Covers the internal components of artificial intelligence platforms (large language models, or LLMs), the data and technological systems necessary to build and deploy them, and the real-world applications, effects, and lines of philosophical inquiry around these models. Key concepts include computational knowledge representation, data and scale, computing infrastructure, opportunities and limitations posed by such models. Key threads of ethical inquiry include theory of mind, language understanding, interrogations of creativity and human relationships, and environmental justice philosophy. Provides the opportunity to learn the history of AI as situated in the history of computing and automatic translation technologies. Studies the practical capabilities and limitations of these models, explores the various contexts in which they are currently deployed, and the technological, societal, and environmental impacts of these technologies.