• Securing LLMs - Addressing Privacy, Bias, and Ethical Challenges

  • Dec 17 2024
  • Length: 12 mins
  • Podcast

Securing LLMs - Addressing Privacy, Bias, and Ethical Challenges

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  • Summary

  • Explore the critical security and ethical considerations surrounding Large Language Models (LLMs) in this insightful chapter. Learn why data privacy is essential, as LLMs are trained on massive datasets that may contain sensitive information, and discover the importance of strong security measures and data governance.

    The chapter also dives into the risks of algorithmic bias and how careful data selection and model training can help mitigate it. It emphasizes the need for responsible deployment, covering issues like copyright compliance, preventing misuse, and avoiding harmful outputs such as misleading content.

    Finally, it examines the legal implications of using copyrighted material for training LLMs, with real-world examples like lawsuits against OpenAI. This guide provides a clear understanding of how to navigate the ethical and legal challenges of deploying LLMs responsibly.
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