Building a Multi-Node Graph-Based AI Agent Framework for Complex Task Automation

In this tutorial, we guide you through the development of an advanced Graph Agent framework, powered by the Google Gemini API. Our goal is to build intelligent, multi-step agents that…

URBAN-SIM: Advancing Autonomous Micromobility with Scalable Urban Simulation

Micromobility solutions—such as delivery robots, mobility scooters, and electric wheelchairs—are rapidly transforming short-distance urban travel. Despite their growing popularity as flexible, eco-friendly transport alternatives, most micromobility devices still rely heavily…

REST: A Stress-Testing Framework for Evaluating Multi-Problem Reasoning in Large Reasoning Models

Large Reasoning Models (LRMs) have rapidly advanced, exhibiting impressive performance in complex problem-solving tasks across domains like mathematics, coding, and scientific reasoning. However, current evaluation approaches primarily focus on single-question…

How Memory Transforms AI Agents: Insights and Leading Solutions in 2025

The importance of memory in AI agents cannot be overstated. As artificial intelligence matures from simple statistical models to autonomous agents, the ability to remember, learn, and adapt becomes…

NVIDIA AI Releases GraspGen: A Diffusion-Based Framework for 6-DOF Grasping in Robotics

Robotic grasping is a cornerstone task for automation and manipulation, critical in domains spanning from industrial picking to service and humanoid robotics. Despite decades of research, achieving robust, general-purpose 6-degree-of-freedom…

Google DeepMind Introduces Aeneas: AI-Powered Contextualization and Restoration of Ancient Latin Inscriptions

The discipline of epigraphy, focused on studying texts inscribed on durable materials like stone and metal, provides critical firsthand evidence for understanding the Roman world. The field faces numerous challenges…

RoboBrain 2.0: The Next-Generation Vision-Language Model Unifying Embodied AI for Advanced Robotics

Advancements in artificial intelligence are rapidly closing the gap between digital reasoning and real-world interaction. At the forefront of this progress is embodied AI—the field focused on enabling robots to…

Building a GPU-Accelerated Ollama LangChain Workflow with RAG Agents, Multi-Session Chat Performance Monitoring

In this tutorial, we build a GPU‑capable local LLM stack that unifies Ollama and LangChain. We install the required libraries, launch the Ollama server, pull a model, and wrap it…

EraRAG: A Scalable, Multi-Layered Graph-Based Retrieval System for Dynamic and Growing Corpora

Large Language Models (LLMs) have revolutionized many areas of natural language processing, but they still face critical limitations when dealing with up-to-date facts, domain-specific information, or complex multi-hop reasoning. Retrieval-Augmented…

FEEDER: A Pre-Selection Framework for Efficient Demonstration Selection in LLMs

LLMs have demonstrated exceptional performance across multiple tasks by utilizing few-shot inference, also known as in-context learning (ICL). The main problem lies in selecting the most representative demonstrations from large…