The AI Summit will define AI and its key components, providing public works professionals with a clear understanding of the terminology and areas of public works already being impacted. Attendees will explore the various engines within AI systems, such as neural networks and machine learning, and consider how AI is trained using data, including the role of large language models. The Summit will also examine the ethical and legal challenges AI presents, addressing risks such as training bias and cybersecurity, while equipping participants with strategies to mitigate these issues. Day two will feature presentations from public works professionals discussing real-world AI applications in different technical areas, followed by an open forum for attendees to share insights, experiences, and next steps for AI in their workplaces. This comprehensive program will demystify AI, facilitate conversations around its future, and offer opportunities for knowledge sharing and collaboration.

Session 2: How AI systems are developed and trained (generative, non-generative/machine learning, etc.)

Learning Objectives:

• Describe the engines within AI systems (neural networks, machine learning, deep learning, etc.).
• Identify the role of data (especially big data) in training AI systems—how much is needed, what quality control must be done, and so forth.
• Explain what large language models (LLMs) are and how transformer models are part of LLMs.

Additional Sessions from the AI Summit are available on the Resource Center

AI Summit-Defining AI and Its Key Components
AI Summit-AI in Public Works Presentation Series
AI Summit-Addressing the ethical and legal considerations and potential impacts of AI in public works, while managing resistance to AI in the workplace

Links/Handouts:

Discussion Guide

Day 1, Session 2 Handout

Speakers:

Steve Cacioppo
Senior GIS Analyst
Douglas County GIS

Chris Lareau
Co-Founder and COO
Vue Robotics

Moderator:
Tracy Warner
Deputy Director of Development Services
Pima County, Arizona

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