In this episode of ThinkFuture, host Chris Kalaboukis sits down with AI expert Aman to break down the reality of large language models (LLMs) and what they mean for data privacy. They discuss how LLMs, despite their impressive reasoning abilities, are just sophisticated "next word prediction" systems trained on vast amounts of online content—often without permission or compensation.The conversation dives into the thorny issues of data ownership, with Aman highlighting how while individuals may not care much about their personal data being used, corporations and regulators are growing increasingly wary of AI’s privacy implications. They explore whether content creators should be compensated for AI-generated outputs based on their work and the evolving legal landscape.Chris and Aman also compare different AI models, including GPT-3, Chinchilla, and Claude, breaking down their strengths, weaknesses, and how newer models are pushing past their predecessors. Looking ahead to 2035, Aman envisions personal AI privacy agents that will help users control their digital footprint while ensuring they get credited and paid for their contributions to AI training datasets. But will privacy ever truly be protected in the age of AI? Tune in to find out!---The First Future Planner: Record First, Action Later: https://foremark.usBe A Better YOU with AI: Join The Community: ⁠https://10xyou.us⁠Get AIDAILY every weekday. ⁠https://aidaily.us⁠My blog: ⁠https://thinkfuture.com

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