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TDK to acquire Qeexo to enable complete smart edge platforms

Qeexo 04 January 2023
  • TDK to acquire Qeexo, Co, a leading developer of automated machine-learning (ML) platform that accelerates the development of tinyML models for low power, always-on intelligent platforms
  • TDK aims to further strengthen its ML expertise and simplify ML application development to become a leader in delivering smart edge solutions
  • Acquisition enables TDK to accelerate the transition to Industry 4.0 with smart edge solutions

SAN JOSE, Calif., Jan. 4, 2023 /PRNewswire/ — TDK Corporation (TSE: 6762) (CEO & President: Noboru Saito, hereinafter “TDK”) announced that today TDK has agreed to acquire Qeexo, Co. (CEO: Sang Won Lee, hereinafter “Qeexo”), a U.S.-based venture-backed company spun out of Carnegie Mellon University engaged in the automation of end-to-end machine learning for edge devices. As a result of the acquisition, Qeexo will become a wholly owned subsidiary of TDK, subject to customary closing conditions, including approval of the Committee on Foreign Investment in the US (CFIUS).

Qeexo, based in Mountain View, California, USA, is the first company to automate end-to-end machine learning for edge devices. Qeexo AutoML enables a no-code environment, enabling data collection and training of 18 (and expanding) different machine learning algorithms, including both neural networks and non-neural-networks, to the same dataset, while generating metrics for each (accuracy, memory size, latency), so that users can pick the model that best fits their unique requirements. A cloud-based easy to use solution, it provides an intuitive UI platform system that allows users to collect, annotate, cleanse, and visualize sensor data and automatically build “tinyML” models using different algorithms. Qeexo’s AutoML platform allows customers to leverage sensor data to rapidly build machine learning solutions optimized to have ultra-low latency and power consumption, with an incredibly small memory footprint for highly constrained environments with applications in industrial, IoT, wearables, automotive, mobile, and more.  Through streamlined intuitive process automation, Qeexo’s AutoML enables customers without precious ML resources and greatly accelerates design of Edge AI capabilities for their own specific applications.

“Qeexo brings together a unique combination of expertise in automating machine learning application development and deployment for those without ML expertise, high volume shipment of ML applications and understanding of sensors to accelerate the deployment of smart edge solutions,” stated Jim Tran, CEO, TDK USA Corporation. “Their expertise combined with TDK’s leadership positions in sensors, batteries and other critical components will enable the creation of system level solutions addressing a broad range of applications and industries.”

“Our platform is an outgrowth of our own history of high-volume ML application development and deployment enabling those with domain expertise but not ML expertise to solve real world problems quickly and efficiently,” continued Sang Lee, CEO, Qeexo. “We see our AutoML tool as a natural partner to the smarter sensor systems that TDK is building.”

The following is an outline of the company profile:

  1. Company name: Qeexo, Co.
  2. Location: Headquartered in Mountain View, CA, office in Pittsburgh, PA, USA
  3. Established: September 2012
  4. Management: CEO – Sang Won Lee; CTO – Chris Harrison
  5. Main business operations: Development of automated machine-learning (ML) platform that accelerates the development of tinyML models for the Edge.
  6. Learn more about fundamental machine learning concepts: ­Qeexo AutoML Best Practice Guide – Qeexo, Co.

TDK will be showcasing over 30 different technologies, solutions, and platforms at CES 2023, January 5-8, 2023, at the Las Vegas Convention Center (LVCC) and can be found at Central Hall – #16181. Qeexo will demonstrate their machine learning platform solution within the TDK booth and also showcase their full range of technology solutions at the Qeexo booth #11222, North Hall. 

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 is capable of performing 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 some set of tasks
  • Smart Edge solutions: Smart Edge solutions refers to the analysis of data and development of solutions at the site where the data is generated.
  • Smart Edge device:  An intelligent edge device is a sophisticated IoT device that performs some degree of data processing within the device itself.

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 is the first company to automate end-to-end machine learning for embedded edge devices (Cortex M0-M4 class). Our 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.

Images related to this release can be downloaded from the following URL: https://www.tdk.com/en/news_center/press/20230104_01.html

Contacts for regional media

RegionContactPhoneMail
GlobalMr. David A.ALMOSLINOTDK USA Corporation
San Jose, CA
+1 408-501-2278[email protected]  
North AmericaMs. Sarah
MACKENZIE
Publitek
Portland, OR
+1 503-720-3743TDK-[email protected]
JapanMr. Yoichi
OSUGA
TDK Corporation
Tokyo, Japan
+813 6778-1055[email protected]
WorldwideMr. Sang
Won Lee
Qeexo
Mountain View, CA
+1 510 508 0446[email protected] 

SOURCE TDK Corporation

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Using AutoML to detect motor issues

Jinwook Shin @ Hackster.io 05 July 2022

Use Qeexo’s AutoML to monitor the motor’s status on a Fischertechnik robot.

Read the full post at Hackster.io: https://www.hackster.io/jinuk1024/using-automl-to-detect-motor-issues-3818e1

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Qeexo, and Bosch Enable Developers to Quickly Build and Deploy Machine-Learning Algorithms to Bosch AI-Enabled Sensors

Qeexo / Bosch Sensortec GmbH 26 May 2022

Machine learning algorithms created using Qeexo’s AutoML can now be deployed on Arduino Nicla Sense ME with Bosch BHI260AP and BME688 sensors

May 25, 2022

Qeexo, developer of the Qeexo AutoML, and Bosch Sensortec GmbH, a technology leader in MEMS sensing solutions, today announced that machine learning algorithms created using Qeexo’s AutoML can now be deployed on Arduino Nicla Sense ME with Bosch BHI260AP and BME688 sensors. Qeexo AutoML is an automated machine-learning (ML) platform that accelerates the development of tinyML models for the Edge.

Bosch’s BHI260AP self-learning AI sensor with integrated IMU, and BME688, a 4-in-1 gas sensor with AI, significantly reduce overall system power consumption while supporting a wide range of applications for different segments of the IoT market.

Using Qeexo AutoML, machine learning (ML) models–that would otherwise run on the host processor–can be deployed in and executed by BHI260AP and BME688. Its highly efficient machine learning models–that overcome traditional die-size-imposed limits to computational power and memory size–extend to applications that transform and improve lives. For example, they can be used for: Monitoring environmental parameters, including humidity and Air Quality Index (AQI); and capturing information embedded in motion, such as person-down systems to fitness apps that check posture. These devices typically have a longer time between charges and provide actionable information.

“Qeexo’s collaboration with Bosch enables application developers to quickly build and deploy machine learning algorithms on Bosch’s AI integrated sensors,” said Sang Won Lee, CEO of Qeexo. “Machine learning solutions running on Bosch’s AI integrated sensors are light-weight and do not consume MCU cycles or additional system resources as seen with traditional embedded ML.”

“Bosch Sensortec and Qeexo are collaborating on machine learning solutions for smart sensors and sensor nodes. We are excited to see more applications made possible by combining the smart sensors BHI260AP and BME688 from Bosch Sensortec and AutoML from Qeexo.” said Dr. Stefan Finkbeiner, CEO at Bosch Sensortec.

About Qeexo

Qeexo is the first company to automate end-to-end machine learning for embedded edge devices (Cortex M0-M4 class). Our 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.

About Bosch Sensortec GmbH

Bosch Sensortec GmbH is a fully owned subsidiary of Robert Bosch GmbH dedicated to the world of consumer electronics; offering a complete portfolio of micro-electro-mechanical systems (MEMS) based sensors and solutions that enable mobile devices to feel and sense the world around them. Bosch Sensortec develops and markets a broad portfolio of MEMS sensors, solutions and systems for applications in smart phones, tablets, wearable devices, and various products within the IoT (Internet of Things).

https://www.eejournal.com/industry_news/qeexo-and-bosch-enable-developers-to-quickly-build-and-deploy-machine-learning-algorithms-to-bosch-ai-enabled-sensors/

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Arm’s Startup Day Shows its Support for Future Hardware Startups

All About Circuits 18 August 2021

Finding new tech often means looking at startups. To support this critical aspect of the tech industry, Arm launches its “Startup Day” event. What is it, and what were some key takeaways?

Read the full article here: https://www.allaboutcircuits.com/news/arms-startup-day-shows-its-support-for-future-hardware-startups/

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IoT News of the Week for July 9, 2021

Stacey on IOT 12 July 2021

Anyone can now build smarter sensors using Qeexo and STMicroelectronics sensors: This is a cool example of ML at the edge. Chip vendor ST Microelectronics is working with Qeexo, a startup that builds software to easily train and generate machine learning algorithms, to ensure that its sensors will easily work with Qeexo software.

Read the full article here: https://staceyoniot.com/iot-news-of-the-week-for-july-9-2021/

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Qeexo adds AutoML to STMicro MLC sensors to speed tinyML, IIoT development

Fierce Electronics 08 July 2021

Machine learning developer Qeexo and semiconductor STMicroelectronics have teamed up to allow STMicro’s machine learning core sensors to leverage Qeexo’s AutoML automated machine learning platform that accelerates the development of tinyML models for edge devices.

Read the full article here: https://www.fierceelectronics.com/iot-wireless/qeexo-adds-automl-to-stmicro-mlc-sensors-to-speed-tinyml-iiot

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Machine-learning capable motion sensors intended for IoT

New Electronics

Qeexo, developer of the Qeexo AutoML automated machine-learning (ML) platform, and STMicroelectronics have announced the availability of ST’s machine-learning core (MLC) sensors on Qeexo AutoML.

Read the full article here: https://www.newelectronics.co.uk/electronics-news/iot-machine-learning-capable-motion-sensors/238717/

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Qeexo and STMicroelectronics Speed Development of Next-Gen IoT Applications with Machine-Learning Capable Motion Sensors

Qeexo / STMicroelectronics 07 July 2021

Qeexo and STMicroelectronics Speed Development of Next-Gen IoT Applications with Machine-Learning Capable Motion Sensors


Mountain View, CA and Geneva, Switzerland, July 7, 2021

Qeexo, developer of the Qeexo AutoML automated machine-learning (ML) platform that accelerates the development of tinyML models for the Edge, and STMicroelectronics (NYSE: STM), a global semiconductor leader serving customers across the spectrum of electronics applications, today announced the availability of ST’s machine-learning core (MLC) sensors on Qeexo AutoML.

By themselves, ST’s MLC sensors substantially reduce overall system power consumption by running sensing-related algorithms, built from large sets of sensed data, that would otherwise run on the host processor. Using this sensor data, Qeexo AutoML can automatically generate highly optimized machine-learning solutions for Edge devices, with ultra-low latency, ultra-low power consumption, and an incredibly small memory footprint. These algorithmic solutions overcome die-size-imposed limits to computation power and memory size, with efficient machine-learning models for the sensors that extend system battery life.

“Delivering on the promise we made recently when we announced our collaboration with ST, Qeexo has added support for ST’s family of machine-learning core sensors on Qeexo AutoML,” said Sang Won Lee, CEO of Qeexo. “Our work with ST has now enabled application developers to quickly build and deploy machine-learning algorithms on ST’s MLC sensors without consuming MCU cycles and system resources, for an unlimited range of applications, including industrial and IoT use cases.” 

Adapting Qeexo AutoML for ST’s machine-learning core sensors makes it easier for developers to quickly add embedded machine learning to their very-low-power applications,” said Simone Ferri, MEMS Sensors Division Director, STMicroelectronics. “Putting MLC in our sensors, including the LSM6DSOX or ISM330DHCX, significantly reduces system data transfer volumes, offloads network processing, and potentially cuts system power consumption by orders of magnitude while delivering enhanced event detection, wake-up logic, and real-time Edge computing.” 

About Qeexo

Qeexo is the first company to automate end-to-end machine learning for embedded edge devices (Cortex M0-M4 class). Our 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. For more information, go to www.qeexo.com.

About STMicroelectronics

At ST, we are 46,000 creators and makers of semiconductor technologies mastering the semiconductor supply chain with state-of-the-art manufacturing facilities. An independent device manufacturer, we work with more than 100,000 customers and thousands of partners to design and build products, solutions, and ecosystems that address their challenges and opportunities, and the need to support a more sustainable world. Our technologies enable smarter mobility, more efficient power and energy management, and the wide-scale deployment of the Internet of Things and 5G technology. Further information can be found at www.st.com.

For Press Information Contact:

Lisa Langsdorf
GoodEye PR for Qeexo
Tel: +1 347 645 0484
Email: [email protected]

Michael Markowitz
Director Technical Media Relations
STMicroelectronics
Tel: +1 781 591 0354
Email: [email protected]

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Lose the MCU: ST and Qeexo Simplify Machine Learning with AutoML

All About Circuits 19 May 2021

Intelligent decision-making has moved to the edge with machine learning, though deployment could be complicated. Qeexo and STMicroelectronics are looking to change that.

Read the full article here: https://www.allaboutcircuits.com/news/lose-the-mcu-st-and-qeexo-simplify-machine-learning-with-automl/