Generative AI: What's Next?
summary
Describes how Stable Diffusion turns text prompts into images and argues generative AI becomes a practical design tool, not just research: models trained on billions of images (hundreds of terabytes) are distilled and retrieval-augmented so they can run on $300 hardware, even mobile, compressing internet-scale visual knowledge down to a few gigabytes (examples: 10 GB desktop, ~2 GB phone). Highlights concrete methods—distillation, mixture-of-experts, database lookups—and warns model scaling outpaces available compute, making democratization and efficient architectures urgent.
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chapters (9)
- 0:00The impact of generative AI
- 1:36From programming to prompting
- 4:28Generative AI vs traditional
- 7:00Opportunities for Europe
- 9:31Future AI trajectory
- 12:07Scaling and cost challenges
- 14:40Democratizing AI technology
- 16:58Future outlook and needs
- 19:43Q&A and societal impact
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