A.i gay sex

By Nouran Sakr

Algorithm Achieves Higher Accuracy Rates than Humans

A study from Stanford University suggests that a intense neural network (DNN) can distinguish between gay and direct people, with 81 per cent accuracy in men and 71 per cent in women. The research was based on a sample of 35,326 facial images of light men and women that were posted publicly on a US dating website. The DNN, a machine learning system, was presented with pairs of images, where one individual was gay and the other was straight.

The DNN’s algorithm displayed even higher accuracy rates when presented with five facial images per person: 91 per cent in men and 83 per cent accuracy in women. Human judges, when presented with one image, achieved a much drop accuracy rate: 61 per cent for men and 54 per cent for women.

According to the research, there were certain trends in facial features that distinguished between lgbtq+ and straight people. Narrower jaws, larger foreheads, and longer noses were frequent among gay men, while gay women were more likely to have smaller foreheads and wider jaws.

The authors of the report, Yilun Wang and Michal Kosinski, concluded that homosexual men and women have more andr