Using generative AI to design, train, or perform steps within a machine-learning system is risky, argues computer scientist Micheal Lones in a paper appearing in Patterns. Though large language models ...

Analysis of the 191 samples shows that 55 percent of groundwater falls within low to no restriction categories for irrigation ...

The results show that the Decision Tree model emerged as the top-performing algorithm, achieving an accuracy rate of 99.36 percent. Random Forest followed closely with 99.27 percent accuracy, while ...

Scaling agentic AI demands a strong data foundation - 4 steps to take first ...

Protein engineering is a field primed for artificial intelligence research. Each protein is made up of amino acids; to ...

The field of intelligent energy systems has witnessed a remarkable transformation owing to innovations in machine learning. Over the past few decades, the ...

Modality-agnostic decoders leverage modality-invariant representations in human subjects' brain activity to predict stimuli irrespective of their modality (image, text, mental imagery).

This study presents valuable findings by reanalyzing previously published MEG and ECoG datasets to challenge the predictive nature of pre-onset neural encoding effects. The evidence supporting the ...

Embed technical assurance into vendor contracts, requiring evidence of performance/robustness/bias testing, transparency ...

The rapid advancement of spatial and single-cell omics technologies has revolutionized molecular biosciences by enabling high-resolution profiling of gene ...

In an era defined by rapid AI adoption, securing software has become increasingly complex. As organizations integrate ...

Boston Dynamics Spot Reads Gauges & Thermometers with Google AI When Boston Dynamics unveiled its agile quadruped Spot a few ...