Qeexo, a TDK group company, released an automated ML platform for Arm Keil MDK delivering an extensive range of ML algorithms developed for the Cortex-M0 to -M4 class processors. It is designed to promptly analyze sensor data for ML solutions.
CES 2023. While highlighting 30 technologies, solutions, and platforms at CES 2023 (Central Hall - #16181), TDK Corporation also released information regarding its agreement to obtain Qeexo, Co. Qeexo will bring its expertise of automated machine-learning (ML) platforms for tinyML models requiring low power, and continuous running intelligent platforms. Qeexo will be completely absorbed by TDK for the goal of being an Industry 4.0 leader in enhancing smart edge applications.
Arm announced its Arm Virtual Hardware solution, a cloud-based virtual modeling platform that provides models of Arm subsystems and third-party development boards to allow software developers, OEMs, and service providers to begin software development as well as software and hardware co-design without physical silicon or complex board farms. This virtual approach enables embedded systems developers to both use and scale modern development practices like MLOps and DevOps flows at scale.
Qeexo and Bosch Enable Developers to Build and Deploy Machine-Learning Algorithms to Bosch AI-Enabled Sensors - NewsMay 25, 2022
Qeexo, developer of the Qeexo AutoML, and Bosch Sensortec GmbH 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 Collaborates with STMicroelectronics to Automate Machine Learning on Machine Learning Core (MLC) Sensors - NewsMay 19, 2021
Qeexo announced that it is working with STMicroelectronics to create machine learning models for ST’s Machine Learning Core (MLC) sensors.
Qeexo AutoML platform now supports machine learning on Arm Cortex-M0 and Cortex-M0+ processors.
For a limited time, users can register for a free Bronze package of AutoML that allows them to upload or collect data sets and automatically build and deploy lightweight machine learning models.