Tag: AI
-
Humans rationally balance abstract world models
This work adds to a growing body of research showing that the brain arbitrates between approximate decision strategies. The current study extends these ideas from simple habits into usage of more sophisticated approximate predictive models, and demonstrates that individuals dynamically adapt these in response to the predictability of their environment. How do people model the…
-
Defining intelligence: Bridging the gap
“Defining intelligence: Bridging the gap between human and artificial perspectives“ Achieving a widely accepted definition of human intelligence has been challenging, a situation mirrored by the diverse definitions of artificial intelligence in computer science. By critically examining published definitions, highlighting both consistencies and inconsistencies, this paper proposes a refined nomenclature that harmonizes conceptualizations across the two disciplines.…
-
Is Ockham’s razor losing its edge?
Is Ockham’s razor losing its edge? New perspectives on the principle of model parsimony The preference for simple explanations, known as the parsimony principle, has long guided the development of scientific theories, hypotheses, and models. Yet recent years have seen a number of successes in employing highly complex models for scientific inquiry (e.g., for 3D…
-
Bayesian Models of Cognition
“Bayesian Models of Cognition Reverse Engineering the Mind” is a new MIT-press Open Access book available for online reading. The definitive introduction to Bayesian cognitive science, written by pioneers of the field. How does human intelligence work, in engineering terms? How do our minds get so much from so little? Bayesian models of cognition provide…
-
Energy cost of computation: stochastic thermodynamics?
“Is stochastic thermodynamics the key to understanding the energy costs of computation?” The relationship between the thermodynamic and computational properties of physical systems has been a major theoretical interest since at least the 19th century. It has also become of increasing practical importance over the last half-century as the energetic cost of digital devices has…
-
KNOWLEDGE ACQUISITION hindered by KNOWLEDGE ENTROPY DECAY during language model pretraining
This paper describes how a model’s tendency to broadly integrate its parametric knowledge evolves throughout pretraining, and how this behavior affects overall performance, particularly in terms of knowledge acquisition and forgetting. The concept of knowledge entropy is introduced, which quantifies the range of memory sources the model engages with; high knowledge entropy indicates that the…
-
regulation of motivated behavior
in “A unified theoretical framework underlying the regulation of motivated behavior“, Yu-Been Kim, Young Hee Lee, Shee-June Park and Hyung Jin Choi explain that multiple psychological components have evolved in order to orchestrate behaviors for survival. Despite several theories regarding behavior regulation, these theories do not clearly distinguish distinct components and do not explain the…
Surtil : 