Welcome to M5BMachine 5-Minute Briefing

In this tutorial, we build a complete AgentScope workflow from the ground up and run everything in Colab. We start by wiring OpenAI through AgentScope and validating a basic model call to understand how messages and responses are handled. From there, we define custom tool functions, register them in...

In this tutorial, we build and run a Colab workflow for Gemma 3 1B Instruct using Hugging Face Transformers and HF Token, in a practical, reproducible, and easy-to-follow step-by-step manner. We begin by installing the required libraries, securely authenticating with our Hugging Face token, and load...

In this tutorial, we work directly with the A-Evolve framework in Colab and build a complete evolutionary agent pipeline from the ground up. We set up the repository, configure an OpenAI-powered agent, define a custom benchmark, and build our own evolution engine to see how A-Evolve actually improve...

In this tutorial, we build and explore the CAI Cybersecurity AI Framework step by step in Colab using an OpenAI-compatible model. We begin by setting up the environment, securely loading the API key, and creating a base agent. We gradually move into more advanced capabilities such as custom function...

As Google integrates AI capabilities across its product suite, a new technical entity has surfaced in server logs: Google-Agent. For software devs, understanding this entity is critical for distinguishing between automated indexers and real-time, user-initiated requests. Unlike the autonomous crawle...

In this tutorial, we take a deep dive into nanobot, the ultra-lightweight personal AI agent framework from HKUDS that packs full agent capabilities into roughly 4,000 lines of Python. Rather than simply installing and running it out of the box, we crack open the hood and manually recreate each of it...

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 ...

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...

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 docume...

In this tutorial, we explore how to solve differential equations and build neural differential equation models using the Diffrax library. We begin by setting up a clean computational environment and installing the required scientific computing libraries such as JAX, Diffrax, Equinox, and Optax. We t...

In this tutorial, we explore how to use NVIDIA Warp to build high-performance GPU and CPU simulations directly from Python. We begin by setting up a Colab-compatible environment and initializing Warp so that our kernels can run on either CUDA GPUs or CPUs, depending on availability. We then implemen...

In this tutorial, we build a workflow using Outlines to generate structured and type-safe outputs from language models. We work with typed constraints like Literal, int, and bool, and design prompt templates using outlines.Template, and enforce strict schema validation with Pydantic models. We also ...

What if AI-assisted coding became more reliable by separating product planning, engineering review, release, and QA into distinct operating modes? That is the idea behind Garry Tan’s gstack, an open-source toolkit that packages Claude Code into 8 opinionated workflow skills backed by a persistent br...

In recent times, many developments in the agent ecosystem have focused on enabling AI agents to interact with external tools and access domain-specific knowledge more effectively. Two common approaches that have emerged are skills and MCPs. While they may appear similar at first, they differ in how ...

In this tutorial, we implement a Colab-ready version of the AutoResearch framework originally proposed by Andrej Karpathy. We build an automated experimentation pipeline that clones the AutoResearch repository, prepares a lightweight training environment, and runs a baseline experiment to establish ...

In this tutorial, we build a Streaming Decision Agent that thinks and acts in an online, changing environment while continuously streaming safe, partial reasoning updates. We implement a dynamic grid world with moving obstacles and a shifting goal, then use an online A* planner in a receding-horizon...

In this tutorial, we build a Meta-Agent that designs other agents automatically from a simple task description. We implement a system that analyzes the task, selects tools, chooses a memory architecture, configures a planner, and then instantiates a fully working agent runtime. We go beyond static a...

In this tutorial, we build an advanced agent system that goes beyond simple response generation by integrating an internal critic and uncertainty estimation framework. We simulate multi-sample inference, evaluate candidate responses across accuracy, coherence, and safety dimensions, and quantify pre...

In the frantic arms race of ‘AI for code,’ we’ve moved past the era of the glorified autocomplete. Today, Anthropic is double-downing on a more ambitious vision: the AI agent that doesn’t just write your boilerplate, but actually understands why your Kubernetes cluster is screaming at 3:00 AM. With ...

Large Language Models (LLMs) are the world’s best mimics, but when it comes to the cold, hard logic of updating beliefs based on new evidence, they are surprisingly stubborn. A team of researchers from Google argue that the current crop of AI agents falls far short of ‘probabilistic reasoning’—the a...

In this tutorial, we build a complete pipeline for single-cell RNA sequencing analysis using Scanpy. We start by installing the required libraries and loading the PBMC 3k dataset, then perform quality control, filtering, and normalization to prepare the data for downstream analysis. We then identify...

In this tutorial, we explore tqdm in depth and demonstrate how we build powerful, real-time progress tracking into modern Python workflows. We begin with nested progress bars and manual progress control, then move into practical scenarios such as streaming downloads, pandas data processing, parallel...

What if the AI industry is optimizing for a goal that cannot be clearly defined or reliably measured? That is the central argument of a new paper by Yann LeCun, and his team, which claims that Artificial General Intelligence has become an overloaded term used in inconsistent ways across academia and...

In this tutorial, we implement a production-grade, large-scale graph analytics pipeline in NetworKit, focusing on speed, memory efficiency, and version-safe APIs in NetworKit 11.2.1. We generate a large-scale free network, extract the largest connected component, and then compute structural backbone...