May 1, 2024
Updated May 9, 2025
26 minute read
Generative Artificial Intelligence, often abbreviated as Generative AI, GenAI, or GAI, is a fascinating and rapidly evolving subfield of artificial intelligence. At its core, Generative AI focuses on creating new, original content. This content can take many forms, including text, images, audio, video, and even code. These sophisticated systems learn the underlying patterns and structures from vast amounts of data they are trained on. They then use this learned knowledge to produce novel outputs based on user-provided instructions, which are often in natural language and are commonly referred to as "prompts."
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Find a path to becoming a Generative AI. Learn more at:
OpenCourser.com/topic/ootr17/generative
Reading list
We've selected ten books
that we think will supplement your
learning. Use these to
develop background knowledge, enrich your coursework, and gain a
deeper understanding of the topics covered in
Generative AI.
Provides a practical guide to using generative AI, covering the different techniques and tools available. It is written by two leading experts in the field, Josh Patterson and Adam Gibson.
Provides a business-oriented perspective on generative AI, discussing its potential impact on industries and how companies can use it to gain a competitive advantage. It is written by three leading experts in the field, Thomas Davenport, Rajeev Ronanki, and Nitin Mittal.
Provides a thought-provoking exploration of the future of generative AI, discussing its potential benefits and risks. It is written by Gary Marcus, a leading researcher in the field.
Explores the relationship between generative AI and the creative process, discussing how generative AI can be used to enhance creativity. It is written by Margaret Boden, a leading researcher in the field.
Explores the potential applications of generative AI in healthcare, discussing how it could be used to improve patient care and accelerate drug discovery. It is written by Eric Topol, a leading researcher in the field.
Explores the philosophical implications of generative AI, discussing how it challenges our understanding of mind and consciousness. It is written by Daniel C. Dennett, a leading philosopher in the field.
Explores the potential applications of generative AI in climate change, discussing how it could be used to model climate change and develop solutions. It is written by Andrew Ng, a leading researcher in the field.
Explores the potential impact of generative AI on the law, discussing how it could be used to automate legal processes and improve access to justice. It is written by Ryan Abbott, a leading researcher in the field.
Explores the potential impact of generative AI on the economy, discussing how it could be used to create new jobs and improve productivity. It is written by two leading experts in the field, Erik Brynjolfsson and Andrew McAfee.
Explores the potential impact of generative AI on society, discussing how it could be used to solve social problems and improve quality of life. It is written by Kai-Fu Lee, a leading researcher in the field.
For more information about how these books relate to this course, visit:
OpenCourser.com/topic/ootr17/generative
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