Artificial intelligence

As explained in Data Storytelling with Altair and AI

Artificial intelligence is the field of computing concerned with systems that perform tasks requiring capabilities associated with human intelligence.

Artificial intelligence (AI) is the discipline of building intelligent agents that can reason, learn, and make decisions independently. It aims to emulate human-like thinking and behavior. In data storytelling, AI provides the broader context for understanding generative AI tools, while responsible use keeps human judgment involved rather than treating automation as a replacement. section 4.1.1 section 4.1

Figure 4.1 The main subfields of AI, with a focus on generative AI

The hierarchy places generative AI inside deep learning, deep learning inside machine learning, and machine learning inside artificial intelligence. section 4.1.1

AI in a data story

A data storyteller can use ChatGPT to generate text, DALL-E to generate images, and GitHub Copilot to turn described coding steps into runnable code. Together, these tools can accelerate the construction of a data story while leaving direction and judgment with the creator. section 4.0 section 1.2

How Data Storytelling with Altair and AI covers it

How deep it goes

Defines intelligent agents and maps AI’s subfields, but stops short of detailed AI fundamentals or implementation internals.

Examples

Uses ChatGPT for text, DALL-E for images, and GitHub Copilot for code within data-storytelling work.

What it assumes

Builds the AI-to-generative-AI hierarchy from basic concepts before introducing specific tools.

What you can do after

Apply it by situating generative AI tools within the wider AI hierarchy and data-storytelling workflow.

How it connects

Connects artificial intelligence to machine learning, deep learning, generative AI, and data storytelling.

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Related concepts

• machine learningincludes · Machine learning is a field of computational methods in which systems learn patterns or relationships from data to make predictions, decisions, or other outputs.
• code reviewuses · Code review is the systematic examination of source code or proposed changes to identify problems and assess or improve quality.
• large language modelincludes · A large language model is a machine-learning model, typically neural, trained on extensive text data to process and generate language.
• dependencykind of · A software dependency is a component, resource, or prerequisite on which another software component or operation relies to function or proceed.
• generative modelingincludes · Generative modeling is a machine-learning approach that learns patterns or a data distribution to generate new samples resembling the data.
• language modelincludes · A language model is a computational model that represents patterns in linguistic tokens to estimate sequence probabilities and predict or generate language from context.

This explainer was generated by Manning's knowledge graph from the text of Data Storytelling with Altair and AI. The section links point to the parts of the book it draws on.