VoltAgent is an open-source TypeScript framework designed to streamline the creation of AI‑driven applications by offering modular building blocks and abstractions for autonomous agents. It addresses the complexity of directly working with large language models (LLMs), tool integrations, and state…
Retrieval augmented generation (RAG) is one of 2025’s hot topics in the AI landscape. Source link
Designing intelligent systems that function reliably in dynamic physical environments remains one of the more difficult frontiers in AI. While significant advances have been made in perception and planning within simulated or controlled contexts, the real world is noisy, unpredictable,…
In this tutorial, we’ll build an end‑to‑end ticketing assistant powered by Agentic AI using the PydanticAI library. We’ll define our data rules with Pydantic v2 models, store tickets in an in‑memory SQLite database, and generate unique identifiers with Python’s uuid…
This post is divided into three parts; they are: • Understanding Context Vectors • Visualizing Context Vectors from Different Layers • Visualizing Attention Patterns Unlike traditional word embeddings (such as Word2Vec or GloVe), which assign a fixed vector to each…
In recent years, vision-language models (VLMs) have advanced significantly in bridging image, video, and textual modalities. Yet, a persistent limitation remains: the inability to effectively process long-context multimodal data such as high-resolution imagery or extended video sequences. Many existing VLMs…
Reliable evaluation of large language model (LLM) outputs is a critical yet often complex aspect of AI system development. Integrating consistent and objective evaluation pipelines into existing workflows can introduce significant overhead. The Atla MCP Server addresses this by exposing…
This post is divided into two parts; they are: • Contextual Keyword Extraction • Contextual Text Summarization Contextual keyword extraction is a technique for identifying the most important words in a document based on their contextual relevance. Source link
Quantization might sound like a topic reserved for hardware engineers or AI researchers in lab coats. Source link
Machine learning models are trained on historical data and deployed in real-world environments. Source link
