103: Using AI in Manufacturing: Generative vs. Predictive and Autonomous AI with Bryan DeBois

Most manufacturers are chasing the wrong AI problem. In this episode Chris talks with Bryan DeBois, Director of Industrial AI at RoviSys, about why industrial AI for manufacturing requires a different approach than generative AI.
Bryan explains the limits of generative AI on the plant floor, why deterministic systems matter in high risk environments, and how analytical AI, predictive AI, computer vision, and autonomous AI are already being used to improve quality, safety, throughput, and asset performance. Leaders should listen to understand how industrial AI can protect expertise, strengthen operations, and create practical advantage beyond the ChatGPT conversation.
Chapters:
00:00 Introduction
01:16 Why Factory Floor AI Is Different From Knowledge Work AI
03:58 The Four Types of AI Used in Manufacturing Today
05:50 Why Generative AI Fails in High Risk Operational Environments
10:56 Manufacturing Risks Also Apply to Construction and Life Sciences
11:36 The Workforce Crisis Driving Industrial AI Adoption
15:26 Why Manufacturing Careers May Be Safer Than White Collar Jobs
20:42 Why Humanoid Robots Are Not the Future of Manufacturing
24:53 Capturing Tribal Knowledge Before Experts Retire
40:00 Who Should Own AI Inside Manufacturing Organizations
43:24 Meta’s Cicero Project and the Future of Hybrid AI Systems
47:08 Deterministic AI vs Probabilistic AI in Critical Industries
49:27 Where to Follow Brian De Bois and Learn More About Industrial AI

Resources:
🔎 Find Out More About Bryan DeBois
Bryan DeBois on LinkedIn:
linkedin.com/in/bryan-debois
RoviSys Industrial AI:rovisys.com/ai
RoviSys:
rovisys.com
🛠 AI Tools and Resources Mentioned:
ChatGPT:chatgpt.com/Claude:https://claude.com/Grok:htt… AI CICERO:ai.meta.com/research/cicero/Google DeepMind AlphaGo:deepmind.google/research/breakthroughs/alphago… HoloLens:microsoft.com/hololensObsidian:https://obsidia…:
sap.com
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