The Hidden Cost of Low-Quality Training Data
Cheap data isn't free. Models trained on noisy web scrapes spend more compute on cleanup, produce weaker outputs, and require expensive fine-tuning to fix.
March 28, 2026
Blog
Cheap data isn't free. Models trained on noisy web scrapes spend more compute on cleanup, produce weaker outputs, and require expensive fine-tuning to fix.
March 28, 2026
Not every book collection is useful for AI training. Format, metadata, deduplication, and category diversity all determine whether a catalog creates value or headaches.
March 22, 2026
Web-scraped text is abundant but noisy. Books offer something rarer: edited, intentional, long-form human thought at scale.
March 15, 2026
Web scraping built the first generation of LLMs. But the limitations are showing, and the most serious AI teams are diversifying their data sourcing strategies.
March 8, 2026
The foundation model companies betting big on book data aren't doing it by accident. Here's what the research says and why the supply chain matters.
February 28, 2026
Model capability is shaped by training data composition. Here's what we've learned about how category mix, era coverage, and linguistic variety affect outcomes.
February 15, 2026
The most valuable training data is often the hardest to find. Rare and out-of-print titles give AI models access to knowledge that exists nowhere else in digital form.
February 1, 2026