Trust and Validation in AI
About this video
What You'll Learn
- Why black-box AI makes proprietary data, training provenance, and enterprise trust inseparable.
- How The Pile, Hugging Face models, and copyright questions shape dataset risk.
- Why citations, clean source data, and human verification matter for hallucinated outputs.
JJ Asgar joins to discuss IBM watsonx.ai and why enterprises distrust today's black-box AI. The conversation covers training data provenance, The Pile, Hugging Face, hallucinations, copyright, and the human problem of verifying AI outputs.
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