Renesas køber AI-eksperten Reality AI
Renesas’ processorer kan i kombination med Reality AI’s værktøjer og løsninger åbne mulighed for enkel integration af AI i IIoT, konsumer og automotive applikationer (n english).Renesas Electronics has entered into a definitive agreement with Reality Analytics, Inc. (Reality AI), a leading provider of embedded AI solutions, under which Renesas will acquire Reality AI in an all-cash transaction.
The transaction has been unanimously approved by the boards of directors of both companies and is expected to close by the end of calendar year 2022, subject to shareholders’ and required regulatory approval and other customary closing conditions. The acquisition will significantly enhance Renesas’ endpoint AI capability, providing more flexibility and efficiency for system developers to make their products AIoT (Artificial Intelligence of Things) ready and get to market faster.
The importance of embedding AI into products has soared lately in the connected world as workload requirements at the endpoint have evolved. For IIoT (Industrial IoT), consumer, automotive and other embedded applications that demand machine learning based intelligent decision-making physically closer to the source of the data, low latency and high security are a must.
In collaboration with its partners, Renesas has been offering development environments and software that allow AI to be embedded in its low-power, highly secure MCUs (microcontrollers) and MPUs (microprocessors). The Reality AI acquisition allows Renesas to expand its in-house capability to provide comprehensive and highly optimized endpoint solutions both from the hardware as well as the software perspective. This enables system developers to realize endpoint intelligence across a wide range of IIoT, consumer and automotive applications.
Headquartered in Columbia, Maryland, U.S., Reality AI offers a wide range of embedded AI and Tiny Machine Learning (TinyML) solutions for advanced non-visual sensing in automotive, industrial and commercial products.
They provide machine learning with advanced signal processing math, delivering fast, efficient machine learning inference that fits on the smallest MCUs. Reality AI’s flagship Reality AI Tools®, a software environment built to support the full product development lifecycle, provides analytics from non-visual sensor data. Their inference-based AI solutions can be implemented across various endpoint AI applications. Good examples of the company’s versatile expertise are industrial anomaly detection and automotive sound recognition using AI-built sensors.
Combining these technologies with Renesas’ broad range of MCU and MPU portfolios designed to provide the best-in-class AI inference and signal processing capabilities will help developers seamlessly apply advanced machine learning and signal processing to complex problems.
In addition to expanding embedded AI technologies, key IPs, software and tools, the acquisition will bring an AIoT center-of-excellence in Maryland by acquiring Reality AI’s experts. This move will extend Renesas’ global software development talent base and spearhead its commitment to address the needs of customers eager to utilize AI.
- The importance and demand of data at the endpoint is increasing at an unprecedented scale. The acquisition of AI technology is an important milestone to address our customers’ emerging requirements for endpoint intelligence, says Hidetoshi Shibata, President and CEO of Renesas.
- The addition of Reality AI’s AI solutions to our existing embedded AI portfolios will further solidify our position as a leading AIoT solution provider.
- Customers are increasingly demanding highly customized solutions involving embedded machine learning, signal processing, high-capability processors, and assistance with hardware integration and solution development, adds Stuart Feffer, CEO of Reality AI.
- Having collaborated with Renesas for some time now, we are looking forward to being able to provide customers with more complete solutions - especially in the areas of IIoT, consumer and automotive products where use of machine learning is growing rapidly.