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: 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
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 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!
SensiML Analytics Toolkit now provides pipeline support for one of the most popular open-source AI frameworks in existence: TensorFlow, specifically its TinyML variant TensorFlow Lite for Microcontrollers. This week we’ve added a step-by-step boxing wearing tutorial showing how SensiML data collection, annotation, and feature preprocessing are combined with a neural network classifier using TFL Micro.
This week SensiML joined a distinguished panel of healthcare, technology, and academic leaders to overview its contributions to towards an innovative COVID-19 screening technology for deployment later this year.
As we seek to spread the word on our COVID-19 AI data collection initiative, Nasdaq generously offered to promote our initiative on the “Nasdaq Tower”, a giant multi-story electronic display in Times Square in New York City. Those interested in contributing anonymous cough sound samples on our collection site https://sensiml.com/covid-19 can help build sensor insight we will make available as open source dataset and an edge AI screening solution later this year.
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.
This week SensiML is releasing an all new version of its industry leading AutoML application SensiML Analytics Studio for building optimized embedded sensor algorithms for IoT devices. SensiML Analytics Studio has existed since our inception as a core component of our AI Toolkit. Previously it consisted of both a Python language interface for data scientists
Today kicked off a week of demo meetings at CES showcasing how SensiMLTM Analytics Toolkit can make quick work of algorithm development for IoT sensing wearable devices. Our demo suite showed first-hand the data collection, AutoML code generation, and testing of two different wearable applications that were built in under a week. Demo #1 –
