AI Notes

Learn a lot

Tag: code

  • Agentic AI using Autonomous Platforms (n8n, make, zapier)

    Agentic AI using Autonomous Platforms (e.g., n8n) (2025) In 2025, the convergence of Agentic AI and Autonomous Platforms like n8n is revolutionizing automation. Agentic AI refers to AI systems capable of perceiving their environment, making decisions, and taking actions to achieve specific goals without constant human intervention. When integrated with autonomous platforms, these agents can… Read more

  • Comparing Autonomous platforms: n8n vs Make vs Zapier

    Comparing n8n vs. Make (formerly Integromat) vs. Zapier (2025) n8n, Make (formerly Integromat), and Zapier are leading visual workflow automation platforms in 2025, empowering users to connect applications and automate tasks without coding. Each platform offers a unique set of features, pricing models, and approaches to automation. Key Differences and Features: Feature n8n Make (formerly… Read more

  • Comparing workflow automation platforms n8n vs Make

    Comparing n8n vs. Make (formerly Integromat) (2025) n8n and Make (formerly Integromat) are both visual workflow automation platforms that enable you to connect apps and automate tasks without code. While they share the goal of automation, they have distinct approaches and features that cater to different user profiles and needs in 2025. Key Differences and… Read more

  • n8n vs Zapier: A Comparison of Automation Platforms

    n8n vs. Zapier (2025) n8n and Zapier are both powerful workflow automation platforms that allow you to connect different apps and automate repetitive tasks without writing code. However, they have distinct characteristics that cater to different user needs and technical expertise in 2025. Key Differences and Features: Feature n8n Zapier Hosting Self-hostable (on your own… Read more

  • Extending n8n with Custom Code

    Extending n8n with Custom Code (2025) n8n’s flexibility extends beyond its pre-built nodes through the ability to incorporate custom code directly within your workflows. This allows you to implement highly specific logic, interact with APIs in unique ways, or perform data transformations that aren’t readily available through existing nodes in 2025. Key Ways to Add… Read more

  • Top 30 Sites to Learn New Technologies

    Top 30 Sites to Learn New Technologies – Details Here are 30 excellent platforms where you can acquire new technological skills, encompassing various learning styles and areas of focus: Comprehensive Learning Platforms: Coursera Extensive catalog of courses, Specializations, and degrees from universities and institutions globally. edX University-level courses and programs across various disciplines, including technology… Read more

  • CQRS (Command Query Responsibility Segregation) Design Pattern

    CQRS Design Pattern The CQRS (Command Query Responsibility Segregation) design pattern separates read and write operations for a data store into distinct models. This means that the operations that modify the state of the system (Commands) are handled by one set of models, and the operations that retrieve data (Queries) are handled by a different… Read more

  • Details of Vector Embeddings

    Details of Vector Embeddings Vector embeddings are numerical representations of data points (such as words, sentences, images, or even abstract concepts) in a multi-dimensional space. The core idea is to translate complex information into a list of numbers (a vector) that captures the underlying meaning, features, and relationships of the data. Multi-dimensional Space: Embeddings exist… Read more

  • Pseudo Code for Trie Data Structure

    Pseudo Code for Trie Data Structure // Trie Data Structure Class TrieNode: isEndOfWord: Boolean // Indicates if this node marks the end of a valid word children: Dictionary<Character, TrieNode> // Maps characters to child nodes Constructor(): isEndOfWord = False children = new empty Dictionary Class Trie: root: TrieNode Constructor(): root = new TrieNode() // Insert… Read more

  • Algorithms for Vector Embeddings

    Here are some of the most common algorithms used for generating vector embeddings, particularly in Natural Language Processing (NLP): 1. Word2Vec (2013) Developed by: Google. Approach: Predicts a word given its context (Continuous Bag of Words – CBOW) or predicts the surrounding context words given a word (Skip-gram). Key Idea: Words appearing in similar contexts… Read more

  • Efficient String Search algorithms among Millions of Strings

    Efficient String Search in a Large List (2025) Searching for a specific string within a list containing millions of entries requires efficient algorithms and data structures to avoid performance bottlenecks. A simple linear search would be highly inefficient in this scenario. Here are several efficient ways to tackle this problem in 2025: 1. Using a… Read more

  • Multi-Threaded Programming in Java

    Multi-Threaded Programming in Java (2025) Java has robust built-in support for multi-threaded programming, allowing developers to execute multiple parts of a program concurrently. This is crucial for building responsive, scalable, and efficient applications that can leverage multi-core processors effectively in 2025. Understanding Threads in Java Threads: In Java, a thread is a lightweight sub-process, a… Read more

  • Multi-Threaded Programming in Node.js

    Multi-Threaded Programming in Node.js (2025) While Node.js has been traditionally known for its single-threaded, non-blocking event loop architecture, it has evolved to incorporate multi-threading capabilities to leverage multi-core processors effectively, especially for CPU-bound tasks. This is primarily achieved through the worker_threads module, introduced in Node.js 10.5.0 and becoming increasingly important in 2025 for building performant… Read more

  • Multi-Threaded Programming in Python

    Multi-Threaded Programming in Python (2025) Multi-threaded programming in Python allows you to run multiple parts of your program concurrently within a single process. This can be beneficial for tasks that involve waiting for external resources (like network requests or file I/O), potentially improving the overall responsiveness of your application. However, due to Python’s Global Interpreter… Read more

  • Design Concepts to Build Flawless Applications

    Smart Design Tricks for Building Applications (2025) Building successful applications in 2025 requires more than just functionality; smart design choices can significantly enhance user experience, maintainability, and scalability. Here are some key design tricks to consider: User Experience (UX) Focused Tricks Prioritize Mobile-First (or Responsive from the Start): With diverse screen sizes, designing for mobile… Read more

  • n8n Integrations with external services

    n8n Existing Integrations n8n boasts a wide array of built-in integrations, allowing you to connect and automate workflows with numerous popular applications and services in 2025. These integrations are constantly expanding, making n8n a versatile tool for various automation needs. Core Nodes (Built-in): HTTP Request: For making generic API calls to any RESTful or GraphQL… Read more

  • GraphQL vs RESTful for Agentic AI

    GraphQL vs RESTful for Agentic AI Both RESTful and GraphQL APIs can be used to build agentic AI systems, and the choice between them depends on the specific requirements and characteristics of the AI agent and the systems it interacts with. Here’s a comparison of their suitability: RESTful APIs for Agentic AI: Pros: Simplicity and… Read more

  • Building Agentic AI applications Using n8n

    Building Agentic AI Using n8n n8n, a powerful open-source workflow automation platform, can be effectively leveraged to build various components and orchestrate the functionalities of agentic AI systems in 2025. While n8n itself isn’t a machine learning framework for training AI models, its ability to connect different services, handle data transformations, and manage complex workflows… Read more

  • Rapid Prototyping Using AI Tools

    Rapid Prototyping Using AI Tools In 2025, Artificial Intelligence (AI) tools are significantly accelerating the rapid prototyping process across various domains, from software and product design to content creation and even biological engineering. These tools enable faster iteration, reduced development costs, and the exploration of a wider range of design possibilities. How AI Facilitates Rapid… Read more

  • Top 50 Websites in AI Technology (April 2025)

    Top 50 Websites in AI Technology (April 2025) The field of Artificial Intelligence is vast and rapidly expanding. Here is an extended list of 50 prominent websites covering various aspects of AI technology, including news, research, tools, education, and communities, as of April 2025: OpenAI (openai.com) Organization behind ChatGPT, DALL-E, and leading AI research. Google… Read more

  • The Cost Implications of Monolithic Architectures

    Whether a monolithic architecture is a cost saver is a nuanced question with no definitive yes or no answer. It largely depends on the specific context, the size and complexity of the application, the development team’s expertise, and the application’s long-term evolution. Potential Initial Cost Savings of Monoliths: Potential Long-Term Cost Increases of Monoliths: Conclusion:… Read more

  • Building Agentic AI Applications on Microsoft Azure

    Microsoft Azure offers a rich set of services and tools for building agentic AI applications – intelligent systems capable of autonomous action, planning, memory, and interaction with their environment. This detailed guide outlines key Azure services, their functionalities, and relevant links to help you get started, formatted for your WordPress site. Core Foundation Models Agent… Read more

  • Building Agentic AI Applications on Google Cloud Platform (GCP)

    Google Cloud Platform (GCP) offers a rapidly evolving suite of tools and services for building agentic AI applications – intelligent systems capable of autonomous action, planning, memory, and interaction with their environment. Here’s a detailed overview of key GCP services and concepts, along with relevant links, formatted for your WordPress site. Core Foundation Models Agent… Read more

  • Top 8 Essential Data Structures You Should Know

    Data structures are fundamental building blocks in computer science, enabling efficient organization and manipulation of data. Understanding these structures is crucial for writing effective and performant code. Here are eight of the most commonly used data structures: 1. Arrays (and Python Lists) An array is a contiguous block of memory used to store a collection… Read more