One of the shared, fundamental goals of most chemistry researchers is the need to predict a molecule's properties, such as ...

Despite the AI hype, tools are proving valuable for leading-edge chip manufacturing. More aggressive feature scaling and ...

The natural protein universe is vast, and yet, going beyond and designing new proteins not observed in nature can yield new ...

Deep learning using fundus and optical coherence tomography imaging may identify mental disorders during routine eye exams.

Artificial intelligence models used to detect depression on social media are often biased and methodologically flawed, according to a study led by Northeastern University computer science graduates.

Aircela demonstrates a machine in Manhattan that produces gasoline directly from air, using direct air capture technology compatible with existing engines and infrastructure.

In Recentive, the Federal Circuit acknowledged the growing significance of AI and machine learning and emphasized that its holding is limited to generic machine learning applications.

I'm using MATLAB or other programming languages like C/C++/Java to perform my experiments. Though not all the experiments are machine learning-related, but sometimes I have to track my experiments ...

Q&A Predicting the Future Using Azure Machine Learning By David Ramel 05/13/2025 The ability to anticipate what comes next has long been a competitive advantage -- one that's increasingly within reach ...

This has led to an increased interest in predictive analytics and machine learning (ML) as tools for proactive supply chain management (Foroutan & Lahmiri, 2024). Machine learning models are ...