The Model Context Protocol (MCP), open-sourced by Anthropic in November 2024, has rapidly become the cross-cloud standard for connecting AI agents to tools, services, and data across the enterprise…
Category: AI
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NVIDIA AI Releases OpenReasoning-Nemotron: A Suite of Reasoning-Enhanced LLMs Distilled from DeepSeek R1 0528
NVIDIA AI has introduced OpenReasoning-Nemotron, a family of large language models (LLMs) designed to excel in complex reasoning tasks across mathematics, science, and code. This model suite—comprising 1.5B, 7B, 14B, and…
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Maybe Physics-Based AI Is the Right Approach: Revisiting the Foundations of Intelligence
Over the past decade, deep learning has revolutionized artificial intelligence, driving breakthroughs in image recognition, language modeling, and game playing. Yet, persistent limitations have surfaced: data inefficiency, lack of…
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Building a Modern Async Configuration Management System with Type Safety and Hot Reloading
In this tutorial, we guide you through the design and functionality of AsyncConfig, a modern, async-first configuration management library for Python. We build it from the ground up to support powerful features, including type-safe…
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Deep Research Agents: A Systematic Roadmap for LLM-Based Autonomous Research Systems
A team of researchers from University of Liverpool, Huawei Noah’s Ark Lab, University of Oxford and University College London presents a report explaining Deep Research Agents (DR agents), a new paradigm in autonomous…
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MemAgent: A Reinforcement Learning Framework Redefining Long-Context Processing in LLMs
Handling extremely long documents remains a persistent challenge for large language models (LLMs). Even with techniques such as length extrapolation and sparse attention, models often suffer from performance degradation and high…
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The Definitive Guide to AI Agents: Architectures, Frameworks, and Real-World Applications (2025)
What is an AI Agent?
An AI Agent is an autonomous software system that can perceive its environment, interpret data, reason, and execute actions to achieve specific goals without explicit human intervention. Unlike…
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Building a Multi-Agent AI Research Team with LangGraph and Gemini for Automated Reporting
In this tutorial, we build a complete multi-agent research team system using LangGraph and Google’s Gemini API. We utilize role-specific agents, Researcher, Analyst, Writer, and Supervisor, each responsible for a distinct part of…
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This AI Paper Introduces ARAG: A Multi-Agent RAG Framework for Context-Aware and Personalized Recommendations
Personalized recommendations have become a vital component of many digital systems, aiming to surface content, products, or services that align with user preferences. The process relies on analyzing past behavior, interactions, and…
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You Don’t Need to Share Data to Train a Language Model Anymore—FlexOlmo Demonstrates How
The development of large-scale language models (LLMs) has historically required centralized access to extensive datasets, many of which are sensitive, copyrighted, or governed by usage restrictions. This constraint severely limits…
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