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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.

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.

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...

Interpretable Machine Learning
From ACM Opinion

Interpretable Machine Learning

A conversation with Been Kim, staff research scientist at Google Brain.

AI Education and Research
From ACM Opinion

AI Education and Research

An interview with Grid.ai's Sebastian Raschka.

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?

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

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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