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Foundation model

Artificial intelligence model paradigm

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📌 Topics

  • Artificial Intelligence (1)
  • Health Technology (1)
  • Knowledge Transfer (1)
  • AI governance (1)
  • Model evaluation (1)
  • Research methodology (1)

🏷️ Keywords

Foundation models (2) · BioX-Bridge (1) · Biosignals (1) · Cross-modal knowledge transfer (1) · Unsupervised learning (1) · Health monitoring (1) · Machine learning efficiency (1) · Parameter reduction (1) · AI model uniqueness (1) · In-Silico Quasi-Experimental Design (1) · AI governance (1) · Model auditing (1) · Functional redundancy (1) · Heterogeneous AI ecosystems (1)

📖 Key Information

In artificial intelligence, a foundation model (FM), also known as large x model (LxM, where "x" is a variable representing any text, image, sound, etc.), is a machine learning or deep learning model trained on vast datasets so that it can be applied across a wide range of use cases. Generative AI applications like large language models (LLM) are common examples of foundation models. Building foundation models is often highly resource-intensive, with the most advanced models costing hundreds of millions of dollars to cover the expenses of acquiring, curating, and processing massive datasets, as well as the compute power required for training.

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Health and usage monitoring systems(1)Biosignal(1)Unsupervised learning(1)Functional equivalence (ecology)(1)Regulation of artificial intelligence(1)Foundation model

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