Tags: data training

Artificial intelligence firms are racing to solve the long‑standing challenge of extracting reliable information from PDF documents. While PDFs dominate high‑quality data sources such as government reports and academic papers, their visual‑centric format thwarts traditional OCR and language models, leading to errors, hallucinations, and costly processing. Startups like Reducto are experimenting with multi‑stage visual models that segment pages into headers, tables, and charts before applying specialized parsers. Researchers at the Allen Institute and Hugging Face are also building dedicated PDF‑reading models, yet even the best systems still miss a small but critical portion of content. The continued proliferation of PDFs ensures the problem will persist, keeping it a hot focus for AI developers. Weiterlesen

Anthropic announced that it will begin using new Claude chat interactions and coding tasks as training data for its large language models. The shift follows an update to the company’s privacy policy slated for October 8, which will automatically include user data unless individuals explicitly opt out. Users can control the setting through a “Help improve Claude” toggle in Privacy Settings. The policy also extends data retention from 30 days to five years for all users, while commercial‑tier accounts licensed through government or educational programs remain exempt from training data collection. Weiterlesen