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

RLCoder: Reinforcement Learning for Repository-Level Code Completion

Abstract: Repository-level code completion aims to generate code for unfinished code snippets within the context of a specified repository. Existing approaches mainly rely on retrievalaugmented ...
GitHub

circuit-synth

What is Code-Based Circuit Design? Circuit-synth brings software engineering practices to hardware design by letting you define circuits in Python code instead of ...
IEEE

A Reinforcement Learning Environment for Automatic Code Optimization in the MLIR Compiler

Abstract: Code optimization is a crucial task that aims to enhance code performance. However, this process is often tedious and complex, highlighting the necessity for automatic code optimization ...
GitHub

Block or report xiaomegmeng233

The Unity Machine Learning Agents Toolkit (ML-Agents) is an open-source project that enables games and simulations to serve as environments for training intelligent agents using deep reinforcement … ...