Browsing: agents

Andrej Karpathy released autoresearch, a minimalist Python tool designed to enable AI agents to autonomously conduct machine learning experiments. The project is a stripped-down version of…

AI development is accelerating fast. Advances in hardware, software optimization, and better datasets now allow training runs that once took weeks to finish in hours. A…

In this tutorial, we build a complete cognitive blueprint and runtime agent framework. We define structured blueprints for identity, goals, planning, memory, validation, and tool access,…

Integrating Google Workspace APIs—such as Drive, Gmail, Calendar, and Sheets—into applications and data pipelines typically requires writing boilerplate code to handle REST endpoints, pagination, and OAuth…

Organizations increasingly deploy custom large language models (LLMs) on Amazon SageMaker AI real-time endpoints using their preferred serving frameworks—such as SGLang, vLLM, or TorchServe—to help gain…

Summary created by Smart Answers AIIn summary:OpenAI’s GPT-5.4 introduces groundbreaking agentic AI capabilities that allow it to perform computer actions like clicking a mouse and editing…

OpenAI has released Symphony, an open-source framework designed to manage autonomous AI coding agents through structured ‘implementation runs.’ The project provides…

Use of crypto by AI agents is a potential use case that has been touted by the industry for years, and now, one study indicates the…

Organizations can face two critical challenges with conversational AI. First, users need answers where they work—in their CRM, support console, or analytics portal—not in separate tools.…

As AI development shifts from simple chat interfaces to complex, multi-step autonomous agents, the industry has encountered a significant bottleneck: non-determinism. Unlike traditional software where code…