Neuroscientist Daeyeol Lee discusses different modes of reinforcement learning in humans and animals, AI and natural intelligence, and future directions of research.
In his book, "The Myth of Artificial Intelligence," computer scientist Erik Larson discusses how widely publicized misconceptions have led AI research down narrow paths that are limiting innovation and scientific discoveries.
Harvard Medical University Professor Gabriel Kreiman discusses biological and computer vision and explains what separates current AI systems from the human visual cortex.
AI will transform our world and the businesses leading the future, but only if it is easily accessible to everyone
Neuroscience-inspired deep learning architectures are more resilient to adversarial attacks, researchers at MIT and IBM have found.
The Self-Assembling Brain, a book by neurobiology professor Peter Robin Hiesinger, sheds light on a largely ignored aspect of intelligence.
DARPA's XAI initiative aims to shed light inside the black box of artificial intelligence algorithms. Project Manager Dave Gunning explains how the agency is working to create explainable AI tools that will build trust and reliability into AI models.
Cerebras CEO Andrew Feldman discusses the hardware challenges of LLMs and his vision to reduce the costs and complexity of training and running large neural networks.
In his book Augmented Mind, Alex Bates argues that the real opportunities of AI lie in augmenting humans, not replacing them.