose, California-based MIPS is targeting its MIPS Atlas portfolio at automotive, industrial and embedded technology companies so they can deploy safe, secure and efficient physical AI at the edge. By combining high performance real-time computing with functional safety and edge deployment of post generative AI models, the Atlas product suite enables the development of next generation autonomous platforms to address the estimated $1 trillion physical AI market opportunity.
Imagination sold MIPS to Tallwood Venture Capital in 2017. Then Wave Computing purchased MIPS in 2018. But Wave Computing declared bankruptcy in 2020, and MIPS announced that it would abandon the MIPS architecture in favor of RISC-V designs. MIPS started launching its RISC-V chip designs in 2022.
At CES 2025, Nvidia CEO Jensen Huang said that the age of physical AI — with self-driving cars and robots — would be accelerated because of synthetic data. That’s the use of simulations to test data for things like self-driving cars in digital twins before they’re deployed in the real world. That synthetic data complements the physical world data, accelerating the time it takes to fully test a product.
He noted MIPS is not competing with Nvidia on building AI brains. Rather, MIPS is building control systems with AI built into it for real-time controllers. He said to expect products in this space in 2026.
“The need for efficient autonomous platforms to advance next-generation driverless vehicles, factory automation, and many other applications is directly aligned with the MIPS Atlas portfolio,” said Wasson. “Our core competencies of safety, efficient data processing and experience in autonomy have enabled us to expand our portfolio with real-time intelligence that is the essential tech stack for Physical AI platforms. MIPS customers can take our compute subsystems with software stacks as a turnkey solution to build physical AI platforms.”
James Prior, marketing executive at MIPS said in an interview with GamesBeat that MIPS is providing a portfolio of solutions for its approach to physical AI, which involves real-time processing, data movement, custom compute and functional safety to enable the world’sindustrial robotics and automation providers with what they need to build physical AI platforms.
“The reason for that is we analyzed the physical AI problem as three different computing issues. There’s the sense, think and act,” he said.
Sensing helps robots see the world around them an make decisions with AI models. It computes solutions to problems based on models that are trained in simulation, and then it turned that decision into action for robots to take.
The MIPS Atlas portfolio is built to provide turn-key enablement for the three categories of computing that make up physical AI – Sense, Think, and Act. Physical AI platforms interpret their surroundings using a diverse array of sensors, generating data that must be seamlessly transferred, integrated, and processed in real time.
This data is processed by the platform’s embedded AI engine to enable fast, private decision making for safe and precise actions. Action, needed for the dexterous control of motors and actuators, is enabled via real-time compute platforms capable of incredibly low latency control-loop processing in robotic movements.
“The MIPS Atlas portfolio aligns tightly with the compute requirements for physical AI and robotics, “ said Jim McGregor, principal analyst at Tirias Research, in a statement. “Working with its customers, MIPS provides a unique multi-threaded architecture with optimized instructions to deliver event-driven low-latency performance along with system-level workload analysis via the Atlas Explorer. MIPS is in a unique position to fill the need for emerging physical AI platforms.”
The new MIPS Atlas portfolio of M8500, I8600, and S8200 solutions deliver these capabilities as application specific turnkey enablers. Enabled by the MIPS Atlas Explorer software platform, customers can employ shift-left methodology to develop and deploy their applications with MIPS Atlas subsystems in a digital twin universe for faster time to market. Select customers will be able to evaluate the MIPS M8500 real-time compute subsystem with Atlas Explorer in mid-2025, with evaluation boards in 4Q25, and reference silicon platforms available in 1H26. A MIPS customer automotive platform featuring M8500 is expected to start production in 2027.
“The MIPS Atlas portfolio represents a significant leap forward in enabling Physical AI at the edge, delivering the real-time compute power needed for autonomous platforms to thrive in industrial and automotive applications,” said Steven Dickens, CEO at HyperFRAME Research, in a statement. “By integrating safety, efficiency and cutting-edge intelligence, MIPS is well-positioned to accelerate innovation across the rapidly expanding $1 trillion Physical AI market.”
A 40-year-old company, MIPS is using the RISC-V architecture to drive intelligence into action for automotive and industrial companies with the MIPS Atlas portfolio of Sense, Think and Act by pushing the boundaries of autonomous platforms. MIPS is an exhibitor at Embedded World 2025 from March 11th – 13th, in Nuremburg, Germany.
MIPS also announced a variety of other chip design products, including the MIPS S8200 physical AI subsystem for physical AI at the edge. It also announced the MIPS I8600 compute subsystem for sensor data movement, the M8500 real-time compute subsystems and more.
A new identity for MIPS
“This announcement should help build the identity of what we’re trying to do MIPS,” Wasson said. “While our technology is applicable to multiple markets, the market which we are solely focusing on with all our energy is the automotive embedded side, the physical AI side,” Wasson said.
Wasson said that if you’ve ever seen an autonomous lawnmower, you’ll know it kind of sucks at doing a good job cutting your lawn. That’s because the physical AI problem hasn’t been solved correctly yet. He said a lawn is not straight and grass can’t be cut with something like a robot vacuum. The grass changes in subtle ways, and it takes real physical AI to solve such problems.
“I’m not becoming a lawnmower company, but it’s an example of where we’re trying to build a system. So when you think of robotics, the same lawnmower problem exists across the board on multiple robotic assessments. And what we’re trying to do is bring AI in the closed loop of a control. And if you can do that successfully with the processing capabilities that we have.”
He noted that MIPS is creating all of the building blocks of subsystems that are needed in autonomous cars and physical robots.
“MIPS has been very IP focused in the past,” he said. “We are now starting to expand into beyond IP. We have building blocks for this, but we are also coming out with reference silicon, with the board, with the ecosystem. We are proving out the ecosystem of the software side so that people are ready to go and can start replicating it very easily.”
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