Now We’re Talking!
We just released a new GenAI feature in Data Studio that rapidly creates hyper-realistic synthetic speech datasets from simple text input. In this blog we walk through the details of the feature and how to use it.
We just released a new GenAI feature in Data Studio that rapidly creates hyper-realistic synthetic speech datasets from simple text input. In this blog we walk through the details of the feature and how to use it.
Integrating generative AI into SensiML’s open-source Piccolo AI toolkit is a significant opportunity ripe for prototyping, testing, and ongoing refinement. We discuss the prospects for generative AI and explore specific ideas for its use.
SensiML announces new open-source AutoML tool Piccolo AI, publishes GitHub repo for developer access.
Why SensiML is open-sourcing its core AutoML server software and how this benefits the TinyML ecosystem.
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.
Innovative SensiML DataOps software now available as a standalone subscription. Streamlined plans and pricing announced across the SensiML lineup.
An example of a complete smart toy application built around on-device, ML-based gesture recognition using the M5StickC PLUS.
We’ve updated SensiML Analytics Toolkit with a variety of new features to make it easier than ever before for users to create and manage their AI/ML projects and visualize their datasets in insightful new ways.
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.
Winner of the Infineon Build AI for the IoT contest selected SensiML for delivering edge AI for their application.
Part 4: Profiling the performance of the AI-accelerated EFR32MG24 model
Part 3: Generating a working smart door lock model for the SiLabs xG24 Dev Kit