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New Databricks KARL RAG Agent Promises 33% Cost Reduction vs. Claude Opus 4.6

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

AutoOpt: A General Framework for Automatically Designing Metaheuristic Optimization Algorithms With Diverse Structures

Abstract: Metaheuristics are widely recognized gradient-free solvers to hard problems that do not meet the rigorous mathematical assumptions of conventional solvers. The automated design of ...
IEEE

A Fuzzy PID-Incorporated Stochastic Gradient Descent Algorithm for Fast and Accurate Latent Factor Analysis

Abstract: A stochastic gradient descent (SGD) based latent factor analysis (LFA) model can obtain superior performance when performing representation to a high-dimensional and incomplete (HDI) matrix, ...

Databricks built a RAG agent it says can handle every kind of enterprise search

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