
Beyond Optimization — Why AI Needs to Learn From Nature’s Creativity
As AI hits the limits of scaling bigger models with more data, researchers are turning to nature’s own innovation engine: evolution, with open-ended exploration that
As AI hits the limits of scaling bigger models with more data, researchers are turning to nature’s own innovation engine: evolution, with open-ended exploration that
Towards a more diverse AI ecosystem
Balancing technological progress with human agency in an era of rapid advancements.
More must be done to establish a middle ground between outright optimism and pessimism about technology.
Insights from the 26th NCC: Decentralized AI systems and the impact of Japanese philosophical perspectives.
Neurodiversity offers a fresh lens to view and evolve AI’s potential.
Deep learning is the prevailing approach today, but history teaches us to broaden our outlook.
Probabilistic programs are aligned with the digital architecture that will shape the next phase of the Internet.
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