Google has unveiled TurboQuant, a new AI compression algorithm that can reduce the RAM requirements for large language models by 6x. By optimizing how AI stores data through a method called ...

In physics, we often begin with elegant equations and clean analytical solutions. From Newton’s laws to Maxwell’s equations, many foundational results can be solved exactly at least under simplified ...

Metaheuristic algorithms are a class of algorithms used to solve complex optimization problems by employing search and optimization techniques to find the best or near-optimal solutions. Over the past ...

It’s a truism at this point that real style is all about wearing what you love with confidence. But that wisdom hardly feels helpful when you’re staring into your closet in utter bewilderment or ...

Shortest path algorithms sit at the heart of modern graph theory and many of the systems that move people, data, and goods around the world. After nearly seventy years of relying on the same classic ...

Algorithmic trading is no longer the exclusive domain of niche quantitative firms—it has become the backbone of modern financial markets. I am already seeing the significant impact AI-driven ...

A newly enacted New York law requires retailers to say whether your data influences the price of basic goods like a dozen eggs or toilet paper, but not how. If you’re near Rochester, New York, the ...

Determining the least expensive path for a new subway line underneath a metropolis like New York City is a colossal planning challenge—involving thousands of potential routes through hundreds of city ...

Dijkstra’s algorithm remains a cornerstone of graph theory, but this new approach shows that optimizations are possible for specific use cases. Whether in navigation systems, logistics, or AI, the ...

There is a new sorting algorithm a deterministic O(m log2/3 n)-time algorithm for single-source shortest paths (SSSP) on directed graphs with real non-negative edge weights in the comparison-addition ...

If you want to solve a tricky problem, it often helps to get organized. You might, for example, break the problem into pieces and tackle the easiest pieces first. But this kind of sorting has a cost.

The foremost objective of optimization is to identify the best solution among a set of feasible solutions to a problem 1. The process involves maximizing or minimizing an objective function by ...