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Mahowald, Kyle; Kachergis, George; Frank, Michael C. – First Language, 2020
Ambridge calls for exemplar-based accounts of language acquisition. Do modern neural networks such as transformers or word2vec -- which have been extremely successful in modern natural language processing (NLP) applications -- count? Although these models often have ample parametric complexity to store exemplars from their training data, they also…
Descriptors: Models, Language Processing, Computational Linguistics, Language Acquisition
Funda Nayir; Tamer Sari; Aras Bozkurt – Journal of Educational Technology and Online Learning, 2024
From personalized advertising to economic forecasting, artificial intelligence (AI) is becoming an increasingly important element of our daily lives. These advancements raise concerns regarding the transhumanist perspective and associated discussions in the context of technology-human interaction, as well as the influence of artificial…
Descriptors: Artificial Intelligence, Technology Uses in Education, Humanism, Capacity Building
Zhenwen Liang – ProQuest LLC, 2024
Mathematical reasoning, a fundamental aspect of human cognition, poses significant challenges for artificial intelligence (AI) systems. Despite recent advancements in natural language processing (NLP) and large language models (LLMs), AI's ability to replicate human-like reasoning, generalization, and efficiency remains an ongoing research…
Descriptors: Mathematics Skills, Thinking Skills, Abstract Reasoning, Generalizability Theory
Schuler, Kathryn D.; Kodner, Jordan; Caplan, Spencer – First Language, 2020
In 'Against Stored Abstractions,' Ambridge uses neural and computational evidence to make his case against abstract representations. He argues that storing only exemplars is more parsimonious -- why bother with abstraction when exemplar models with on-the-fly calculation can do everything abstracting models can and more -- and implies that his…
Descriptors: Language Processing, Language Acquisition, Computational Linguistics, Linguistic Theory
McClelland, James L. – First Language, 2020
Humans are sensitive to the properties of individual items, and exemplar models are useful for capturing this sensitivity. I am a proponent of an extension of exemplar-based architectures that I briefly describe. However, exemplar models are very shallow architectures in which it is necessary to stipulate a set of primitive elements that make up…
Descriptors: Models, Language Processing, Artificial Intelligence, Language Usage
Hayes-Roth, Frederick – 1980
This paper discusses the theoretical problem of matching and abstraction of concepts as the processes occur in human minds, and the structures used to represent these processes for use in automated, knowledge based systems. A basic premise of the paper is that hierarchies play a crucial role in structuring knowledge and in solving problems. Data…
Descriptors: Abstract Reasoning, Artificial Intelligence, Automation, Databases