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Alex Hickey • A Conversation With "Range" Author David Epstein
Hypercycle
docs.google.comtechnological progress seems to have been faster with larger, connected groups of people. In the smallest groups, like in Tasmania, they actually lost technology, like some fishing techniques.
Dwarkesh Patel • The Scaling Era: An Oral History of AI, 2019–2025
In the 1930s, Max Kleiber, a Swiss agricultural biologist, observed that, across mammal species, from shrews to elephants, the energy required to maintain basic metabolic function is closely correlated with an organism’s body size.
Jessica C. Flack • Worlds Hidden in Plain Sight: The Evolving Idea of Complexity at the Santa Fe Institute, 1984–2019 (Compass)
Advances in Financial Machine Learning
Because these groups of users generally live inside of atomic networks, the other thing that happens is that networks tend to attract other atomic networks. And so
Andrew Chen • The Cold Start Problem: How to Start and Scale Network Effects
the Collective Intelligence Project (CIP), Anthropic's recently released Claude3 model, considered by many to be the current state-of-the-art in GFMs, sourced the constitution used to steer model behavior using Polis.
Audrey Tang • ⿻ 數位 Plurality: The Future of Collaborative Technology and Democracy
Kleinberg was trying to understand network behavior. Page and Brin were building something.
Steven Levy • In The Plex: How Google Thinks, Works, and Shapes Our Lives
Complex systems science is different. It seeks order by understanding how simple parts, interacting together and perhaps adapting to one another, create an entirely new whole. The