Machine learning

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SmartEdgeML: Ultra-low power on-sensor machine learning
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TDK SmartEdgeML brings the power of machine learning (ML) algorithms to motion sensors. Enable next-generation features such as activity and gesture recognition to smartwatches, hearable, wearables, and health monitors. Execute pre-trained machine learning models directly on tiny IMU sensor chips to offload tasks from device processors.
About us section
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Key Capabilities of SmartEdgeML
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1. Ultra-low power

Run decision tree ML models on < 30 ยตA for always on sensing without sacrificing battery life

2. Tiny size

Extreme edge machine learning to run ML models on TDK IMU chips as small as 2.5 x 3 mm

3. Auto mode & easy development

Developer tools to get started quickly, configure options, train, view performance metrics

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Ultra-low power
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Run decision tree ML models on < 30 ยตA for always on sensing without sacrificing battery life

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Tiny size
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Extreme edge machine learning to run ML models on TDK IMU chips as small as 2.5 x 3 mm

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Auto mode & easy development
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Developer tools to get started quickly, configure options, train, view performance metrics

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Machine Learning sensors
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Explore popular sensors that can run ML models
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Key Capabilities of SmartEdgeML
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Select spotlight products
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Add device ML intelligence to an array of applications
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SmartEdgeML enables personalized experiences for a range of devices
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Smartglasses
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  • Run sensing algorithms on sensor for extra long battery life
  • Detect a variety of gestures and automated controls, including taps, donning and doffing, and voice detection 
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Low power gesture, movement and direction awareness
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Smartphones and PCs
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  • Detect in-car vs. walking
  • Program new device behaviors based on difficult to sense conditions 
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Improve movement recognition as each device learns individual variations
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Wearables & hearables
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  • Reliably recognize and differentiate head, hand, and body gestures despite individual differences
  • Better differentiate between different activities and exercises 
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Deliver accurate gesture and activity monitoring to enable new use cases
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Enable new use cases
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Train sensors to recognize human activities, motions, and gestures

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Ensure data privacy
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Leverage highly personal user data without it ever leaving the sensor

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Improve battery life
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Machine learning can execute on sensors while the rest of the devices is asleep 

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Make smarter devices with on-sensor machine learning
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TDK SmartEdgeML brings ML algorithms to sensors
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