True agentic AI is years away - here's why and how we get there

Today's AI agents are a primitive approximation of what agents are meant to be. True agentic AI requires serious advances in reinforcement learning and complex memory.
Science Daily

This simulation reveals what really happens near black holes

Black holes are among the most extreme objects in the universe, and now scientists can model them more accurately than ever before. By combining Einstein’s gravity with realistic behavior of light and ...
IEEE

Approximation Algorithms for Computing Virtual Backbones Considering Routing Costs in Wireless Networks

Abstract: The strategy of constructing a virtual backbone (VB) to perform routing tasks is considered a mature method for addressing the broadcast storm problem in wireless sensor networks (WSNs). A ...
IEEE

Approximation Algorithms for Training One-Node ReLU Neural Networks

Abstract: Training a one-node neural network with the ReLU activation function via optimization, which we refer to as the ON-ReLU problem, is a fundamental problem in machine learning. In this paper, ...
acm.org

Remark on algorithm 162: Near-minimax polynomial approximations and partitioning of intervals

A method of near-minimax polynomial approximation is described. As a by-product, this method provides a formula for an estimate of the maximum error associated with a ...
gc.cuny

Applications and algorithms for topologically correct approximations of curves

Abstract: In applied and numerical algebraic geometry, many problems are reduced to computing an approximation to a real algebraic curve. In order to elevate the results of such a computation to the ...
Scientific Research Publishing

Zhao, X., Sun, Z. and Karniadakis, G.E. (2015) Second-Order Approximations for Variable Order Fractional Derivatives: Algorithms and Applications. Journal of Computational ...

ABSTRACT: Fractional-order time-delay differential equations can describe many complex physical phenomena with memory or delay effects, which are widely used in the fields of cell biology, control ...
SciELO

An SLP algorithm and its application to topology optimization

We introduce a globally convergent sequential linear programming method for nonlinear programming. The algorithm is applied to the solution of classic topology optimization problems, as well as to the ...
The Conversation

Opening the black box: how ‘explainable AI’ can help us understand how algorithms work

David Martens has received funding from AXA JRI. Sofie Goethals has received funding from the Flemish Research Foundation. When you visit a hospital, artificial intelligence (AI) models can assist ...
Frontiers

Improving the convergence of an iterative algorithm for solving arbitrary linear equation systems using classical or quantum binary optimization

1 Centro Brasileiro de Pesquisas Físicas, Rio de Janeiro, RJ, Brazil 2 Petróleo Brasileiro S.A., Centro de Pesquisas Leopoldo Miguez de Mello, Rio de Janeiro, Brazil Recent advancements in quantum ...
The New York Times

Black Artists Say A.I. Shows Bias, With Algorithms Erasing Their History

Tech companies acknowledge machine-learning algorithms can perpetuate discrimination and need improvement. By Zachary Small The artist Stephanie Dinkins has long been a pioneer in combining art and ...