Most AI projects fail because they’re built on demo data, not production data.
David Bauer explains why machine learning, LLMs, model training, model serving, MLOps, federated AI, and enterprise AI systems often break when they leave the demo environment. If your AI workflow starts with a CSV file instead of real production data, you're probably solving the wrong problem.
The difference between a successful AI deployment and a failed project often comes down to production data, testing, evaluation, and real-world AI engineering.
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