Databricks has released KARL, an RL-trained RAG agent that it says handles all six enterprise search categories at 33% lower cost than frontier models.

AI is reshaping online search in ways that reduce friction for consumers while increasing it for businesses. Large language models such as ChatGPT and Copilot now function as answer engines, ...

Databricks' KARL agent uses reinforcement learning to generalize across six enterprise search behaviors — the problem that breaks most RAG pipelines.

Newsrooms have long used AI to sift through document dumps. Now that same tech is being used to build search tools for ...

Abstract: Despite the wide variety of applications and use cases that can be solved with the help of machine learning algorithms, researchers have yet to develop a general artificial intelligence ...

Welcome to the artifact repository of OSDI'25 accepted paper: Achieving Low-Latency Graph-Based Vector Search via Aligning Best-First Search Algorithm with SSD! This repository contains the ...

We discuss whether science is in the process of being transformed from a quest for causality to a quest for correlation in light of the recent development in artificial intelligence. We observe that ...

WASHINGTON – The U.S. Army has established a new career pathway for officers to specialize in artificial intelligence and machine learning (AI/ML), formally designating the 49B AI/ML Officer as an ...

Google launched four official and confirmed algorithmic updates in 2025, three core updates and one spam update. This is in comparison to last year, in 2024, where we had seven confirmed updates, then ...

Abstract: Multidimensional parameter estimation is a critical challenge in fields such as radar, sonar, and wireless communications, where the space-alternating generalized expectation-maximization ...

Music recommendation algorithms were supposed to help us cut through the noise, but they just served us up slop. If you buy something from a Verge link, Vox Media may earn a commission. See our ...

A machine learning algorithm used gene expression profiles of patients with gout to predict flares. The PyTorch neural network performed best, with an area under the curve of 65%. The PyTorch model ...