In the rapidly evolving landscape of business and technology, optimizing computational efficiency is key to breaking new ground. At the International Conference for Machine Learning held July 23–29 in Honolulu, researchers presented a paper exploring whether an algorithm called Ford-Fulkerson—which computes the maximum flow in a network—can work faster by using machine learning.
Large-scale software often requires several machines and hundreds of hours of computing power to solve industry problems. By combining machine learning with problem-solving techniques, computers can analyze and process data faster. Another bonus: companies can save energy because computers are working more efficiently and using less power.
