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2 clusters · 4 sources · 26 days · First seen · Last updated
Evolution of Large-Scale Artificial Intelligence Models
Overview
Research into artificial intelligence has focused on the expanding capabilities of large-scale models. Initial investigations explored the ability of Large Language Models (LLMs) to generate multibody system dynamics models from natural language descriptions. While these models can successfully generate simulation models for simple cases through zero-shot attempts, complex scenarios often result in modeling or programming errors.
The field is currently evolving from standard LLMs toward Large Multimodal Models (LMMs). These newer models integrate diverse data types, including text, images, audio, and video, allowing them to relate different forms of information within single tasks. This progression is being supported by the convergence of supervised learning, reinforcement learning, and evolutionary algorithms to solve complex computational problems.
Entities
Timeline
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[TECHNOLOGY] 2 sourcesArtificial Intelligence evolves toward Large Multimodal Models
AI is shifting from text-only LLMs to Large Multimodal Models (LMMs) that process text, images, audio, and video, while integrating reinforcement learning and evolutionary algorithms for complex tasks.
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[TECHNOLOGY] 2 sourcesLarge Language Models demonstrate ability to generate multibody models
Researchers have found that Large Language Models can generate multibody simulation models from natural language, successfully handling simple kinematic and dynamic systems.
Sources
digital.obvsg.at · diglib.uibk.ac.at · mayacomunicacion.com.mx · sg.com.mx