One of the key challenges of building effective AI agents is teaching them to choose between using external tools or relying on their internal knowledge. But large language models are often trained to ...

Abstract: Python has become the programming language of choice for research and industry projects related to data science, machine learning, and deep learning. Since optimization is an inherent part ...

Most enterprise RAG pipelines are optimized for one search behavior. They fail silently on the others. A model trained to synthesize cross-document reports handles constraint-driven entity search ...

Microsoft Research has released OptiMind, an AI based system that converts natural language descriptions of complex decision problems into mathematical formulations that optimization solvers can ...

This repository provides the Java (jMetal 4.5), C, Matlab/Octave, and Python implementations of the (at least not synthetic) real-world (RE) problems presented in the following paper: Ryoji Tanabe and ...

This Unity asset provides an end-to-end, Human-in-the-Loop (HITL) Bayesian Optimization workflow (single- and multi-objective) built on botorch.org. It lets you declare design parameters and ...

In this advanced tutorial, we aim to build a multi-agent task automation system using the PrimisAI Nexus framework, which is fully integrated with the OpenAI API. Our primary objective is to ...

Aqarios' platform Luna v1.0 marks a major milestone in quantum optimization. This release significantly improves usability, performance, and real-world applicability by introducing FlexQAOA, a hybrid ...

ProcessOptimizer is a Python package designed to provide easy access to advanced machine learning techniques, specifically Bayesian optimization using, e.g., Gaussian processes. Aimed at ...

Generative design is a new way to create and build things that helps us make complicated and creative shapes that are hard to make with traditional methods. In simple words, it uses computer programs ...

Data-driven models that act as surrogates for computationally costly 3D topology optimization techniques are very popular because they help alleviate multiple time-consuming 3D finite element analyses ...