Learn how to solve problems using linear programming. A linear programming problem involves finding the maximum or minimum value of an equation, called the objective functions, subject to a system of ...

Hybrid hash function post-quantum cryptography research: a new paper on IACR ePrint formalizes a construction whose collision ...

Agentic artificial intelligence needs shared memory and traceability. Yugabyte’s Meko provides a data layer for multi-agent ...

D-Wave quantum supremacy challenged: Flatiron Institute physicists showed that a classical algorithm using 3D tensor networks ...

A twelve-word post from Peter Steinberger on July 18 triggered millions of views and a live technical war over AI agent architecture. Andrew Ng's new knowledge graph course added fuel: should ...

Abstract: Scientific workloads are often described by Directed Acyclic task Graphs. Indeed, DAGs represent both a theoretical model and the structure employed by dynamic runtime schedulers to handle ...

Abstract: We study distributed optimization to minimize a sum of smooth and strongly-convex functions. Recent work on this problem uses gradient tracking to achieve linear convergence to the exact ...

A derivative is a function which measures the slope. It depends upon x in some way, and is found by differentiating a function of the form y = f (x). When x is substituted into the derivative, the ...

Recently, a technique called equality saturation adapted e-graphs for program optimization. Equality saturation can ...

For the second time in a week, a long-standing conjecture has been disproved by artificial intelligence, highlighting the ...

Don't underestimate the power of a yes-or-no question. Some of the toughest computing problems boil down to thousands of tiny ...

In May 2026, OpenAI released a new math result that sent shock waves throughout the world of mathematical research. A major unsolved problem called the “unit distance conjecture” had just been ...