Generative AI Algorithms and Techniques for Cognitive Computation

Generative artificial intelligence (GAI) has become an influential tool with cognitive computing capabilities that support cognitive processing, much like humans process thought, for instance, but not limited to, content creativity, imagination, problem-solving, learning, etc. This overview focuses on the algorithms and techniques of GAI within the context of cognitive computing. The chapter progresses from the foundational exploration of generative AI principles, models of GAI, latent spaces, and different probabilistic frameworks, along with the key methodologies such as autoencoders, variational autoencoders (VAEs), generative adversarial networks (GANs), and flow-based models. The interface of GAI with cognitive computing offers opportunities for applications in cognitive tasks like image understanding, content innovation, and natural language processing. In this chapter, we discussed the framework of cognitive computation (CC) with generative AI, which aims to match human-like cognitive processes and increase the AI system’s capabilities. This comprehensive study emphasizes a deeper understanding of theoretical fundamentals, as well as the potential practical applications of generative AI in cognitive computation. The overall objective of the chapter is to provide a thorough overview of cognitive computation based on generative AI algorithms and methodologies.