Introduction to Generative AI Archives

Generative Artificial Intelligence: What Everyone Needs to Know by Jerry Kaplan.

Jerry holds BA in History and Philosophy of Science from the University of Chicago and PhD in Computer and Information Science (specializing in AI) from the University of Pennsylvania. He is Adjunct Lecturer at Stanford University’s Center for Democracy, Development, and the Rule of Law. Jerry co-founded GO Corporation in 1987.

This is a somewhat comprehensive guide to the very rapidly evolving field of Generative AI (Gen AI). Jerry is basically conveying GenAI may revolutionize society.

At the same time, Jerry is outlining risks and dangers associated with Gen AI including the abuse and misuse by authoritarian governments to spread disinformation and suppress dissent. Yet in the later chapters there seems to be a simplification of the ethical and societal impacts. There are also concerns that with such a respectable career, a more firm approach to AI ethics was missed.

To be fair, the AI market is so fluid today that the major competitors OpenAI, Microsoft, Google among a small handful of others, it appears somewhat challenging to forecast a market that will surly shift before the end of the year.

Introduction to Generative AI by Numa Dhamani and Maggie Engler.

Numa holds degrees in Physics and Chemistry from the University of Texas at Austin. She has served as the Principal Investigator on the United States Department of Defense’s research program. Today she is a Principal Machine Learning Engineer at Kungfu.ai.
Numa is an adjunct instructor at Georgetown University.

Maggie holds Masters in Electrical Engineering from Stanford University. She is a safety team member at Inflection AI. Previously Maggie was a Data Science Fellow at the Center for New Data and a Senior Machine Learning Engineer at Twitter. Maggie is also an adjunct instructor at the University of Texas at Austin School of Information.

Perhaps this book should be required reading for any organization’s AI planning team. Yes, your AI staff should have this well understood. However Numa and Maggie convey a grounded understanding of large language models (LLMs). In addition, you will understand the new rush for integrating generative AI (Microsoft and OpenAI) into your organizational workflows. To be fair, they also are addressing organizational benefits, risks, and limitations.