Responsible AI is paramount in the realm of machine learning, especially with the growing call for AI regulation. This series addresses the practical needs of organizations and AI developers, offering hands-on learning to identify, debug, and mitigate issues associated with AI solutions. By leveraging both LLMs and traditional ML models, you’ll gain valuable insights to navigate the complexities of building AI solutions responsibly.

Gain a strategic advantage by minimizing risks associated with your AI services, earning the trust of investors, B2B customers, and end users. This session equips you to address regulatory compliance concerns and showcases responsible AI practices crucial for success in the evolving AI landscape.

What attendees will learn
Participants, whether individuals or startup teams, will acquire best practices in utilizing vectors, prompt engineering, and identifying harmful AI issues such as biases, jailbreaks, hallucinations, and offensive content.

Prerequisite:
Basic understanding of Python is recommended.