Foundational model

As explained in The Art of AI Product Development

A foundational model is a broadly trained model that can be adapted to support many downstream tasks and applications.

How The Art of AI Product Development covers it

How deep it goes

Defines adaptation and integration at a practical level, while stopping short of model-training internals or fine-grained optimization.

Examples

Uses prompts, AI-powered applications, production workflows, and unstructured-data pipelines as practical applications.

What you can do after

Apply it via pretrained models, prompts, APIs, and integrated AI workflows in production applications.

How it connects

Connects foundational models with prompt engineering, AI engineering, machine learning engineering, MLOps, and data engineering.

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Also explained in

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  Inside Deep Learning: Math, Algorithms, ModelsA model whose parameters were fitted on a source task or dataset before reuse.
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  Deep Learning with Python, Third EditionA model trained beforehand on large-scale data and then reused for downstream tasks or analysis without starting from scratch.
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  Deep Learning with R, Third EditionA foundation model is a large pretrained model intended to support many downstream tasks with little or no task-specific retraining.
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  AI-Powered SearchA pretrained model is a model that has already been trained on general data before adaptation to a particular task or domain.
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  Generative AI in ActionA pretrained model is a machine-learning model that has already been trained on an initial dataset before being adapted to another task or dataset.
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  Time Series Forecasting Using Foundation ModelsA foundation model is a machine learning model trained on large, diverse data and applicable to a wide variety of tasks, often through adaptation or fine-tuning.
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  Deep Learning with PyTorch, Second EditionA neural network already trained on prior data and reused for inference or further training.
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  Machine Learning System DesignA machine learning model whose parameters were learned previously on a dataset or task before being applied or adapted to another task.
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  Delivering Machine Learning Projects: From design to deploymentA foundation model is a broadly trained machine learning model that can be adapted to support multiple downstream tasks.
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  LLMs in ProductionA foundation model is a broadly pretrained model that can be adapted to multiple downstream tasks or domains.
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  How Large Language Models WorkA foundation model is a broadly trained model that can be adapted or used as a basis for many applications.
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  Hugging Face in ActionA pretrained model is a machine learning model whose parameters have already been learned from a training dataset before being adapted or used for a particular task.
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  Effective Data AnalysisA foundation model is a broadly pretrained model that can be adapted or prompted for many downstream tasks and domains.
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  The AI Pocket BookA preexisting model used as-is or with minimal adaptation instead of building one from scratch.
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  Reinforcement Learning from Human FeedbackA foundation model is a broadly pretrained model that can be adapted to support multiple downstream tasks.
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  Software Testing with Generative AIA foundational model is a pretrained machine-learning model that provides a general base for further adaptation or specialization.
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  Natural Language Processing in Action, Second EditionA pretrained model is a model whose parameters were previously learned from a separate training corpus or task.
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  Transformers in ActionA pretrained model is a machine-learning model whose parameters have already been learned from a broad training corpus before adaptation to a specific task.
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  Deep Learning with JAXA model that has already been trained on a large corpus and can be reused directly or adapted to a new task.
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  Financial AI in PracticeA foundation model is a large, broadly trained model that can be adapted or guided for many downstream tasks.

Compare how 21 books explain foundational model →

Related concepts

• language modelkind of · A language model is a computational model that represents patterns in linguistic tokens to estimate sequence probabilities and predict or generate language from context.
• pretrained modelkind of · A pretrained model is a machine-learning model whose parameters were learned through prior training before it is used or adapted for a subsequent task.
• feature engineeringused by · Feature engineering is the creation, transformation, or selection of input features from data to provide useful representations for analysis or modeling.
• TimesFMincludes · TimesFM is a foundation model designed for deterministic time-series forecasting.
• instruct modelincludes · An instruction-tuned model is a pretrained model further trained to follow natural-language instructions and produce task-appropriate responses.

This explainer was generated by Manning's knowledge graph from the text of The Art of AI Product Development. The section links point to the parts of the book it draws on.