Generative AI & its Transformation of Business, Research, and Society
summary
Generative AI lets people command large models in natural language and thus turn prompts into working artifacts — images, website mockups and even source code — exemplified by Stable Diffusion which reliably generates images from text. Training uses self-supervised learning and yields emergent capabilities rather than mere parroting. Progress relied on massive scaling (about 15,000-fold model growth in five years) but hardware lags by roughly a 10x compute gap, causing flattening and some performance drops and forcing new research directions.
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chapters (14)
- 0:00Introduction
- 0:29Generative AI transformative tech
- 1:10Why AI changes everything fast
- 3:40Natural language as new code
- 6:30Self-supervised learning & AI emergence
- 7:56Unsustainable model growth
- 10:04Beyond scaling models
- 11:06AI revolution in software dev
- 12:52European AI innovation
- 13:57AI in societal communication
- 17:11Personalized complex messaging
- 17:52AI magnifies labor issues
- 19:20Open-source AI for risk mitigation
- 20:24Future of generative AI
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