RealPage Settlement Shows Algorithmic Pricing Isn’t the Enemy

Opinion: The Department of Justice's settlement with RealPage argues that the use of algorithmic pricing software itself ...
IEEE

A TD3-Based Reinforcement Learning Algorithm With Curriculum Learning for Adaptive Yaw Control in All-Wheel-Drive Electric Vehicles

Abstract: A novel artificial intelligence-based approach for the direct yaw control (DYC) of an all-wheel drive (AWD) electric vehicle (EV) is proposed in this paper. To improve adaptability and ...
Frontiers

Efficiency algorithm: new AI-based tools for an adaptive learning environment

Introduction: The learning process is characterized by its variability rather than linearity, as individuals differ in how they receive, process, and store information. In traditional learning, taking ...
The New York Times

I’m Building an Algorithm That Doesn’t Rot Your Brain

new video loaded: I’m Building an Algorithm That Doesn’t Rot Your Brain transcript “Our brains are being melted by the algorithm.” [MUSIC PLAYING] “Attention is infrastructure.” “Those algorithms are ...
Rutgers University

Algorithm-Based Strategy Shows Promise in Reducing Urban Poverty

As aid organizations turn to artificial intelligence to optimize resources, a Rutgers expert reports on a new targeting approach that puts people first When the COVID-19 pandemic hit, aid ...
Finextra

AI vs Rules-Based Transaction Monitoring: Why a Hybrid Approach Wins

Fraud in payments is growing more sophisticated, forcing payment service providers (PSPs) to rethink their defenses. Today’s fraudsters are even leveraging AI tools to scale attacks and evade ...
marktechpost

Building a Hybrid Rule-Based and Machine Learning Framework to Detect and Defend Against Jailbreak Prompts in LLM Systems

In this tutorial, we introduce a Jailbreak Defense that we built step-by-step to detect and safely handle policy-evasion prompts. We generate realistic attack and benign examples, craft rule-based ...
IEEE

A Learning Algorithm Based on Similarity Identification and Knowledge Transfer for Dynamic Multi-Objective Optimization

Abstract: Prediction-based dynamic multi-objective optimization algorithms (DMOEAs) are widely used to explore the relationships of Pareto-optimal solutions (POSs) under continuous time steps, aiming ...
Frontiers

Deep reinforcement learning and robust SLAM based robotic control algorithm for self-driving path optimization

A reward shaping deep deterministic policy gradient (RS-DDPG) and simultaneous localization and mapping (SLAM) path tracking algorithm is proposed to address the issues of low accuracy and poor ...