Tutorials

Auto Added by WPeMatico

An Implementation of IWE’s Context Bridge as an AI-Powered Knowledge Graph with Agentic RAG, OpenAI Function Calling, and Graph Traversal

agentic ai, ai, AI (Artificial Intelligence), Artificial Intelligence, Editors Pick, Knowledge Graphs, Machine Learning, Staff, Technology, Tutorials

In this tutorial, we implement IWE: an open-source, Rust-powered personal knowledge management system that treats markdown notes as a navigable knowledge graph. Since IWE is a CLI/LSP tool designed for local editors. We build a realistic developer knowledge base from scratch, wire up wiki-links and markdown links into a directed graph, and then walk through […]

An Implementation of IWE’s Context Bridge as an AI-Powered Knowledge Graph with Agentic RAG, OpenAI Function Calling, and Graph Traversal Read More »

A Coding Implementation to Run Qwen3.5 Reasoning Models Distilled with Claude-Style Thinking Using GGUF and 4-Bit Quantization

agentic ai, ai, AI (Artificial Intelligence), Artificial Intelligence, Editors Pick, Large Language Model, Staff, Technology, Tutorials

In this tutorial, we work directly with Qwen3.5 models distilled with Claude-style reasoning and set up a Colab pipeline that lets us switch between a 27B GGUF variant and a lightweight 2B 4-bit version with a single flag. We start by validating GPU availability, then conditionally install either llama.cpp or transformers with bitsandbytes, depending on

A Coding Implementation to Run Qwen3.5 Reasoning Models Distilled with Claude-Style Thinking Using GGUF and 4-Bit Quantization Read More »

How to Build a Vision-Guided Web AI Agent with MolmoWeb-4B Using Multimodal Reasoning and Action Prediction

agentic ai, ai, AI (Artificial Intelligence), AI Agents, Artificial Intelligence, Editors Pick, Tutorials

In this tutorial, we explore MolmoWeb, Ai2’s open multimodal web agent that understands and interacts with websites directly from screenshots, without relying on HTML or DOM parsing. We set up the full environment in Colab, load the MolmoWeb-4B model with efficient 4-bit quantization, and build the exact prompting workflow that lets the model reason about

How to Build a Vision-Guided Web AI Agent with MolmoWeb-4B Using Multimodal Reasoning and Action Prediction Read More »

Paged Attention in Large Language Models LLMs

ai, AI (Artificial Intelligence), AI Shorts, Applications, Artificial Intelligence, Editors Pick, Language Model, Large Language Model, Machine Learning, Staff, Technology, Tutorials

When running LLMs at scale, the real limitation is GPU memory rather than compute, mainly because each request requires a KV cache to store token-level data. In traditional setups, a large fixed memory block is reserved per request based on the maximum sequence length, which leads to significant unused space and limits concurrency. Paged Attention

Paged Attention in Large Language Models LLMs Read More »

A Coding Implementation to Design Self-Evolving Skill Engine with OpenSpace for Skill Learning, Token Efficiency, and Collective Intelligence

agentic ai, ai, AI (Artificial Intelligence), Artificial Intelligence, Editors Pick, Staff, Tutorials

In this tutorial, we explore OpenSpace, a self-evolving skill engine developed by HKUDS that makes AI agents smarter, more cost-efficient, and capable of learning from every task they perform. We walk through the complete lifecycle of OpenSpace: from installing and configuring an OpenAI model, to executing cold-start tasks where no prior skills exist, watching the

A Coding Implementation to Design Self-Evolving Skill Engine with OpenSpace for Skill Learning, Token Efficiency, and Collective Intelligence Read More »

How to Design a Production-Ready AI Agent That Automates Google Colab Workflows Using Colab-MCP, MCP Tools, FastMCP, and Kernel Execution

agentic ai, ai, AI (Artificial Intelligence), AI Agents, Artificial Intelligence, Editors Pick, Model Context Protocol (MCP), Tutorials

In this tutorial, we build an advanced, hands-on tutorial around Google’s newly released colab-mcp, an open-source MCP (Model Context Protocol) server that lets any AI agent programmatically control Google Colab notebooks and runtimes. Across five self-contained snippets, we go from first principles to production-ready patterns. We start by constructing a minimal MCP tool registry from

How to Design a Production-Ready AI Agent That Automates Google Colab Workflows Using Colab-MCP, MCP Tools, FastMCP, and Kernel Execution Read More »

How BM25 and RAG Retrieve Information Differently?

ai, AI (Artificial Intelligence), Artificial Intelligence, Editors Pick, RAG, Staff, Technology, Tutorials

When you type a query into a search engine, something has to decide which documents are actually relevant — and how to rank them. BM25 (Best Matching 25), the algorithm powering search engines like Elasticsearch and Lucene, has been the dominant answer to that question for decades.  It scores documents by looking at three things:

How BM25 and RAG Retrieve Information Differently? Read More »

Implementing Deep Q-Learning (DQN) from Scratch Using RLax JAX Haiku and Optax to Train a CartPole Reinforcement Learning Agent

agentic ai, ai, AI (Artificial Intelligence), AI Agents, Artificial Intelligence, Editors Pick, Reinforcement Learning, Staff, Technology, Tutorials

In this tutorial, we implement a reinforcement learning agent using RLax, a research-oriented library developed by Google DeepMind for building reinforcement learning algorithms with JAX. We combine RLax with JAX, Haiku, and Optax to construct a Deep Q-Learning (DQN) agent that learns to solve the CartPole environment. Instead of using a fully packaged RL framework,

Implementing Deep Q-Learning (DQN) from Scratch Using RLax JAX Haiku and Optax to Train a CartPole Reinforcement Learning Agent Read More »

A Coding Implementation for Building and Analyzing Crystal Structures Using Pymatgen for Symmetry Analysis, Phase Diagrams, Surface Generation, and Materials Project Integration

ai, AI (Artificial Intelligence), Artificial Intelligence, Editors Pick, Machine Learning, Quantum Machine Learning, Staff, Technology, Tutorials

In this tutorial, we explore the capabilities of the pymatgen library for computational materials science using Python. We begin by constructing crystal structures such as silicon, sodium chloride, and a LiFePO₄-like material, and then investigate their lattice properties, densities, and compositions. Also, we analyze symmetry using space-group detection, examine atomic coordination environments, and apply oxidation-state

A Coding Implementation for Building and Analyzing Crystal Structures Using Pymatgen for Symmetry Analysis, Phase Diagrams, Surface Generation, and Materials Project Integration Read More »

Safely Deploying ML Models to Production: Four Controlled Strategies (A/B, Canary, Interleaved, Shadow Testing)

ai, AI (Artificial Intelligence), AI Shorts, Applications, Artificial Intelligence, Editors Pick, Machine Learning, Staff, Tech News, Technology, Tutorials

Deploying a new machine learning model to production is one of the most critical stages of the ML lifecycle. Even if a model performs well on validation and test datasets, directly replacing the existing production model can be risky. Offline evaluation rarely captures the full complexity of real-world environments—data distributions may shift, user behavior can

Safely Deploying ML Models to Production: Four Controlled Strategies (A/B, Canary, Interleaved, Shadow Testing) Read More »