『Predictive AI Should Make Sense, with Eric Siegel』のカバーアート

Predictive AI Should Make Sense, with Eric Siegel

Predictive AI Should Make Sense, with Eric Siegel

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This is Episode 1 of the Zeroed In Podcast. Marvin Tansley from Thing-Zero interviews Eric Siegel from Gooder AI to tackle real-world smart manufacturing challenges using predictive AI. Together, they break down common issues seen on the factory floors into quick-wins, with step-by-step guidance you can use to break into the exciting world of OT and increase ROI with predictive AI.

If you're in an IT or OT role in Manufacturing, this episode is for you!

Chapters: 00:00 – Intro & episode setup (manufacturing + AI)

01:06 – What Thing-Zero does: secure predictive analytics

01:30 – Guest intro: Eric Siegel (Goodter AI, ex-Columbia)

02:21 – The pain: ~30% downtime / quality loss in factories

04:26 – Predictive maintenance explained (why it’s the gold standard)

06:12 – Decisions by probability: expected cost in plain English

08:08 – Why pilots stall: missing business visibility & ROI

10:01 – Data you need: historical + real-time (same schema)

12:38 – Secure OT→Cloud pipeline (zero-trust, compliant)

13:02 – Crawl-Walk-Run roadmap to production value

16:03 – Change management: augment operators, don’t replace them

17:52 – Beyond binary: process optimization & democratized data

19:12 – From data lake to business wins (scrap, shifts, capex)

33:23 – Visibility → optimization → financial decisions (playbook)

38:33 – Wrap-up, next steps & how to get in touch


🎧 Brought to you by Thing-Zero — Secure. Predict. Augment. Automate.

📌 Follow Marvin Tansley on LinkedIn - https://www.linkedin.com/in/marvin-tansley-a914551/

📌 Follow Eric Siegel on LinkedIn - https://www.linkedin.com/in/predictiveanalytics/


Follow Thing-Zero on:

- YouTube: YouTube.com/@Thing-Zero

- Linkedin: https://www.linkedin.com/company/thing-zero/

- 𝕏: https://x.com/ThingZ96954

- Web: https://www.Thing-Zero.com#operationaltechnology

#IoT#AI #PredictiveAnalytics #SmartManufacturing

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