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Databricks KARL Agent Tackles All Enterprise Search Types via RL

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.

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.

Google’s AI Mode in Search now lets you plan, write, and code on its own Canvas

Google Search has updated Canvas inside AI Mode, a workspace powered by Gemini that already lets users draft and refine documents, to now support coding projects and interactive tools. With the latest ...
IEEE

A Two-Stage Soft-Decision Decoding Algorithm for BCH Codes

Abstract: In this paper, we propose a two-stage soft-decision decoding (SDD) algorithm for BCH codes. At the first stage, we search for test error patterns (TEPs ...
IEEE

A Joint High-Precision Frequency and Code Phase Estimation Algorithm for Iridium NEXT Satellites’ Signals of Opportunity

Abstract: In recent years, Low Earth Orbit (LEO) satellite signals of opportunity (SOPs) positioning technology has emerged a significant alternative to the Global Navigation Satellite System (GNSS), ...