The Fed paper found that Kalshi's markets provide data that's "valuable to both researchers and policymakers." ...

RIT researchers publish a paper in Nature Scientific Reports on a new tree-based machine learning algorithm used to predict chaos.

Researchers have created a prediction method that comes startlingly close to real-world results. It works by aiming for strong alignment with actual values rather than simply reducing mistakes. Tests ...

Figure 1. This figure depicts the four categories of protein druggability target screening tools discussed in this section, which include structure-based methods, sequence-based methods, machine ...

Google's DeepMind just released WeatherNext 2, a new version of its AI weather prediction model. The company promises that it "delivers more efficient, more accurate and higher-resolution global ...

Artificial intelligence has taken the world by storm. In biology, AI tools called deep neural networks (DNNs) have proven ...

Data assimilation is an important mathematical discipline in earth sciences, particularly in numerical weather prediction (NWP). However, conventional data assimilation methods require significant ...

AI models outperform traditional statistics in predicting post-complete cytoreduction outcomes in ovarian cancer patients. AI's diagnostic accuracy was high for predicting overall survival and no ...

On-chain prediction markets such as Myriad have rapidly gained traction in recent years. Here’s how they work.

In the rapidly advancing field of computational biology, a newly peer-reviewed review explores the transformative role of deep learning techniques in revolutionizing protein structure prediction. The ...