Machine Learning and AI Topics

Join Us at the TinyML Summit

March 23, 2021

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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UPDATE: SensiML Integrates Google’s TensorFlow Lite for Microcontrollers

September 23, 2020

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.

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SensiML Integrates Google’s TensorFlow Lite for Microcontrollers

September 16, 2020

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. The combination of SensiML and TensorFlow Lite for Microcontrollers offers best-in-class AI code generation for TinyML applications from consumer wearables to multi-sensor industrial monitoring devices.

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When AI Goes Wrong: Avoid This Leading Cause for Project Failure

July 30, 2020

Scenario: Six months and $500,000 of investment into a key initiative to build a more intelligent product or streamline a strategic internal process using AI, and things are not going well.

The frequent culprit is poor upfront planning for a data-centric approach to development. Read more about this all too common issue that can undermine AI project success before you even start.

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SensiML’s Response to the Coronavirus Pandemic

May 11, 2020

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.

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The Case for AI at the Edge

February 21, 2020

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

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