DETECTING FAKE NEWS
Online disinformation, or fake news intended to deceive, has emerged as a major societal problem. Currently, fake news articles are written by humans, but recently-introduced AI technology based on Neural Networks might enable adversaries to generate fake news. Our goal is to reliably detect this “neural fake news” so that its harm can be minimized.
To study and detect neural fake news, we built a model named Grover. Our study presents a surprising result: the best way to detect neural fake news is to use a model that is also a generator.
Learn more and try Grover by clicking the link below.
https://t.me/ai_python_en/1416
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AI, Python, Cognitive Neuroscience The Enigma of Neural Text Degeneration as the First Defense Against Neural Fake News If you want a sneek-peek in Yejin Choinka,and co-workers work on GROVER (a 1.5 billion param GPT-2-like model), check this live tweet 👇 Interesting hints, results, and analysis!…