In this tutorial, we will learn how to deploy a fully functional Model Context Protocol (MCP) server using smithery as the configuration framework and VeryaX as the runtime orchestrator. We’ll walk through installing and configuring…
MCP-Use is an open-source library that lets you connect any LLM to any MCP server, giving your agents tool access like web browsing, file operations, and more — all without relying on closed-source clients. In this tutorial, we’ll use langchain-groq…
LLMs have gained outstanding reasoning capabilities through reinforcement learning (RL) on correctness rewards. Modern RL algorithms for LLMs, including GRPO, VinePPO, and Leave-one-out PPO, have moved away from traditional PPO approaches by eliminating the learned value function network in favor…
OpenAI has released HealthBench, an open-source evaluation framework designed to measure the performance and safety of large language models (LLMs) in realistic healthcare scenarios. Developed in collaboration with 262 physicians across 60 countries and 26 medical specialties, HealthBench addresses the…
Video-LLMs process whole pre-recorded videos at once. However, applications like robotics and autonomous driving need causal perception and interpretation of visual information online. This fundamental mismatch shows a limitation of current Video-LLMs, as they are not naturally designed to operate…
In this tutorial, we will guide you step-by-step through creating and publishing a sleek, modern AI blogging website using Lovable.dev. Lovable.dev simplifies website creation, enabling users to effortlessly develop visually appealing and responsive web pages tailored to specific niches, like…
Artificial intelligence has grown beyond language-focused systems, evolving into models capable of processing multiple input types, such as text, images, audio, and video. This area, known as multimodal learning, aims to replicate the natural human ability to integrate and interpret…
As language models scale in parameter count and reasoning complexity, traditional centralized training pipelines face increasing constraints. High-performance model training often depends on tightly coupled compute clusters with fast interconnects, which are costly, limited in availability, and prone to scalability…
The current generation of AI agents has made significant progress in automating backend tasks such as summarization, data migration, and scheduling. While effective, these agents typically operate behind the scenes—triggered by predefined workflows and returning results without user involvement. However,…
Audio diffusion models have achieved high-quality speech, music, and Foley sound synthesis, yet they predominantly excel at sample generation rather than parameter optimization. Tasks like physically informed impact sound generation or prompt-driven source separation require models that can adjust explicit,…
