A Smarter Way to Make Intelligent Machines
Build Products using Sensors and Edge AI / TinyML
A Smarter Way to Make Intelligent Machines
Build Products using Sensors and Edge AI / TinyML
Benefits
Speed and Accuracy, with a Small FootprintProducts need to work, and they also need to fit a price point. Reality AI merges machine learning with advanced signal processing math, delivering fast, efficient machine learning inference that fits on the smallest microcontrollers — enabling smart product features with inexpensive hardware.
Transparency and ExplainabilityNo engineer will deploy a solution they don’t understand. Reality AI Tools® delivers visualizations of model function in terms of time and frequency domains, so you can explain to colleagues and stakeholders why models perform as they do.
Cost OptimizationInstrumentation and data collection are 80% of the cost of machine learning projects. Reality AI Tools® can identify the most cost-effective combinations of sensor channels, find the best sensor locations, and generate minimum component specifications. It can also help you manage the cost of data collection by finding instrumentation and data processing problems as data is gathered.
Benefits
Speed and Accuracy, with a Small Footprint
Products need to work, and they also need to fit a price point. Reality AI merges machine learning with advanced signal processing math, delivering fast, efficient machine learning inference that fits on the smallest microcontrollers — enabling smart product features with inexpensive hardware.
Transparency and Explainability
No engineer will deploy a solution they don’t understand. Reality AI Tools® delivers visualizations of model function in terms of time and frequency domains, so you can explain to colleagues and stakeholders why models perform as they do.
Cost Optimization
Instrumentation and data collection are 80% of the cost of machine learning projects. Reality AI Tools® can identify the most cost-effective combinations of sensor channels, find the best sensor locations, and generate minimum component specifications. It can also help you manage the cost of data collection by finding instrumentation and data processing problems as data is gathered.
“A different approach to edge AI through hardware optimization and MCU modeling.”
Jem Davies, VP, GM and Fellow
Machine Learning Group, Arm
“Very well suited to automotive applications, able to run on cost-effective automotive components.”
Motoki Kanamori
Advanced Hardware Development – Denso Cockpit Systems
“We can quickly evaluate sensor options and develop prediction models for diverse
equipment.”
Shuji Itatani
Director of the Technology and Innovation Center, Daikin
“Can inspect and interpret complex signatures using time and frequency.”
Sellafield Ltd and National Nuclear Laboratory
“The market impact of innovations like Reality AI are tremendous because they leverage a customer’s existing assets and add significant value on top of substantial prior investments.”
Gartner
“Emerging Technologies: Tech Innovators in Edge AI”, 2020
“A completely new sensory input for cars… will likely play an important role in future sensor suites”
LARS ULRICH
VP of Automotive, Infineon Technologies Americas
Reality AI Partners Include:
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