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Yoshua Bengio: The Past, Present, and Future of Deep Learning
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.

Open-Endedness and Evolution through Large Models
From ACM Opinion

Open-Endedness and Evolution through Large Models

A conversation with Joel Lehman, machine-learning scientist formerly of OpenAI and Uber AI Labs.

Linguistics and the Development of NLP
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...

Teaching Robots to Help People in Their Everyday Lives
From ACM Opinion

Teaching Robots to Help People in Their Everyday Lives

An interview with Max Braun of Everyday Robots.

Connecting Large Language Models to Human Values
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

Machine-Learning Robustness, Foundation Models, and Reproducibility
From ACM Opinion

Machine-Learning Robustness, Foundation Models, and Reproducibility

An interview with Percy Liang, associate professor of Computer Science at Stanford University

Robot Learning at Google and Generalization via Language
From ACM Opinion

Robot Learning at Google and Generalization via Language

Google Robotics research scientist Eric Jang talks about robotic manipulation and self-supervised robotic learning

Self-Supervised Learning and Large Language Models
From ACM Opinion

Self-Supervised Learning and Large Language Models

Stanford PhD student discusses recent research on understanding, building, and controlling pre-trained models

RL Benchmarking, Climate Impacts of AI, and AI for Law
From ACM Opinion

RL Benchmarking, Climate Impacts of AI, and AI for Law

Stanford JD-PhD candidate Peter Henderson talks about creating robust decision-making systems and ML methods that benefit society

Strong AI Requires Autonomous Building of Composable Models
From ACM Opinion

Strong AI Requires Autonomous Building of Composable Models

Models built by AI must encode the fundamental patterns of experience

Meta Learning and Model-Based Reinforcement Learning
From ACM Opinion

Meta Learning and Model-Based Reinforcement Learning

Stanford professor Chelsea Finn talks about robotics and meta learning research

Yann LeCun Talks Research Beginnings and Recent Developments
From ACM Opinion

Yann LeCun Talks Research Beginnings and Recent Developments

Deep-learning pioneer discusses early days in image-processing and developments in self-supervised learning for computer vision
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