What’s New in AI: Large Language Model Evaluation, Robustness, and Interpretability with Nazneen Rajani

Join George Anadiotis and Nazneen Rajani, robust research lead at Hugging Face, for a discussion about one of the fastest changing and most exciting technologies in AI—large language models (LLMs)—and discover how LLMs can contribute to solving your organization's needs. LLMs have revolutionized both NLP and AI by enabling the creation of more accurate systems for understanding human speech as well as cutting-edge applications for tasks such as text processing, machine translation, and text generation. You’ll learn how to develop a framework for evaluating different LLMs, how LLMs can be used and fine-tuned effectively, and what ethical implications to consider for potential applications.

What’s New in AI gives you a chance to hear from leading minds in the field on topics such as generative AI, large language models, responsible AI, current regulations, and other developments as they appear. Host George Anadiotis, founder of Linked Data Orchestration, and members of O’Reilly’s community of experts help you make sense of the bigger picture in AI and leverage emerging AI technologies to solve your organization’s most challenging problems.

What you’ll learn and how you can apply it

• Learn about the most recent LLMs including ChatGPT, BLOOM, Anthropic’s Claude, and Google’s Bard
• Understand the capabilities and limitations of these large language models
• Develop an understanding of the criteria used to evaluate LLMs and how they apply to your setting
• Learn how to tailor LLMs to your needs

This recording of a live event is for you because…

• You’re a data scientist, machine learning engineer, machine learning architect, leader, or practitioner who designs, develops, and deploys machine learning systems.
• You want to keep up-to-date on the latest developments and breakthroughs in the field of AI.

Recommended follow-up:

• Read “Hello Transformers” (chapter 1 in Natural Language Processing with Transformers, revised edition)
• Watch Natural Language Processing Using Transformer Architectures (video)
• Read “Text Generation” (chapter 5 in Natural Language Processing with Transformers, revised edition)
• Read “Managing Bias in Machine Learning” (chapter 4 in Machine Learning for High-Risk Applications)

Please note that slides or supplemental materials are not available for download from this recording. Resources are only provided at the time of the live event.