search slide
search slide
pages bottom
Currently Browsing: Results for Tag "bias"

Lies, damned lies, and benchmarks: Futuremark responds to accusations of bias in new DirectX 12 Time Spy test

Lies, damned lies, and benchmarks: Futuremark responds to accusations of bias in new DirectX 12 Time Spy test Last week, Futuremark released Time Spy, a new DirectX 12 benchmark that takes full advantage of DX12’s features and capabilities, including asynchronous compute.Much of the confusion on this topic is related to what Time Spy tests and how it implements support for asynchronous compute in DirectX 12.

Grad Students can't finish degrees

Grad Students can't finish degrees I know you all will see an anti-trump header and thumb down because its what FJ does, but this should be concerning.I know people at MIT and its a major issue right now, it is not a political media bias.

Welp. Turns out AI learns gender and race stereotypes from humans.

Welp. Turns out AI learns gender and race stereotypes from humans. That finding, while not entirely surprising, suggests that AI might accidentally perpetuate bias instead of simply streamlining data analysis and work tasks.To reveal this troubling dynamic, the researchers used off-the-shelf AI and developed an algorithm to determine how it associated pairs of words.

FaceApp takes heat for ‘hotness’ filter that’s biased toward lighter skin tones

FaceApp takes heat for ‘hotness’ filter that’s biased toward lighter skin tones The neural network app that edits selfies is now taking a lot of heat for its “hot” filter — FaceApp recently apologized after users noticed the filter designed to make selfies look “hot” was actually lightening skin tones.After apologizing to users, FaceApp changed the name of the filter to “spark,” and the app says a complete fix is currently in progress.

Study suggests gender bias exists in open-source programming

Study suggests gender bias exists in open-source programming Evidence that gender bias exists in the field of computer science has emerged in the form of a new study examining acceptance rates of contributions from men and women in an open-source software community.The study’s findings indicated that women’s contributions were rejected more often, but only if their gender is identifiable.