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At a time when computational resources seem abundant, there is much excitement around scaling up machine learning and training increasingly larger models on bigger datasets. Intelligent life, however, has arisen not from an abundance of resources, but rather from the lack of it. Evolution naturally selects systems that are able to do more with less. We can see many examples of such resource “bottlenecks” that helped shaped our development as a species: from the way the brain is wired, and how our consciousness is able to process abstract thought, to how we are able to convey abstract concepts to one another through drawings and gestures that developed into languages, stories, and culture. It is debatable whether such bottlenecks are a requirement for intelligence to emerge, but it is undeniable that our own intelligence is a result of resource constraints.
I am interested in studying how intelligence might have emerge from limited resource constraints. Below are a selection of projects that I had worked on over the years that is related to my interest. Some of the works illustrate machine learning concepts interactively inside of a web browser.
I am interested in studying how intelligence might have emerge from limited resource constraints. Below are a selection of projects that I had worked on over the years that is related to my interest. Some of the works illustrate machine learning concepts interactively inside of a web browser.
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论文共 56 篇作者统计合作学者相似作者
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CoRR (2024)
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Proceedings of the Genetic and Evolutionary Computation Conference Companion (2022)
Collective Intelligenceno. 1 (2022): 26339137221114874-26339137221114874
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