DeepSeek researchers have developed a technique that makes training large language models more stable. The approach uses mathematical constraints to solve a well-known problem with expanded network architectures.
Benchmarks are supposed to measure AI model performance objectively. But according to an analysis by Epoch AI, results depend heavily on how the test is run. The research organization identifies numerous variables that are rarely disclosed but significantly affect outcomes.
Harry Potter, Game of Thrones, 1984: researchers pulled nearly complete books from commercial language models. Two of the four systems tested didn’t even put up a fight. The findings could shape ongoing copyright lawsuits against AI companies.
ByteDance tackles one of AI video generation’s most persistent problems: characters that change appearance from scene to scene. The new StoryMem system remembers how characters and environments should look, keeping them consistent throughout an entire story.
If I spent more time thinking about a simple task than a complex one—and did worse on it—my boss would have some questions. But that’s exactly what’s happening with current reasoning models like Deepseek-R1. A team of researchers took a closer look at the problem and proposed theoretical laws describing how AI models should ideally ‘think.’
