How can AI teams run Tinker style reinforcement learning on large language models using their own infrastructure with a single […]
Category: AI Agents
How to Design a Persistent Memory and Personalized Agentic AI System with Decay and Self-Evaluation?
In this tutorial, we explore how to build an intelligent agent that remembers, learns, and adapts to us over time. […]
DeepAgent: A Deep Reasoning AI Agent that Performs Autonomous Thinking, Tool Discovery, and Action Execution within a Single Reasoning Process
Most agent frameworks still run a predefined Reason, Act, Observe loop, so the agent can only use the tools that […]
How to Design an Autonomous Multi-Agent Data and Infrastructure Strategy System Using Lightweight Qwen Models for Efficient Pipeline Intelligence?
In this tutorial, we build an Agentic Data and Infrastructure Strategy system using the lightweight Qwen2.5-0.5B-Instruct model for efficient execution. […]
How to Build Ethically Aligned Autonomous Agents through Value-Guided Reasoning and Self-Correcting Decision-Making Using Open-Source Models
In this tutorial, we explore how we can build an autonomous agent that aligns its actions with ethical and organizational […]
Microsoft Releases Agent Lightning: A New AI Framework that Enables Reinforcement Learning (RL)-based Training of LLMs for Any AI Agent
How do you convert real agent traces into reinforcement learning RL transitions to improve policy LLMs without changing your existing […]
How Exploration Agents like Q-Learning, UCB, and MCTS Collaboratively Learn Intelligent Problem-Solving Strategies in Dynamic Grid Environments
In this tutorial, we explore how exploration strategies shape intelligent decision-making through agent-based problem solving. We build and train three […]
MiniMax Releases MiniMax M2: A Mini Open Model Built for Max Coding and Agentic Workflows at 8% Claude Sonnet Price and ~2x Faster
Can an open source MoE truly power agentic coding workflows at a fraction of flagship model costs while sustaining long-horizon […]
How to Build, Train, and Compare Multiple Reinforcement Learning Agents in a Custom Trading Environment Using Stable-Baselines3
In this tutorial, we explore advanced applications of Stable-Baselines3 in reinforcement learning. We design a fully functional, custom trading environment, […]
How to Build a Fully Functional Computer-Use Agent that Thinks, Plans, and Executes Virtual Actions Using Local AI Models
In this tutorial, we build an advanced computer-use agent from scratch that can reason, plan, and perform virtual actions using […]