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8 results for "GPT"
ZG_5_01 — Computational Linguistics and NLP
Computational linguistics (CL) and natural language processing (NLP) are the interdisciplinary fields concerned with enabling computers to process, analyze, understand, and generate human language. CL originated in the 1
ZD_2_15 — Transformer Architecture: Self-Attention and the Foundation of Modern AI
The transformer is a neural network architecture introduced in 2017 that replaced recurrent and convolutional models as the dominant paradigm in artificial intelligence. Its core innovation — the self-attention mechanism
ZD_2_03 — Natural Language Processing
Natural language processing (NLP) — the computational analysis, understanding, and generation of human language — spans rule-based, statistical, and neural approaches across tasks including machine translation, text clas
ZD_2_07 — Artificial General Intelligence — Architectures and Challenges
Artificial General Intelligence (AGI) — a hypothetical AI system capable of performing any intellectual task that a human can, with the same flexibility, generality, and ability to learn and transfer knowledge across dom
ZD_2_12 — Generative AI: Large Language Models, Diffusion, and the Transformer Revolution
Generative AI refers to artificial intelligence systems capable of creating new content — text, images, audio, video, code, 3D models — that is novel, coherent, and often indistinguishable from human-created work. The fi
S_1_16 — Large Language Models: Architecture, Capabilities, and Societal Impact
Large Language Models (LLMs) are neural networks with billions to trillions of parameters, trained on massive text corpora to predict the next token in a sequence. Built on the transformer architecture introduced by Vasw
S_1_01 — Artificial General Intelligence and Existential Risk
Artificial General Intelligence — a system with human-level or greater cognitive capabilities across ALL domains — may be the most consequential invention in human history. Current foundational AI systems (GPT-4, Claude,
S_1_11 — Machine Learning and Deep Learning
Machine learning (ML) is the subfield of AI in which systems learn patterns from data rather than being explicitly programmed. Deep learning uses artificial neural networks with many layers (hence "deep") to learn hierar
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