AIML16 - Practical A.I.: From Core Concepts to Modern Models
Program Description
With OpenAI’s release of GPT-3 in 2021, industries across the board (including many with little prior engagement in A.I.) began rapidly exploring how these technologies could transform their operations. This workshop offers a clear, practical introduction to artificial intelligence and machine learning for professionals in any field, with applied examples tailored to additive manufacturing.
This program is a Pre-Conference Training for AMUG 2026 in Reno, NV. AMUG Conference attendees are encouraged to register for this pre-conference training. This training is not included in AMUG Conference registration, and signing up for this training does not register you for the AMUG Conference.
Learning Objectives:
After completing the program, participants will be able to:
- The fundamentals of A.I., including the different types of problems that A.I. is well-suited to solving and how those solutions differ
- More advanced A.I. techniques (e.g., large language models and transformer-based embedding techniques) and how participants can apply these techniques to their own real-world problems
- How errors and biases can arise in A.I. solutions, how to defend against them, and other ethical considerations when using A.I.
Participants will work through many hands-on examples, and there will be dedicated time to discuss individual questions and specific additive-manufacturing scenarios.
No prior experience with A.I. is required!
Dr. Gabriel Wright is an Assistant Professor of Computer Science at the Milwaukee School of Engineering. He graduated with a Ph.D. in Computer Science and Engineering from the University of Notre Dame in May 2021. Gabriel’s primary research work is in computational biology, specifically studying the effects of rare codons on resulting protein expression, folding, and function.