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.
IEEE

Learning-Aided Iterated Local Search Algorithm for Integrated Order Batching, Picker Assignment, Batch Sequencing, and Picker Routing Problem

Abstract: This work tackles an integrated order batching, picker assignment, batch sequencing, and picker routing problem in warehouse environments. A Learning-Aided Iterated Local Search (LILS) is ...
IEEE

Bridging Evolutionary Algorithms and Reinforcement Learning: A Comprehensive Survey on Hybrid Algorithms

Abstract: Evolutionary reinforcement learning (ERL), which integrates the evolutionary algorithms (EAs) and reinforcement learning (RL) for optimization, has demonstrated remarkable performance ...

Meet Project Catapult, a super-search machine network being built by Microsoft engineers

Microsoft engineers are working on Project Catapult, utilizing field-programmable arrays (FPGAs) that Microsoft can modify specifically for use on its own software such as Bing. This allows for faster ...
GitHub

The search-extract-summarize flow

Of course this flow is a very simplified version of the real AI search engines, but it is a good starting point to understand the basic concepts. One benefit is that we can manipulate the search ...
eWeek

6 Best Nano Banana 2 Prompts in 2026: How to Generate Smarter AI Images

Discover the best Nano Banana 2 prompts to test Gemini 3.1 Flash Image, from 4K mockups to multilingual text and character consistency.