Kaiya now plans, reasons, and executes multi-step analytic workflows autonomously—leveraging SQL, Python, and contextual intelligence to deliver 20× deeper insights as well as offering custom ...

An artificial-intelligence algorithm that discovers its own way to learn achieves state-of-the-art performance, including on some tasks it had never encountered before. Joel Lehman is at Lila Sciences ...

Summary: A new computational tool developed by researchers has uncovered genetic evidence directly linking Alzheimer’s disease to the loss of memory-making neurons, helping to resolve a decades-long ...

Abstract: In the field of single objective optimization algorithms, learned evolutionary algorithms have achieved success in obtaining better performance than human-designed strategies. However, these ...

High-dimensional data often contain noisy and redundant features, posing challenges for accurate and efficient feature selection. To address this, a dynamic multitask learning framework is proposed, ...

AI improves renewable energy forecasting accuracy by up to 33%, helping grid operators better integrate solar and wind resources. Predictive maintenance powered by AI reduces equipment downtime by ...

Deep neural networks (DNNs), which power modern artificial intelligence (AI) models, are machine learning systems that learn hidden patterns from various types of data, be it images, audio or text, to ...

Filip's path to RIT Croatia began unexpectedly, sparked by an article about a successful Croatian hotel manager who had attended an American university. "I felt this intuitive pull to call them, and ...

The private equity playbook is being rewritten. Debt is pricier, exits are slower and limited partners scrutinize every basis point. Over the past quarter, a common mandate has called for funds to use ...

Abstract: The Dynamic Vehicle Routing Problem with Time Windows (DVRPTW) is a widespread real-world challenge, and numerous algorithms have been proposed to address it. However, in the context of an ...