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datePast Year
subjectComputer Applications
authorThe Gradient
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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.

Artificial Intelligence and the Future of Demos
From ACM Opinion

Artificial Intelligence and the Future of Demos

One way to examine the relationship between AI and democracy is to turn the attention toward the very basic unit common to all forms of democracy: the people.

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.

Lessons From Deploying Deep Learning to Production
From ACM Opinion

Lessons From Deploying Deep Learning to Production

Peter Gao, an early engineer at Cruise, reflects on his experience deploying deep-learning models into production.

The Missing Voices in Natural Language Processing
From ACM Opinion

The Missing Voices in Natural Language Processing

Who and what is being represented in the data and development of NLP models?

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
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