An in-depth analysis of web-page boilerplate detection algorithms, their evolution from simple text heuristics to visual rendering, and their critical role in both Search Engine Indexing and Large Language Model training.
Read more →An analysis of how Large Language Models ingest and utilize structured data during pre-training, moving beyond ’text-only’ ingestion to understanding the semantic backbone of the intelligent web.
Read more →In the early days of the web, we were told to use Semantic HTML for accessibility. We were told it allowed screen readers to navigate our content, providing a better experience for the visually impaired. We were told it might help SEO, though Google’s engineers were always famously coy about whether an <article> tag carried significantly more weight than a well-placed <div>.
In 2025, that game has changed entirely. We are no longer just optimizing for screen readers or the ten blue links on a search results page. We are optimizing for the training sets of Large Language Models (LLMs).