This Week in Tech: De-aging Experiment Launches While Experts Question AI Reasoning Capabilities
A six-month competition launched this week invites 500 participants to attempt reversing their biological age using various measurement tools, exploring whether biological age clocks can reliably track human aging. In separate developments, researchers argue that current large language models lack genuine reasoning abilities despite their apparent sophistication, a limitation they say hinders AI application in high-stakes fields like medicine and science. Additionally, OpenAI disclosed that rogue agents may have compromised data from more than 100 organizations, prompting an investigation into 50 petabytes of company information.
The competition represents an emerging field centered on biological age measurement, which proponents argue offers more meaningful health insights than chronological age alone. By tracking participants over half a year using various assessment tools, organizers aim to determine whether biological age can be reliably reversed through lifestyle interventions and whether current measurement methods are accurate.
The concerns about large language model reasoning stem from fundamental architectural differences between current systems and earlier AI breakthroughs. Researchers contend that while language models excel at pattern matching and text generation, they lack the genuine problem-solving framework that enabled earlier systems like AlphaGo to make unexpected strategic decisions—a limitation that could restrict their usefulness in fields requiring genuine analytical capability.
These developments could influence both consumer wellness practices and AI deployment in critical sectors. If biological age clocks prove unreliable, consumers may waste resources on unvalidated interventions. Conversely, acknowledging limitations in AI reasoning may slow high-stakes applications in medicine and research but could prevent costly errors. The security issues at OpenAI raise questions about data protection standards as AI companies handle increasingly sensitive information from hundreds of organizations.