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You may have heard the terms proof-of-concept, pilot, and production thrown around relating to various projects at your organization. But, do you know the difference between all of them?
And when running and AI project should you start with a proof-of-concept or pilot project?
In this episode of the AI Today podcast hosts Kathleen Walch and Ron Schmelzer define the terms Proof-of-Concept, Pilot, and Production. The podcast explains how these terms relate to AI projects and why it’s important to know about them.
We also explain why AI projects should always be pilots, and by the end of this podcast you’ll have a better understanding of why.
Show Notes:
- FREE Intro to CPMAI mini course
- CPMAI Training and Certification
- The Five Steps for an AI Project: What you’re missing
- A Step-by-Step Approach to Running AI and Machine Learning Projects
- AI Glossary
- AI Glossary Series – DevOps, Machine Learning Operations (ML Ops)
- AI Glossary Series – Data Preparation, Data Cleaning, Data Splitting, Data Multiplication, Data Transformation
- AI Glossary Series – Data Augmentation, Data Labeling, Bounding box, Sensor fusion
- AI Glossary Series – Data, Dataset, Big Data, DIKUW Pyramid
- AI Glossary Series – V’s of Big Data, Data Volume, Exabyte / Petabyte / Yottabyte / Zettabyte, Data Variety, Data Velocity, Data Veracity
- AI Glossary Series – Machine Learning, Algorithm, Model
- Glossary Series: Machine Learning Approaches: Supervised Learning, Unsupervised Learning, Reinforcement Learning
- AI Glossary Series- Methodology, Waterfall, Agile, CRISP-DM, Cognitive Project Management for AI (CPMAI)
