Table of Contents
What is meant by embedded intelligence?
‘Embedded Intelligence’ refers to the capability of a certain product, service, or process to evaluate and contemplate its performance. As well as the ability to handle the workload or its own working environment. This in turn leads to performance enhancement further resulting in the ultimate user satisfaction.
How machine learning is used in embedded systems?
Machine learning (ML) enables electronic systems to learn autonomously from existing data and to use this acquired knowledge to independently make assessments, predictions and decisions. Embedded devices for machine learning applications can fulfill many tasks in industry.
What problems do artificial intelligence systems include?
Notwithstanding the tangible and monetary benefits, AI has various shortfall and problems which inhibits its large scale adoption. The problems include Safety, Trust, Computation Power, Job Loss concern, etc.
What is the future of AI in embedded systems?
The future is entirely practical: AI will be in embedded systems, designed to operate as close as possible to a device which only needs to be turned on. The practical reality is dealing with the gargantuan knowledge gap between AI developers and their customers.
Why embedded developers need to pay attention to AI and ML?
Embedded developers need to start paying attention to AI and ML, and the time to start learning these new capabilities isn’t when you need to implement them in a design and are already behind — the time is now. Artificial intelligence (AI) and machine learning (ML) seem to be in the headlines more and more each year.
What does an embedded developer need to know about machine learning?
It has everything that an embedded developer needs to run machine learning algorithms quickly and efficiently in a real-time microcontroller. Using machine learning can add a level of intelligence to an embedded system that would otherwise be time consuming or nearly impossible to implement traditionally.
What course should I do to become an embedded systems engineer?
Computer Science with Machine Learning then an extra course in embedded systems. Or an embedded systems course with an extra course in machine learning. Good targets for machine learning in embedded systems are: IoT, HVAC and medical appliances. Machine learning depends on mathematical modelling approach.