More Is Different Broken symmetry and the nature of the hierarchical structure of science

By P. W. Anderson. 1972

Subfields: Natural Language Processing, Philosophy

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Citations in the corpus

Emergent Abilities of Large Language Models (2022, neutral): “Emergence as an idea has been long discussed in domains such as physics, biology, and computer science (Anderson, 1972; Hwang et al., 2012; Forrest, 1990; Corradini & O’Connor, 2010; Harper & Lewis, 2012, inter alia ).”
Can language models learn from explanations in context? (2022, positive): “Scaling and emergence: While LM loss can exhibit predictable scaling with model size (Ka-plan et al., 2020), these smooth changes can lead to qualitative differences in speciﬁc behaviours (Gan-guli et al., 2022)—“more is different” (Anderson, 1972).”
Transcending Scaling Laws with 0.1% Extra Compute (2022, neutral): “‘ [Anderson, 1972] which describes unpredictable phenomena at different scales.”
Understanding Well-Being and Optimal Functioning: Applying the Multilevel Personality in Context (MPIC) Model (2011, unknown): “What does it mean to say a phenomenon or level of organization “emerges” from the level below? This remains a very difficult issue in the philosophy of science, with various distinctions proposed between strong versus weak emergence, synergistic versus combinatorial emergence, and more (Anderson, 19”
Nonequilibrium physics in biology (2019, unknown): “A physical picture and unified quantitative theory is crucial for understanding this organization hierarchy and emergent complexity of the systems (Anderson, 1972; Frauenfelder and Wolynes, 1994; Haken, 2000; Hopfield, 1994; Laughlin et al., 2000; Prigogine and Stengers, 1984; Wolynes, 1996).”
Behavioral & Experimental Macroeconomics and Policy Analysis: A Complex Systems Approach (2018, unknown): “As a simple example from physics one may think of a glass of water, exhibiting a critical transition from liquid to solid when the temperature (which (3)The key observation that macro behavior in a complex system can not be reduced to micro behavior has been nicely summarized in the title of one of ”
Scientific discovery in the age of artificial intelligence (2023, unknown): “Integrating geometric priors 65 in learned representations has proved effective as geometry and structure play a central role in scientific domains 66–68 .”
The re-emergence of "emergence": A venerable concept in search of a theory (2002, unknown): “”[85] “The ability to reduce everything to simple fundamental laws does not imply the ability to start from those laws and reconstruct the universe.”