This post discusses the bottleneck of Chinese language data for LLM training and proposes a practical multi-source pipeline. It details how to scrape clean, structured data from key Chinese social platforms like Weibo, Bilibili, and Xiaohongshu to enrich training datasets.
The content highlights the absence of a unified API for LLM pricing across multiple providers, leading to quickly outdated comparisons. An Apify Actor is introduced as a solution to scrape and standardize this pricing data in real-time.
Strava is restricting API access and charging developers an $11.99/month subscription, blaming "zero-code AI tools" and scraping attempts for increased misuse and platform degradation. The company reported a 448% surge in developer applications this year, with API intermediaries violating policy terms.
This content introduces data scraping as an essential method for automating data collection, detailing a four-step process from identifying sources to automation. It highlights its utility with a real-world example of building a competitor analysis pipeline.