Fighting Fake News and Deep Fakes with Machine Learning w/ Delip Rao - TWiML Talk #260
Analysis
This article introduces a podcast episode featuring Delip Rao, a prominent figure in AI research. The discussion centers on the use of machine learning to combat the spread of fake news and deepfakes. The conversation covers the creation and identification of artificial content across text, video, and audio formats. It highlights the challenges in each modality, the role of Generative Adversarial Networks (GANs), and potential solutions. The focus is on the technical aspects of detecting and generating synthetic media.
Key Takeaways
- •The podcast episode focuses on the use of machine learning to combat fake news and deepfakes.
- •The discussion covers the generation and detection of artificial content across different media formats.
- •The role of GANs and the challenges in each modality are key topics of the conversation.
“In our conversation, we discuss the generation and detection of artificial content, including “fake news” and “deep fakes,” the state of generation and detection for text, video, and audio, the key challenges in each of these modalities, the role of GANs on both sides of the equation, and other potential solutio”