New machine-learning models capture the rapid evolution of antimicrobial resistance

Antimicrobial resistance (AMR) is an increasingly dangerous problem affecting global health. In 2019 alone, ...

TillerPET: An AI model for high-throughput phenotyping of rice tiller traits

In a new study published in The Crop Journal on November 7, researchers developed an AI model named TillerPET that enables ...
pv magazine USA

Machine learning models identify hidden physical defects in solar arrays

The software tool developed by Stony Brook University uses self-supervised learning to detect long-term solar equipment damage weeks or years before manual inspections find it.

AI Image Generators Default to the Same 12 Photo Styles, Study Finds

AI image generation models have massive sets of visual data to pull from in order to create unique outputs. And yet, ...
InfoQ

Meta Details GEM Ads Model Using LLM-Scale Training, Hybrid Parallelism, and Knowledge Transfer

Meta released details about its Generative Ads Model (GEM), a foundation model designed to improve ads recommendation across ...
Communications of the ACM

Collective Intelligence Doesn’t Scale, In-Context Collaborative Learning Does

This is where Collective Adaptive Intelligence (CAI) comes in. CAI is a form of collective intelligence in which the ...
eLife

Human EEG and artificial neural networks reveal disentangled representations and processing timelines of object real-world size and depth in natural images

Neural and computational evidence reveals that real-world size is a temporally late, semantically grounded, and hierarchically stable dimension of object representation in both human brains and ...
Interesting Engineering

AlphaFold and the architecture that cracked protein structure

AlphaFold didn't accelerate biology by running faster experiments. It changed the engineering assumptions behind protein structure prediction.