SensiML at Embedded World 2024
Embedded World 2024 is a wrap. If you missed us in Nuremberg, read this summary of what SensiML showed at the show and a preview of upcoming events where you can find us.
Embedded World 2024 is a wrap. If you missed us in Nuremberg, read this summary of what SensiML showed at the show and a preview of upcoming events where you can find us.
Watch the video of Chris Rogers’ conversation with Ross Sabolcik, VP/GM of Industrial and Commercial IoT products at Silicon Labs, about the benefits of AI at the edge, key use cases, and how Silicon Labs and SensiML are working together to advance IoT smart sensing with ML.
We just announced that SensiML has teamed up with Infineon Technologies AG to deliver a complete AI/ML solution for the Infineon PSoC™ 6 family of microcontrollers (MCUs) and XENSIV™ sensors. This is great news for Infineon customers as they can now use SensiML’s tools to easily create intelligent IoT endpoints using the ultra-low power and
SensiML has collaborated with Microchip Technology to deliver ultra-compact machine learning at the IoT edge combining SensiML Analytics Toolkit with the SAM-IoT WG evaluation kit, SAMD21 MCU, and MPLAB X IDE tool suite.
Today SensiML took a leadership position in AI/ML tools for the IoT edge by announcing our new Open Source Initiative. SensiML Open Source Embedded SDK (coming later this summer) – The full library of SensiML segmenters, transforms, features, and classifiers as implemented by the AutoML and Python-based SensiML Analytics Toolkit Notebook will become available in open source format.
SensiML has collaborated with Silicon Labs to enable AutoML-based rapid development of optimized machine learning sensor models for Silicon Labs’ energy-friendly EFR32 and EFM32 microcontrollers (MCUs).
This month SensiML is pleased to announce SensiML Analytics Toolkit now provides native support for STMicroelectronics’ SensorTile.Box Development Kit for wireless IoT and wearable sensor applications. SensiML’s support for SensorTile.Box includes our most sophisticated MQTT-based device data collection firmware yet made available in open source for customers to extend and modify as necessary to suit their particular application needs.
This month SensiML is pleased to announce SensiML Analytics Toolkit now provides native support for STMicroelectronics’ SensorTile.Box Development Kit for wireless IoT and wearable sensor applications. SensiML’s support for SensorTile.Box includes our most sophisticated MQTT-based device data collection firmware yet made available in open source for customers to extend and modify as necessary to suit their particular application needs.
This week SensiML added support for the Quicklogic QuickFeather Development Kit. Noteworthy for its inclusion of Arm Cortex-M4 MCU, FPGA, and an array of sensors in a fully open-source HDK using the popular Adafruit Feather form factor, the QuickFeather makes a great IoT development platform for developers of consumer, wearable, and industrial products.
SensiML announces two COVID-19 initiatives:
1) SensiML Toolkit Starter Edition is now available for a limited time at $99 for a 90-day license.
2) SensiML to open-source a COVID-19 AI dataset for rapid virus screening from cough sounds. Learn how you can contribute to this project yourself.
Today we announced that our SensiML Analytics Toolkit supports NXP’s i.MXT RT portfolio of crossover microcontrollers and their associated i.MX RT1050 Evaluation Kit. This announcement is significant as it gives users of those devices a complete AI-based sensor algorithm development solution for IoT endpoints. With this, NXP customers using the i.MX RT crossover MCUs can
Artificial Intelligence (AI) is becoming increasingly commonplace as organizations seek to bring effective decision making and operational efficiencies to business in ways that transform how humans and machines work together. As this transformation takes shape, the advantages of edge-based AI implementations over centralized or cloud-based models is changing how AI tools are being deployed and