A surprisingly easy way to multiply an AI model’s profit is to drive decisions via expected value instead of predictive scores. Here's how, illustrated with fraud detection.
For more than half a century, materials scientists have struggled with how to simulate the complexity of polymer materials.
The team built a DenseNet – a densely connected convolutional neural network – that learns hierarchical features directly ...
Tax Notes reporters Paul Jones and Emily Hollingsworth discuss how bias in artificial intelligence can affect automated ...
AllDigital Specialty Insurance never had to. When CEO Athula Alwis (pictured) and his co-founders launched the company, they ...
AI models can simulate the answers thousands of people would provide to a survey, but the results aren’t a reliable measure ...
The Rocklin Lab at Northwestern University today announced the release of the MGnify Stability Dataset, a large-scale experimental resource containing folding stability measurements for 1.8 million ...
Predictive Horizons launches a new AI model, enabling accurate vehicle diagnostics without human input; clearing a ...
When you tap your card, a signal travels to your bank’s fraud detection system in the time it takes to blink. The transaction processing at your checkout is fully automated, ope ...
Getting up to speed with a new research field can be tricky – it’s difficult to understand everything fully, but tempting to think that you do. There’s a parallel with sport where it might sound ...
New research warns that attackers, public authorities, and companies can now turn every router "into a potential means for surveillance" with "almost 100% ...
A team spends months - sometimes over a year - building an AI system. Engineers are hired, infrastructure is set up, a model ...
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