The recent emergence of artificial intelligence (AI) as a tool for applications ranging from facial recognition to industrial control has been both exciting and shocking. While many will debate how well our current implementation of AI compares to Turing’s initial conceptualization and definition, few will debate how quickly it has become a useful and indispensable tool for designers, as well as an area worthy of further research in academia. Still, the actual definition of AI remains subjectively and unfairly tied to the current state-of-the-art instead of what Turing had imagined, and for many designers and engineers, its implementation is a complex balance of capabilities and processing performance versus available power, memory, and communications resources.

This Three Part EETimes University Course will clear away some of the misperceptions around AI, clarify what it can—and cannot—do, describe how to form training models, and show to deploy that model on real-word hardware. 

 

Three-Day Curriculum:

 

Part 1:  Concepts –   November 10th @ 9amPT/12pm ET

In Part 1 of this week’s course, we will define the state-of-the art of AI, clarify how it works, explain its underlying principles, provide updates on its advances and branches of research.

 

Part 2: Training –   November 11th @  9amPT/12pm ET

 

In Part 2 Attendees will come away with a clear understanding of the various training methodologies and available tools (hardware and software) and how to use them. Design and optimization techniques will be discussed and notes on the importance of acquiring the right data will be included.

 

Part 3: Deployment – November 12th @ 9amPT/12pm ET

 

In Part 3, we will examine the process of deployment, and the host platform design considerations and discuss further optimization techniques.