AI agents are powerful, but without a strong control plane and hard guardrails, they’re just one bad decision away from chaos.

Submodular maximization is a significant area of interest in combinatorial optimization, with numerous real-world applications. A research team led by Xiaoming SUN from the State Key Lab of Processors ...

Service intelligence startup Neuron7 Inc. said today it has come up with a solution to solve the reliability challenges that prevent enterprises from adopting artificial intelligence agents. That ...

Imagine a town with two widget merchants. Customers prefer cheaper widgets, so the merchants must compete to set the lowest price. Unhappy with their meager profits, they meet one night in a ...

Learn the Adagrad optimization algorithm, how it works, and how to implement it from scratch in Python for machine learning models. #Adagrad #Optimization #Python Trump administration looking to sell ...

import torch @torch.compile(backend="inductor") def fn(src, index, base_tensor): src = src + 10 torch.use_deterministic_algorithms(True) base_tensor.scatter_(0, index ...

The amount of electronic content in passenger cars is growing rapidly, primarily due to the integration of advanced safety features. The shift towards fully autonomous vehicles, which must comply with ...

ABSTRACT: Background/Objective: Wrinkles, nasolabial folds, pigmented spots, and roughness are representative parameters reflecting facial skin aging. Among them, nasolabial folds are a particular ...

Abstract: Traditional DDPG algorithm experience replay is limited by the fixed replay buffer capacity, which cannot meet the demand for multi-feature data with the improvement of the learning ability ...

Learn how the Adadelta optimization algorithm really works by coding it from the ground up in Python. Perfect for ML enthusiasts who want to go beyond the black box! Florida State Bracing for Hefty ...