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Generative AI Could Power the Next Wave of Self-Driving Cars

The advancements in AI are driving a new phase in autonomous vehicle (AV) development, termed "AV 2.0," aiming for a faster and cost-effective way to teach robots to drive. Companies like Waabi and Wayve are using AI for intuitive learning, making rapid progress with significant investments. Despite advancements, AI in AVs still faces challenges in ensuring safety and reliability.

Lawmakers Address Deepfake AI Porn Boom with New Bill

Lawmakers are introducing the "Take It Down Act," aiming to hold social media companies accountable for removing deepfake pornographic images. Sponsored by Sen. Ted Cruz, the bill mandates platforms remove such images within 48 hours of a victim's request and make efforts to delete other copies. The Federal Trade Commission will enforce the rules. The bill seeks to protect victims, including celebrities and high school students, from non-consensual AI-generated images. While there is bipartisan support for action, two competing Senate bills propose different approaches to address the issue.

Google DeepMind Unveils AI Tech to Generate Video Soundtracks

Google DeepMind's new AI tech generates soundtracks for videos. This AI, designed to enhance video experiences, uses machine learning to create music that matches the video's mood and context. This innovation aims to streamline the process for content creators, potentially revolutionizing how soundtracks are produced for various multimedia projects.

Why Artists Are Becoming Less Afraid of AI

Artists are becoming less fearful of AI as they realize its limitations and potential benefits. AI can help with initial drafts and structuring, but it struggles to produce original, stimulating, and funny content. With increasing awareness of data-scraping practices and copyright concerns, artists are leveraging AI to augment creativity while ensuring ethical use.

Why Does AI Hallucinate?

AI chatbots often generate incorrect information, known as "hallucinations," because they predict words based on statistical patterns from large datasets rather than retrieving factual data. Techniques like training on more data and chain-of-thought prompting can improve accuracy, but errors are inevitable due to the probabilistic nature of these models.

Keep HILT

Human-in-the-loop (HILT) and reinforcement learning from human feedback (RLHF) are essential for AI safety and reliability. HILT involves human oversight to correct AI errors, while RLHF helps AI learn from human feedback. This combination ensures accurate decision-making in high-stakes areas like security, balancing automation with human judgment to mitigate risks.