Communications of the ACM
Innovation Is Overrated: A Provocation
Digital innovation is not working in the interest of the whole of society. It is time to radically rethink its purpose without…
From ACM Opinion
Yoshua Bengio: The Past, Present, and Future of Deep Learning
2018 ACM A.M. Turing Award recipient discusses his career, collaborations, deep learning's promise, and directions for the field.
From ACM Opinion
Linguistics and the Development of NLP
An interview with Christopher Manning, director of the Stanford University AI Lab and an associate director of Stanford's Human-Centered Artificial Intelligence...
From ACM Opinion
Interpretable Machine Learning
A conversation with Been Kim, staff research scientist at Google Brain.
From ACM Opinion
Connecting Large Language Models to Human Values
AI researcher Connor Leahy talks about replicating GPT-2/GPT-3, superhuman AI, AI alignment, AI risk and research norms, and more
From ACM Opinion
Machine-Learning Robustness, Foundation Models, and Reproducibility
An interview with Percy Liang, associate professor of Computer Science at Stanford University
From ACM Opinion
Self-Supervised Learning and Large Language Models
Stanford PhD student discusses recent research on understanding, building, and controlling pre-trained models
From ACM Opinion
Strong AI Requires Autonomous Building of Composable Models
Models built by AI must encode the fundamental patterns of experience
From ACM Opinion
Meta Learning and Model-Based Reinforcement Learning
Stanford professor Chelsea Finn talks about robotics and meta learning research
From ACM Opinion
The Imperative for Sustainable AI Systems
The impact of AI's massive carbon footprint is social, not just environmental
From ACM Opinion