Y Combinator-backed Random Labs launches Slate V1, claiming the first 'swarm-native' coding agent

When a worker thread completes a task, it doesn't return a sprawling transcript of every failed attempt; it returns a compressed summary of the successful tool calls and conclusions.

Probing entanglement and parameter sensitivity in QAOA via Quantum Fisher Information

Practical Application: The authors propose QFI-Informed Mutation (QIm), a heuristic that adapts mutation probabilities using diagonal QFI entries. QIm outperforms uniform and random-restart baselines, ...
Scientific American

How to find pi in randomness all around you

Celebrate Pi Day and read all about how this number pops up across math and science on our special Pi Day page. Grab something circular, like a cup, measure the distance around the circle, and divide ...
MyChesCo on MSN

University of Michigan’s Mark Newman awarded 2026 SIAM von Neumann Prize

PHILADELPHIA, PA — The Society for Industrial and Applied Mathematics announced that University of Michigan professor Mark Newman will receive the 2026 John von Neumann Prize for contributions to ...

Mark Newman is the 2026 SIAM John von Neumann Prize Lecturer

Mark Newman will deliver this flagship lecture at the 2026 SIAM Annual Meeting (AN26), happening July 6-10, 2026. Anatol ...
Devdiscourse

Big Data and AI propel geoscience into new digital era

A new study published in the journal Minerals sheds light on this sweeping shift. Titled Big Data and AI in Geoscience: From ...
Open Heart

Enhanced cardiovascular disease risk prediction using integrated machine learning models: a study from the UK Biobank cohort

Objective Cardiovascular diseases (CVD) remain the leading cause of mortality globally, necessitating early risk identification to improve prevention and management strategies. Traditional risk ...
EurekAlert!

PolyU develops novel AI graph neural network models to unravel interdisciplinary complexities in image recognition and neuroscience

As an emerging technology in the field of artificial intelligence (AI), graph neural networks (GNNs) are deep learning models designed to process graph-structured data. Currently, GNNs are effective ...
MIT Technology Review

This is the most misunderstood graph in AI

To some, METR’s “time horizon plot” indicates that AI utopia—or apocalypse—is close at hand. The truth is more complicated. MIT Technology Review Explains: Let our writers untangle the complex, messy ...
techxplore

New graph attention network models higher-order relationships in complex graph data

As an emerging technology in the field of artificial intelligence (AI), graph neural networks (GNNs) are deep learning models designed to process graph-structured data. Currently, GNNs are effective ...
EurekAlert!

A survey of geometric graph neural networks: data structures, models and applications

The 2024 Nobel Prize in Chemistry was recently granted to David Baker, Demis Hassabis and John M. Jumper, renowned for their pioneering works in protein design. In addition, Nature has recently ...