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General-purpose AI model

As explained in Introduction to Generative AI, Second Edition

A general-purpose AI model is an artificial-intelligence model capable of performing a broad range of tasks across different applications and domains.

A general-purpose AI model is designed to perform many kinds of tasks across applications and domains rather than serving one narrow function. Foundational large language models are a prominent example. section 10.30

Its broad usefulness also creates governance challenges: downstream providers need reliable information about capabilities and limitations, while powerful models may require stronger evaluation, risk mitigation, cybersecurity, and incident reporting. section 10.30

Current obligations for providers can include:

  • Summarizing training data and documenting the model. section 10.30
  • Publishing copyright-compliance policies and information for downstream integrators. section 10.30
  • Providing evaluations, risk assessments, mitigations, cybersecurity protections, and incident-reporting processes for models classified as systemic risk. section 10.30
Figure 10.7 The four risk categories in the AI Act
A pyramid of risk levels

AI-generated content may be incorrect.

Use the risk-category diagram to place general-purpose model obligations within the European Union’s wider AI risk framework. section 10.30

How Introduction to Generative AI, Second Edition covers it

How deep it goes
Explains provider obligations and systemic-risk safeguards, but stops short of model architecture or implementation.
Examples
Uses foundational large language models, chatbots, deepfakes, emotion-recognition systems, video games, and spam filters as contrasting AI applications.
What you can do after
Evaluate provider responsibilities, model limitations, and systemic-risk controls under the European Union AI framework.
How it connects
Connects general-purpose AI models with foundational models, large language models, generative AI, copyright law, and risk assessment.

Related concepts

This explainer was generated by Manning's knowledge graph from the text of Introduction to Generative AI, Second Edition. The section links point to the parts of the book it draws on.