The Atlantic – And that could change everything for the tech industry. Alex Reisner: “On Tuesday, researchers at Stanford and Yale revealed something that AI companies would prefer to keep hidden. Four popular large language models—OpenAI’s GPT, Anthropic’s Claude, Google’s Gemini, and xAI’s Grok—have stored large portions of some of the books they’ve been trained on, and can reproduce long excerpts from those books. In fact, when prompted strategically by researchers, Claude delivered the near-complete text of Harry Potter and the Sorcerer’s Stone, The Great Gatsby, 1984, and Frankenstein, in addition to thousands of words from books including The Hunger Games and The Catcher in the Rye. Varying amounts of these books were also reproduced by the other three models. Thirteen books were tested. This phenomenon has been called “memorization,” and AI companies have long denied that it happens on a large scale. In a 2023 letter to the U.S. Copyright Office, OpenAI said that “models do not store copies of the information that they learn from.” Google similarly told the Copyright Office that “there is no copy of the training data—whether text, images, or other formats—present in the model itself.” Anthropic, Meta, Microsoft, and others have made similar claims. (None of the AI companies mentioned in this article agreed to my requests for interviews.) The Stanford study proves that there are such copies in AI models, and it is just the latest of several studies to do so. In my own investigations, I’ve found that image-based models can reproduce some of the art and photographs they’re trained on. This may be a massive legal liability for AI companies—one that could potentially cost the industry billions of dollars in copyright-infringement judgments, and lead products to be taken off the market. It also contradicts the basic explanation given by the AI industry for how its technology works. AI is frequently explained in terms of metaphor; tech companies like to say that their products learn, that LLMs have, for example, developed an understanding of English writing without explicitly being told the rules of English grammar. This new research, along with several other studies from the past two years, undermines that metaphor. AI does not absorb information like a human mind does. Instead, it stores information and accesses it. In fact, many AI developers use a more technically accurate term when talking about these models: lossy compression. It’s beginning to gain traction outside the industry too. The phrase was recently invoked by a court in Germany that ruled against OpenAI in a case brought by GEMA, a music-licensing organization. GEMA showed that ChatGPT could output close imitations of song lyrics. The judge compared the model to MP3 and JPEG files, which store your music and photos in files that are smaller than the raw, uncompressed originals. When you store a high-quality photo as a JPEG, for example, the result is a somewhat lower-quality photo, in some cases with blurring or visual artifacts added. A lossy-compression algorithm still stores the photo, but it’s an approximation rather than the exact file. It’s called lossy compression because some of the data are lost…”