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datePast Year
subjectComputer Systems
authorThe Gradient
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At the Boundary of Machine and Mind
From ACM Opinion

At the Boundary of Machine and Mind

An interview with researcher Linus Lee.

Dense Visual Representations, NeRFs, and LLMs for Robotics
From ACM Opinion

Dense Visual Representations, NeRFs, and LLMs for Robotics

Google research scientist Pete Florence discusses how robotics can benefit from dense visual representations, neural radiance fields, and large language models....

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
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