Lecture
This lecture presents a review paper on Neuroscience Inspired Artificial Intelligence, exploring the intertwined relationship between neuroscience and AI disciplines. It covers the historical development of deep learning, reinforcement learning, attention mechanisms, episodic memory, working memory, and continual learning. The lecture delves into how concepts from neuroscience have inspired AI algorithms, such as attention mechanisms for object classification tasks and the integration of episodic memory to enhance reinforcement learning. It also discusses the importance of dopamine in reward prediction error and the role of working memory in AI architectures. The presentation highlights the ongoing influence of neuroscience concepts on AI research, emphasizing the foundational inspiration derived from biological neural networks.