Lance Fortnow on the current status and future outlook of solving the P-NP problem.

As AI tools evolve at a rapid pace, smaller, more flexible learning environments are well-positioned to test new approaches, develop expectations, and adjust as needed.

In recent years, numerous landslides on hillsides in urban and rural areas have underscored that understanding and predicting ...

Learn how to normalize a wave function using numerical integration in Python. This tutorial walks you through step-by-step coding techniques, key functions, and practical examples, helping students ...

Researchers from Kyushu University have developed an innovative computational method, called ddHodge, that can reconstruct the complex dynamics of how cells decide their fate. As reported in Nature ...

A monthly overview of things you need to know as an architect or aspiring architect. Unlock the full InfoQ experience by logging in! Stay updated with your favorite authors and topics, engage with ...

WASHINGTON — A new report from the National Academies of Sciences, Engineering, and Medicine examines how the U.S. Department of Energy could use foundation models for scientific research, and finds ...

A multicolored 3D model of an enzyme binding double-stranded DNA against a light purple background Computational enzyme design could allow for reactions not seen in nature. Credit: Ian Haydon ...

WEST LAFAYETTE, Ind. — With recent advances, cancer research now generates vast amounts of information. The data could help researchers detect patterns in cancer cells and stop their growth, but the ...

Researchers from Turku Bioscience Centre at the University of Turku, Finland, have developed a new computational method to interpret complex single-cell data. The method helps researchers identify and ...

Researchers from The University of New Mexico and Los Alamos National Laboratory have developed a novel computational framework that addresses a longstanding challenge in statistical physics. The ...

ABSTRACT: Mathematical optimization is a fundamental aspect of machine learning (ML). An ML task can be conceptualized as optimizing a specific objective using the training dataset to discern patterns ...