Lean in on Generative AI: Latest Trends and Developments

The advent of generative artificial intelligence (Gen AI) has revolutionized content development and infiltrated various industries. Gen AI engines use large language models (LLM) created by ‘reading’ digital content, such as images, text, and audio files, and detecting patterns and relationships therein. While generative AI technologies have emerged as powerful, innovative tools, there has been a solid backlash from the creative community and copyright holders about using their works as Gen AI training data without permission. Copyright holders have reverted to litigation, leaving the courts to wrestle with the legal difficulty of whether using unlicensed copyrighted works as AI training material constitutes copyright infringement. Meanwhile, the AI community is trending toward developing open-source AI models and smaller, focus-driven models. Training data for these AI models are specifically curated.

This panel presentation will address:

1.) How open-source AI models are being engineered/generated
2.) Legal risks involved with leveraging generative AI systems
3.) The rise of GenAI copyright traps
4.) GenAI governance, compliance, and management challenges
5.) Advantages of scalable, domain-driven AI models
6.) Risks and benefits of widespread use of generative AI source code in the open-source software domain
7.) Open source vs. proprietary LLMs
8.) Navigating the curation of specific focus training data sets in the face of copyright protected data