Many large tech companies are competing to develop general-purpose artificial intelligence (AI) -- allowing their model to approach and solve just about any problem we give them, no matter how time-consuming or challenging. This is referred to as the alignment problem. To test out and scale a potential solution, the OpenAI team recently trained an artificial intelligence model to recursively summarize books. Using natural language processing through GPT-3 can get you the gist of a book of any length. According to the OpenAI team, the model "achieves a 6/7 rating (similar to the average human-written summary) from humans who have read the book 5% of the time and a 5/7 rating 15% of the time."

The Transform Technology Summits start October 13th with Low-Code/No Code: Enabling Enterprise Agility. OpenAI has developed an AI model that can summarize books of arbitrary length. A fine-tuned version of the research lab's GPT-3, the model works by first summarizing small sections of a book and then summarizing those summaries into higher-level summaries, following a paradigm OpenAI calls "recursive task decomposition." Summarizing book-length documents could be valuable in the enterprise, particularly for documentation-heavy industries like software development. A survey by SearchYourCloud found that workers take up to eight searches to find the right document, and McKinsey reports that employees spend 1.8 hours every day -- 9.3 hours per week, on average -- searching and gathering job-related information.