Building Web Scraping Architecture for AI Companies

According to Fei-Fei Li, godmother of AI, data is critical for learning. And good AI models require good data. The quality and quantity of training data directly impact the model's performance and accuracy. In AI training, quantity has a quality of its own, improving inference when provided with more volume.

Web data drives AI development

The World Wide Web is by far the largest source of multimodal data for AI applications. This white paper introduces web scraping as a means of sourcing AI training data.

We hope the architecture provided in this paper will help enter the world of large-scale web data collection. Completing the actions of the data extraction architecture will grant software that efficiently collects structured data for AI training without IP timeouts.

The presented tools and methods are for collecting publicly available web data that is not protected by login credentials and falls under the terms of fair use.