The constant scaling of AI applications and other digital technologies across industries is beginning to tax the energy grid ...

Recently, a research team from the Rudolf Technology Center in Slovenia proposed a new method to optimize the sparse subgraph problem, which has wide applications in fields such as network analysis ...

Sparse matrices are fundamental to many computational problems, and their efficient representation in quantum computing is crucial for unlocking the potential of quantum algorithms. The core ...

A line of engineering research seeks to develop computers that can tackle a class of challenges called combinatorial optimization problems. These are common in real-world applications such as ...

Quantum computers that were previously limited to theoretical physics now learn to discover patterns, optimize decisions and ...

Your AI might look smart on benchmarks but could be brittle in the real world, leading to unexpected failures and eroding ...

S&P 500, Microsoft Corporation, International Business Machines, Honeywell International Inc. Read 's Market Analysis on Investing.com ...