Artificial Intelligence and Machine Learning
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Inferring and Improving Street Maps with Data-Driven Automation
Automatic map inference, data refinement, and machine-assisted map editing promises more accurate map datasets.
Industry experiences on the data challenges of AI and the call for a data ecosystem for industrial enterprises.
An obsessive gamer's quest for the absolutely most significant computer ever.
AI and Sustainability: Where Are We and What’s Next?
Researchers are exchanging views and proposing solutions as questions around AI's environmental impact become more urgent.
Google’s AI Upscaling Technology Outperforms Previous Models
New models developed by the search giant upgrade the resolution of photos.
Language Imitation Games and the Arrival of Broad and Shallow AI
On the impact of large language models.
Algorithms can have a devastating impact on people's lives, especially if they already are struggling economically.
Beyond the pandemic, organizations need to recognize what digital assets, interactions, and communication processes reap the most benefits from virtual reality.
Human Detection of Machine-Manipulated Media
Technologies for manipulating and faking online media may outpace people's ability to tell the difference.
The pursuit of responsible AI raises the ante on both the trustworthy computing and formal methods communities.
AI Calling ET: How Artificial Intelligence Supports the Search for Extraterrestrial Life
Researchers increasingly ask AI whether anybody is out there.
Not everyone who questions computational hegemony is appealing to magic, mysticism, or divinity.
Who is Camille Noûs, who has contributed to hundreds of papers on Google Scholar?
GLOM: Teaching Computers to See the Way(s) We Do
Geoffrey Hinton wants to design neural networks so they have different ways of seeing the same thing.
Photonic Processors Light the Way
Highly efficient light-based processors can overcome the bottlenecks of today's electronics.
The architect of the Sagrada Familia appears to have done parametric modeling in his head; software is helping to complete the structure a century later.
Technical Perspective: The Importance of WINOGRANDE
"WINOGRANDE" explores new methods of dataset development and adversarial filtering, expressly designed to prevent AI systems from making claims of smashing through benchmarks without making real progress.
Formalizing and Guaranteeing Human-Robot Interaction
As robots begin to interact closely with humans, we need to build systems worthy of trust regarding the safety and quality of the interaction.
WinoGrande: An Adversarial Winograd Schema Challenge at Scale
We introduce WinoGrande, a large-scale dataset of 44k problems, inspired by the original Winograd Schema Challenge, but adjusted to improve both the scale and the hardness of the dataset.
Mathematician Martin Jackson is known for his work on Hilbert's Tenth Problem, among other things.
U.S. AI Policy Still Effectively A Closed Box
Expect a tapestry of federal, state and local policies to take shape.
Unveiling Unexpected Training Data in Internet Video
Using clever video curation and processing practices to extract video training signals automatically.
Shape the Future of Computing
ACM encourages its members to take a direct hand in shaping the future of the association. There are more ways than ever to get involved.
Get InvolvedCommunications of the ACM (CACM) is now a fully Open Access publication.
By opening CACM to the world, we hope to increase engagement among the broader computer science community and encourage non-members to discover the rich resources ACM has to offer.
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