Deep Learning is Human, Through and Through

I wrote this story for the Communications of the ACM and it was published on October 18, 2022

It was 10 years ago, in 2012, that deep learning made its breakthrough, when an innovative algorithm for classifying images based on multi-layered neural networks suddenly turned out to do spectacularly better than all algorithms before it. That breakthrough has led to deep learning's adoption in domains like speech and image recognition, automatic translation and transcription, and robotics.

As deep learning was embedded into ever-more everyday applications, more and more examples of what can go wrong also surfaced: artificial intelligence (AI) systems that discriminate, confirm stereotypes, make inscrutable decisions and require a lot of data and sometimes also a huge amount of energy.

In this context, the 9th Heidelberg Laureate Forum organized a panel discussion on the applications and implications of deep learning for an audience of some 200 young researchers from more than 50 countries. The panel included Turing Award recipients Yoshua Bengio, Yann LeCun, and Raj Reddy, 2011 ACM Prize in Computing recipient Sanjeev Arora, and researchers Shannon Vallor, Been Kim, Dina Machuve, and Shakir Mohamed. Katherine Gorman moderated the discussion.

The full story can be read on the website of the Communications of the ACM

There is Plenty of Room at The Top (of Supercomputing)

Supercomputers are the Olympic champions of scientific computing. Through numerical simulations, they enrich our understanding of the world, be it stars lightyears away in the universe, the Earth's weather and climate, or the functioning of the human body.

For over four decades, Jack Dongarra has been a driving force in the field of high-performance computing. Earlier this year, Dongarra was awarded the 2021 ACM A.M. Turing Award for "his pioneering contributions to numerical algorithms and libraries that enabled high performance computational software to keep pace with exponential hardware improvements for over four decades."

Writer Bennie Mols met with Dongarra during the 9th Heidelberg Laureate Forum in Germany in September to talk about the present and future of high-performance computing. Dongarra, now 72, has been a University Distinguished Professor at the University of Tennessee (U.S.) and a Distinguished Research Staff Member at the U.S. Department of Energy's Oak Ridge National Laboratory since 1989.

Read the rest of my article on the website of the Communications of the ACM