, University of Massachusetts, Amherst, MA
This talk dissected the complex dynamics of open-source Large Language Models, emphasizing their power to democratize AI and drive innovation against the backdrop of ethical challenges. The talk outlined strategies for harnessing the benefits of open-source LLMs while addressing critical concerns like bias and privacy, aiming for a responsible AI future.
Webinar, DataHour by Analytics Vidhya, Virtual
Conference proceedings talk, Testing Institute of America 2014 Annual Conference, Los Angeles, CA
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Talk, London School of Testing, London, UK
Tutorial, UC-Berkeley Institute for Testing Science, Berkeley, CA, USA
Talk, UC San Francisco, Department of Testing, San Francisco, CA, USA
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