We discuss Symbolic AI via LLMs for advanced reasoning in manufacturing and real-time analytics. Key points included leveraging symbolic representations and algebraic equations, utilizing knowledge graphs to improve model accuracy, and exploring agentic AI frameworks with specialized agents working together using swarm intelligence principles to tackle complex problems like anomaly detection and process optimization. The group also discussed the challenges of building trust in AI systems and the importance of capturing and storing questions and answers to build a knowledge base.
Tag Archives: Artificial Intelligence
Generative DevOps
NOTE: This is Rob’s Gluecon topic on 5/24. Save $300 if you register with speaker300 at www.gluecon.com
We dive into the question of whether or not generative AI can be used to productively change DevOps automation and the control of infrastructure.
We’ve discussed the closed loop side of using AI to manage infrastructure in the past, but this episode we really dive into the idea of creating automation and using generative AI.
Transcript: otter.ai/u/VtnznHgydT3_6QSJpk…?utm_source=copy_url
Image: www.pexels.com/photo/tossing-fri…ying-pan-6937457/
Machine Learning in Operations
Today’s episode is about how to trust machine learning in operations. This is a really serious issue because the attraction of machine learning is strong, but does not translate into operations.
Why doesn’t it translate? Because operations is a closed loop process where we constantly get feedback and have to adapt and adjust. That makes it difficult to train models and hope that they work. This discussion gets into why that’s the case and what we can do about it.
Then we explore scenarios for machine learning and AI in operations.
Transcript: otter.ai/u/UBjf5IVnKvebTfQgW1xlneZdjOU
Photo: www.pexels.com/photo/high-angle-…of-robot-2599244/