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How the Model Context Protocol (MCP) Standardizes, Simplifies, and Future-Proofs AI Agent Tool Calling Across Models for Scalable, Secure, Interoperable Workflows Traditional Approaches to AI–Tool Integration

Before MCP, LLMs relied on ad-hoc, model-specific integrations to access external tools. Approaches like ReAct interleave chain-of-thought reasoning with explicit function calls, while Toolformer trains the model to learn when and how to invoke APIs. Libraries such as LangChain and…

Read MoreHow the Model Context Protocol (MCP) Standardizes, Simplifies, and Future-Proofs AI Agent Tool Calling Across Models for Scalable, Secure, Interoperable Workflows Traditional Approaches to AI–Tool Integration

Multimodal Queries Require Multimodal RAG: Researchers from KAIST and DeepAuto.ai Propose UniversalRAG—A New Framework That Dynamically Routes Across Modalities and Granularities for Accurate and Efficient Retrieval-Augmented Generation

RAG has proven effective in enhancing the factual accuracy of LLMs by grounding their outputs in external, relevant information. However, most existing RAG implementations are limited to text-based corpora, which restricts their applicability to real-world scenarios where queries may require…

Read MoreMultimodal Queries Require Multimodal RAG: Researchers from KAIST and DeepAuto.ai Propose UniversalRAG—A New Framework That Dynamically Routes Across Modalities and Granularities for Accurate and Efficient Retrieval-Augmented Generation

Building AI Agents Using Agno’s Multi-Agent Teaming Framework for Comprehensive Market Analysis and Risk Reporting

In today’s fast-paced financial landscape, leveraging specialized AI agents to handle discrete aspects of analysis is key to delivering timely, accurate insights. Agno’s lightweight, model-agnostic framework empowers developers to rapidly spin up purpose-built agents, such as our Finance Agent for…

Read MoreBuilding AI Agents Using Agno’s Multi-Agent Teaming Framework for Comprehensive Market Analysis and Risk Reporting

Google Researchers Advance Diagnostic AI: AMIE Now Matches or Outperforms Primary Care Physicians Using Multimodal Reasoning with Gemini 2.0 Flash

LLMs have shown impressive promise in conducting diagnostic conversations, particularly through text-based interactions. However, their evaluation and application have largely ignored the multimodal nature of real-world clinical settings, especially in remote care delivery, where images, lab reports, and other medical…

Read MoreGoogle Researchers Advance Diagnostic AI: AMIE Now Matches or Outperforms Primary Care Physicians Using Multimodal Reasoning with Gemini 2.0 Flash

A Step-by-Step Tutorial on Connecting Claude Desktop to Real-Time Web Search and Content Extraction via Tavily AI and Smithery using Model Context Protocol (MCP)

In this hands-on tutorial, we’ll learn how to seamlessly connect Claude Desktop to real-time web search and content-extraction capabilities using Tavily AI’s Model Context Protocol (MCP) server and the Smithery client. We’ll begin by reviewing the Tavily homepage and dashboard,…

Read MoreA Step-by-Step Tutorial on Connecting Claude Desktop to Real-Time Web Search and Content Extraction via Tavily AI and Smithery using Model Context Protocol (MCP)

IBM AI Releases Granite 4.0 Tiny Preview: A Compact Open-Language Model Optimized for Long-Context and Instruction Tasks

IBM has introduced a preview of Granite 4.0 Tiny, the smallest member of its upcoming Granite 4.0 family of language models. Released under the Apache 2.0 license, this compact model is designed for long-context tasks and instruction-following scenarios, striking a…

Read MoreIBM AI Releases Granite 4.0 Tiny Preview: A Compact Open-Language Model Optimized for Long-Context and Instruction Tasks

Oversight at Scale Isn’t Guaranteed: MIT Researchers Quantify the Fragility of Nested AI Supervision with New Elo-Based Framework

Frontier AI companies show advancement toward artificial general intelligence (AGI), creating a need for techniques to ensure these powerful systems remain controllable and beneficial. A major approach to this challenge involves methods like Recursive Reward Modeling, Iterated Amplification, and Scalable…

Read MoreOversight at Scale Isn’t Guaranteed: MIT Researchers Quantify the Fragility of Nested AI Supervision with New Elo-Based Framework