Beyond the Hype: Realistic Expectations of AI
summary
Panelists report concrete wins and limits: Perplexity shopping curates product lists, Copali vision LLMs finally extract structure from PDFs, and voice cloning from 11 labs restores work for professionals who lose speech. Examples of tooling that speeds work include GitHub Copilot and DeepL; costs show up as training energy and token bills. Misconceptions get named — LLMs as human thinkers or having common sense — and ROI is framed in hours saved, missed-deadline penalties, and measurable benchmarks rather than hype.
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chapters (7)
- 0:00Introduction
- 1:07Panelists' AI moments
- 9:21AI misconceptions
- 16:52AI augments human roles
- 25:03Measuring AI ROI
- 33:15Ethical AI development
- 37:30AI hype vs reality
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