# AI in Manufacturing Podcast: Episode Show Notes
## Episode: Optimizing AI Inference for Agentic Operations in Manufacturing
**Podcast Name:** AI in Manufacturing Podcast (Industry40.tv)
**Episode Title:** Optimizing AI Inference for Agentic Operations in Manufacturing
**Guest:** Kelvin Cooper, Co-Founder & CEO, Neurometric.ai
**Host:** Kudzai Manditereza
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## 1. Episode Summary
This episode explores why manufacturing companies struggle to scale AI from pilot to production—and how inference orchestration and small language models (SLMs) offer a practical path forward. Kelvin Cooper, Co-Founder and CEO of Neurometric.ai, joins host Kudzai Manditereza to break down why routing all AI tasks through a single frontier model becomes a cost and reliability liability at scale. Cooper draws on his background in venture capital, private equity AI rollups at Pilot Wave Holdings, and AI policy research at the Milken Institute to argue that the future of industrial AI is not one model that knows everything, but a coordinated system of specialized models that each know their job. The conversation covers Neurometric's AI maturity framework, real customer results showing 10x cost and latency improvements, the concept of catastrophic forgetting, and why manufacturing leaders need to adopt a startup execution mindset rather than over-analyzing use cases. Leaders seeking to cut AI inference costs and accelerate deployment will find actionable strategies throughout.
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## 2. Key Questions Answered in This Episode
- Why do 95% of AI proof-of-concepts in manufacturing never make it to production?
- How should manufacturers select their first AI use case instead of getting stuck in analysis paralysis?
- What is inference orchestration and why does it matter for scaling AI in manufacturing?
- Why is relying on a single large language model a liability for industrial AI at scale?
- What are small language models (SLMs) and how do they deliver faster, cheaper, and more accurate AI?
- What is catastrophic forgetting and how does it affect AI deployments in manufacturing?
- How can manufacturers avoid vendor lock-in when building AI systems?
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