Communications of the ACM

AI Regulation in U.S. States: Lessons Learned and Key Takeaways

This regulatory conundrum is particularly acute in the U.S., where the absence of an overarching federal AI law has created a ...

AI coach rewrites the rules of cardiovascular research

Every day, millions of Americans open a fitness app, glance at their step count, and may even feel a mild pang of guilt ...

Atomic step–terrace ordering enables unprecedented precision in mechanical testing

As modern technologies shrink to the nanoscale, surfaces increasingly dictate how materials deform, yield, and fail. Yet ...
British Journal of Ophthalmology

Peripheral retinal haemorrhage density on ultra-widefield imaging as a novel biomarker for predicting diabetic retinopathy progression: a 2-year longitudinal stu…

Aims To evaluate whether predominantly peripheral lesions (PPLs) and other imaging biomarkers on ultra-widefield (UWF) ...

The Future of Intoxication Detection May Be in Your Voice

BioMedWire Editorial Coverage: The ability to accurately detect drug and alcohol intoxication has long been a persistent challenge across industries, from law ...
WUNC

Your 'step count' can predict how well you recover from surgery

So the number of steps you take each day can say a lot about your health. Upping your step count can help boost everything from mood to metabolism, even longevity. And now a new study finds another ...
EurekAlert!

Method for stress-testing cloud computing algorithms helps avoid network failures

Researchers from MIT and elsewhere have developed a more user-friendly and efficient method to help networking engineers identify potential system failures before they cause major problems, like a ...
IEEE

Algorithm Design and Regret Analysis for Aggregative Optimization in Open Multi-Agent Systems

Abstract: This paper studies the problem of aggregative optimization in open multi-agent systems (OMAS), where agents are allowed to join and leave the system in a free manner during the ...
Digi Times

In-depth: Google TurboQuant cuts LLM memory 6x, resets AI inference cost curve

Google has introduced TurboQuant, a compression algorithm that reduces large language model (LLM) memory usage by at least 6x while boosting performance, targeting one of AI's most persistent ...
Wall Street Journal

The Five Step 'Algorithm' Driving Tesla’s Success

This transcript was prepared by a transcription service. This version may not be in its final form and may be updated. Tim Higgins: A lot is written about Elon Musk. What did he say when you told him ...
TechCrunch

Google unveils TurboQuant, a new AI memory compression algorithm — and yes, the internet is calling it ‘Pied Piper’

If Google’s AI researchers had a sense of humor, they would have called TurboQuant, the new, ultra-efficient AI memory compression algorithm announced Tuesday, “Pied Piper” — or, at least that’s what ...
Ars Technica

Google’s TurboQuant AI-compression algorithm can reduce LLM memory usage by 6x

Even if you don’t know much about the inner workings of generative AI models, you probably know they need a lot of memory. Hence, it is currently almost impossible to buy a measly stick of RAM without ...