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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

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

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

The Imperative for Sustainable AI Systems
From ACM Opinion

The Imperative for Sustainable AI Systems

The impact of AI's massive carbon footprint is social, not just environmental

Machine Learning Won't Solve Natural Language Understanding
From ACM Opinion

Machine Learning Won't Solve Natural Language Understanding

Data-driven approaches to NLU are psychologically, cognitively, and computationally implausible.
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