TDK to present on machine learning at tinyML Summit

TDK Corporation (TSE 6762) announced today that it will give two presentations and participate in a panel at the 2023 tinyML Summit being held March 27-29 at the Hyatt Regency in Burlingame, California. The Summit is a gathering of key tinyML members from all aspects of the ecosystem encompassing the expanding breadth of industries within the tinyML technology and application space.

Al Heshmati, VP of Systems and Software, TDK U.S.A Corporation, will be speaking at 9:45 am PT on Tuesday, March 28th on the trajectory from custom intelligent sensors to broad market adoption of smart platforms. Mr. Heshmati will be exploring the widespread adoption of smart sensor platforms that require seamless availability and optimized interworking of end-to-end elements from tool-chains to readily-available ML-enabled hardware platforms. Mr. Heshmati will also participate in a panel later that afternoon at 4:00 pm PT titled “tinyML Application Throwdown: What application area has the most potential?”

Stephanie Pavlick, Machine Learning Engineer, Qeexo, a TDK group company, will be presenting a case study at 4:45 pm PT on Wednesday, March 29th on how a consumer goods company leverages Qeexo’s AutoML to accelerate data science adoption and value. Qeexo has developed novel assisted segmentation technology focused on event-type time-series sensor data. Qeexo has collaborated closely with leaders at the consumer goods company to leverage Qeexo’s AutoML as a tool to lower activation energy, helping enable this broad innovator community to develop, manage and deploy new algorithms. Some of these include: an assisted segmentation feature to aid customers in quickly and efficiently labeling large amounts of data, model size reduction, data augmentation to represent possible variations of a collected dataset, and more.

For further information on the Qeexo ML platform, please visit www.qeexo.tdk.com or contact Qeexo Sales at https://qeexo.tdk.com/contact-us/.

Glossary

• AutoML: Automated machine learning is the process of automating the tasks of applying machine learning to real-world problems
• tinyML: Tiny machine learning is broadly defined as a fast-growing field of machine learning technologies that can perform on-device sensor data analytics at extremely low power
• ML: Machine learning is a field of inquiry devoted to understanding and building methods that “learn,” that is, methods that leverage data to improve performance on a set of tasks

About TDK Corporation

TDK Corporation is a world leader in electronic solutions for the smart society based in Tokyo, Japan. Built on a foundation of material sciences mastery, TDK welcomes societal transformation by resolutely remaining at the forefront of technological evolution and deliberately “Attracting Tomorrow.” It was established in 1935 to commercialize ferrite, a key material in electronic and magnetic products. TDK‘s comprehensive, innovation-driven portfolio features passive components such as ceramic, aluminum electrolytic and film capacitors, as well as magnetics, high-frequency, and piezo and protection devices. The product spectrum also includes sensors and sensor systems such as temperature and pressure, magnetic, and MEMS sensors. In addition, TDK provides power supplies and energy devices, magnetic heads and more. These products are marketed under the product brands TDK, EPCOS, InvenSense, Micronas, Tronics and TDK-Lambda. TDK focuses on demanding markets in automotive, industrial and consumer electronics, and information and communication technology. The company has a network of design and manufacturing locations and sales offices in Asia, Europe, and in North and South America In fiscal 2022, TDK posted total sales of USD 15.6 billion and employed about 117,000 people worldwide.

About Qeexo

Qeexo, a TDK Group Company, is the first company to automate end-to-end machine learning for embedded edge devices (Cortex M0-M4 class). Its one-click, fully automated Qeexo AutoML platform allows customers to leverage sensor data to rapidly build machine learning solutions for highly constrained environments with applications in industrial, IoT, wearables, automotive, mobile, and more. Over 300 million devices worldwide are equipped with AI built on Qeexo AutoML. Delivering high performance, solutions built with Qeexo AutoML are optimized to have ultra-low latency, ultra-low power consumption, and an incredibly small memory footprint.https://qeexo.tdk.com

Downloads

• Press release (pdf: 173 KB)

• Further information on the products can be found under
  https://qeexo.tdk.com

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