We’ve discussed many of the other top applications submitted for our Challenge Climate Change contest (a collaboration between us, QuickLogic, and hackster.io). Next we’d like to discuss one called “BirdBuddy” – a really interesting project and a 2nd place finisher in the contest. Due to climate change, birds are migrating earlier each year. Different species in
Opportunities to improve manufacturing processes by adding machine learning sensors at the IoT edge are rapidly emerging. Thanks to a combination of Powerful microcontrollers and multi-core SoCs like the EOS S3 on QuickLogic’s QuickAI HDK High-resolution, low-cost MEMS sensors and microphones Powerful AutoML-based AI tools like SensiML Analytics Toolkit it is possible to bring sophisticated
Highlights: New Proto Plan offers fixed fee for a single application Proto reduces term anxiety with a full year license to use All paid plans to provide flexible add-on features Customers can now tailor their plans to suit their exact needs Starting August 1st, SensiML is updating its service plans to bring more value and
About six months ago we, the folks at QuickLogic, and the Avnet Hackster.io online community announced our Challenge Climate Change contest. The idea was to encourage creative smart technology projects that improve awareness, change behavior, or optimize processes to impact climate change for the better. Towards that end, we opened up the contest to developers
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.
Webinar tutorial series discussing a variety of topics related to embedded IoT development, TinyML and AI at the edge, sensor data processing, and the application of SensiML Analytics Toolkit.
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).
SensiML will be presenting on Thursday, March 25th at 12 noon. We will cover how to build smart IoT products with production-quality AI tools.
SensiML is introducing a new free Community Edition tier of its industry-leading edge AI toolkit made expressly for experimenters, innovators, and product R&D teams. SensiML Community Edition provides the means to build fully functional edge IoT inference models using one’s own existing labeled or unlabeled datasets, newly captured sensor datasets using SensiML Data Capture Lab, or models built leveraging our growing Data Depot library of example and community datasets.
Climate change: A huge challenge forcing us all to be smarter about how we utilize our planet’s resources. At SensiML we’re all about smarter, which is why we’re teaming up with QuickLogic and Hackster.io to create the “Challenge Climate Change” contest with over $70k in prizes. So do some good, learn about edge AI, and maybe win big!
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.
