With the rapid spread of digital content, doctored videos pose growing risks across media, security, and legal domains. A new study published in The Journal of Engineering Research introduces an automated approach to detect interpolated frames—artificially inserted images used to smooth manipulated video sequences and make them appear authentic.

University of Washington researchers developed the first system that incorporates tiny cameras in off-the-shelf wireless earbuds to allow users to talk with an AI model about the scene in front of them. For instance, a user might turn to a Korean food package and say, "Hey Vue, translate this for me." They'd then hear an AI voice say, "The visible text translates to 'Cold Noodles' in English."

Perfect AI alignment with human values and interests is mathematically impossible, according to a study, but behavioral diversity among AI agents offers the promise of some control. Published in PNAS Nexus, Hector Zenil and colleagues used Gödel's incompleteness theorem and Turing's undecidability result for the Halting Problem to show that any LLM complex enough to exhibit general intelligence or superintelligence will also be computationally irreducible and produce unpredictable behavior, making forced alignment impossible.

Alumna, author and machine learning expert Vivienne Ming explains why the best defense against AI's downsides is investing in human skills—and using the technology inquisitively, not passively.

What if ChatGPT answered with the name of a minister from a year ago when asked, "Who was the minister inaugurated last month?" This is a prime example of the limitations of AI that fails to properly reflect the latest information. A KAIST research team has developed a new evaluation technology that automatically reflects changing real-world information while catching "temporal errors" that may appear correct on the surface. This is expected to drastically improve AI reliability.