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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.

Software Engineering in Physics Research
From ACM Opinion

Software Engineering in Physics Research

A discussion on how physics research scientists use software.

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...

The AI Researcher Giving Her Field Its Bitter Medicine
From ACM Opinion

The AI Researcher Giving Her Field Its Bitter Medicine

Anima Anandkumar wants computer scientists to move beyond the matrix, among other challenges.

 Supercomputer Emulator: AI's New Role in Science
From ACM Opinion

Supercomputer Emulator: AI's New Role in Science

Chris Bishop, Microsoft's head of AI4Science, sees machine learning partially supplanting simulation.

Interpretable Machine Learning
From ACM Opinion

Interpretable Machine Learning

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

How to Solve AI's 'Common-Sense' Problem
From ACM Opinion

How to Solve AI's 'Common-Sense' Problem

AI systems without common sense will make mistakes when they reach the limits of where they've been trained.

An Interview with Dana Scott
From Communications of the ACM

An Interview with Dana Scott

ACM Fellow and A.M. Turing Award recipient Dana Scott reflects on his career.

Yann LeCun's Bold New Vision for the Future of AI
From ACM Opinion

Yann LeCun's Bold New Vision for the Future of AI

One of deep learning's godfathers pulls together old ideas to sketch out a fresh path for AI.

The Computer Scientist Who Parlays Failures into Breakthroughs
From ACM Opinion

The Computer Scientist Who Parlays Failures into Breakthroughs

An interview with Yale University Sterling Professor of Computer Science Daniel Spielman.

What Is So Great about Quantum Computing?
From ACM Opinion

What Is So Great about Quantum Computing?

A Q&A with NIST theorist Alexey Gorshkov.

How to Write Software with Mathematical Perfection
From ACM Opinion

How to Write Software with Mathematical Perfection

Leslie Lamport revolutionized how computers talk to each other, and now he's working on how engineers talk to their machines.

Computers Have Memories Too
From ACM Opinion

Computers Have Memories Too

Simons Foundation Junior Fellow Sebastian Wolff discusses his quest to simplify the switch between the two deletion processes.

25 years with cURL
From ACM Opinion

25 years with cURL

Founder and lead developer Daniel Stenberg discusses looking after cURL and libcurl for the past 25 years.

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

Avoiding Defects in C Programming
From ACM Opinion

Avoiding Defects in C Programming

Computer security specialist details tools and techniques developers can use to write secure code in C

The Benefits of Rust
From ACM Opinion

The Benefits of Rust

An in-depth discussion about the virtue of Rust, its future, and more

How Much Has Quantum Computing Actually Advanced?
From ACM Opinion

How Much Has Quantum Computing Actually Advanced?

John Martinis, former chief architect of Google Sycamore, offers a measured perspective on quantum's progress

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
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