Arthur T Knackerbracket has found the following story:
MIT researchers have built a system that fools natural-language processing systems by swapping words with synonyms:
The software, developed by a team at MIT, looks for the words in a sentence that are most important to an NLP classifier and replaces them with a synonym that a human would find natural. For example, changing the sentence "The characters, cast in impossibly contrived situations, are totally estranged from reality" to "The characters, cast in impossibly engineered circumstances, are fully estranged from reality" makes no real difference to how we read it. But the tweaks made an AI interpret the sentences completely differently.
The results of this adversarial machine learning attack are impressive:
For example, Google's powerful BERT neural net was worse by a factor of five to seven at identifying whether reviews on Yelp were positive or negative.
The paper:
-- submitted from IRC
(Score: 0) by Anonymous Coward on Wednesday April 29 2020, @03:28PM (3 children)
It sounds like a dodgy New Zealand accent.
(Score: 2) by DannyB on Wednesday April 29 2020, @04:34PM (2 children)
It's still fun when trapped at home in times of emergent seas.
The lower I set my standards the more accomplishments I have.
(Score: 1, Funny) by Anonymous Coward on Wednesday April 29 2020, @06:19PM (1 child)
Shhh, you can't talk about rising sea levels.
Folks get all gun-totin' when you mention climate change.
(Score: 2) by DannyB on Wednesday April 29 2020, @08:42PM
Rising C levels demand more efishient compilers. More efishency is wanted for every porpoise.
The lower I set my standards the more accomplishments I have.