OpenAI

2299 Articles
OpenAI Releases an Open‑Sourced Version of a Customer Service Agent Demo with the Agents SDK
OpenAI

OpenAI Releases an Open‑Sourced Version of a Customer Service Agent Demo with the Agents SDK

OpenAI has open-sourced a new multi-agent customer service demo on GitHub, showcasing how to build domain-specialized AI agents using its Agents SDK. This...

ReVisual-R1: An Open-Source 7B Multimodal Large Language Model (MLLMs) that Achieves Long, Accurate and Thoughtful Reasoning
OpenAI

ReVisual-R1: An Open-Source 7B Multimodal Large Language Model (MLLMs) that Achieves Long, Accurate and Thoughtful Reasoning

The Challenge of Multimodal Reasoning Recent breakthroughs in text-based language models, such as DeepSeek-R1, have demonstrated that RL can aid in developing strong...

HtFLlib: A Unified Benchmarking Library for Evaluating Heterogeneous Federated Learning Methods Across Modalities
OpenAI

HtFLlib: A Unified Benchmarking Library for Evaluating Heterogeneous Federated Learning Methods Across Modalities

AI institutions develop heterogeneous models for specific tasks but face data scarcity challenges during training. Traditional Federated Learning (FL) supports only homogeneous model...

How to Build an Advanced BrightData Web Scraper with Google Gemini for AI-Powered Data Extraction
OpenAI

How to Build an Advanced BrightData Web Scraper with Google Gemini for AI-Powered Data Extraction

In this tutorial, we walk you through building an enhanced web scraping tool that leverages BrightData’s powerful proxy network alongside Google’s Gemini API...

Why Small Language Models (SLMs) Are Poised to Redefine Agentic AI: Efficiency, Cost, and Practical Deployment
OpenAI

Why Small Language Models (SLMs) Are Poised to Redefine Agentic AI: Efficiency, Cost, and Practical Deployment

The Shift in Agentic AI System Needs LLMs are widely admired for their human-like capabilities and conversational skills. However, with the rapid growth...

AREAL: Accelerating Large Reasoning Model Training with Fully Asynchronous Reinforcement Learning
OpenAI

AREAL: Accelerating Large Reasoning Model Training with Fully Asynchronous Reinforcement Learning

Introduction: The Need for Efficient RL in LRMs Reinforcement Learning RL is increasingly used to enhance LLMs, especially for reasoning tasks. These models,...

How Latent Vector Fields Reveal the Inner Workings of Neural Autoencoders
OpenAI

How Latent Vector Fields Reveal the Inner Workings of Neural Autoencoders

Autoencoders and the Latent Space Neural networks are designed to learn compressed representations of high-dimensional data, and autoencoders (AEs) are a widely-used example...

Building High-Performance Financial Analytics Pipelines with Polars: Lazy Evaluation, Advanced Expressions, and SQL Integration
OpenAI

Building High-Performance Financial Analytics Pipelines with Polars: Lazy Evaluation, Advanced Expressions, and SQL Integration

In this tutorial, we delve into building an advanced data analytics pipeline using Polars, a lightning-fast DataFrame library designed for optimal performance and...