In this episode of "The Macro AI Podcast," Gary and Scott guide business leaders through building a private AI system for manufacturing, hosted in a colocation facility, from ideation to launch. Discover how AI can transform operations—think predictive maintenance to cut downtime or real-time quality control to boost product consistency. We start with ideation, spotlighting use cases like GE’s Predix (30% cost savings) and Tesla’s AI vision in Gigafactories. Next, we dive into data prep, leveraging factory sensors and images, and explore colocation’s edge for secure, scalable processing. Model selection gets deep—CNNs for defect detection, RNNs for machine health, plus options like Transformers and pre-trained models from Hugging Face or TensorFlow Hub, alongside vendors like Siemens. Training’s unpacked too: source data from IoT or simulations, use GPUs in a colo for speed, and fine-tune for precision (aiming for 95% accuracy). Testing ensures reliability, integrating with systems like MindSphere, while launching scales from pilot to enterprise, as Toyota’s 15% cost cuts show. Costs? $1,000-$3,000 monthly per colo rack, with massive ROI potential—PwC pegs AI’s manufacturing value at $4 trillion by 2030. For leaders, it’s practical advice: start focused, tap teams, and partner smart. Tune in to lead in the AI era and compete globally! 

 

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About your AI Guides

Gary Sloper

https://www.linkedin.com/in/gsloper/

Scott Bryan

https://www.linkedin.com/in/scottjbryan/

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