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Scraping

As explained in Introduction to Generative AI, Second Edition

Web scraping is the automated retrieval and extraction of content from web pages or websites.

Web scraping is the programmatic retrieval and copying of content from web pages. It lets people gather text and images for datasets used to train and test artificial intelligence models. section 4.12

Publicly available content has often been treated as legally scrapeable, but licenses still govern code and data. Website owners can publish robots.txt instructions, although malicious programs may ignore them. section 4.12

Data sources and stale recommendations

ImageNet was assembled from internet images and human labels. Search-engine bots scrape indexed websites, while Reddit, Twitter, and Stack Overflow have negotiated data-access deals. A later AI recommendation to put glue on pizza reportedly traced back to an 11-year-old Reddit comment, illustrating the risks of scraped, outdated sources. section 4.12

How Introduction to Generative AI, Second Edition covers it

How deep it goes
Defines scraping and sketches its legal, commercial, licensing, and robots.txt dimensions without implementation detail.
Examples
Uses ImageNet, search-engine bots, Reddit, Twitter, Stack Overflow, and an outdated Reddit recommendation as examples.
What you can do after
Evaluate scraped web data as a dataset source while considering public availability, licenses, bot instructions, and source freshness.
How it connects
Connects scraping with datasets, artificial intelligence training, search engines, data licenses, and robots.txt.

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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.