SensiML Blog

The Protecting the Peatlands Project won the second place in the battery-operated category of our “Combat Climate Change Challenge” contest. Peatlands are a special type of wetlands which are particularly valuable for preserving global biodiversity, sequestering carbon, and filtering water.  Unfortunately, a good percentage of the earth’s peatlands have already been eliminated or significantly damaged,

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For Alejandro, helping to solve this problem really hit home as it’s a big issue in his native country of Mexico.  In his words, “The environmental effects of illegal logging include deforestation, the loss of biodiversity and the emission of greenhouse gases.  Illegal logging has contributed to conflicts with indigenous and local populations, violence, human rights

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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

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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

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Highlights: Starting August 1st, SensiML is updating its service plans to bring more value and flexibility to its customers.  A new plan offering called ‘Proto Edition‘ (or just ‘Proto’) provides a pay-per-use option for first-time and infrequent users of AutoML tools. By offering service on a single application basis, ‘Proto’ allows such users to gain familiarity

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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

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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.

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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.

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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.

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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).

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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.

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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.

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