Node-RED is a powerful flow-based programming tool that makes wiring together hardware devices, APIs, and online services remarkably simple. Whether you’re building IoT projects, automating workflows, or creating integrations between services, Node-RED provides a browser-based visual editor that lets you connect nodes with just a few clicks. In this guide, we’ll walk through installing Node-RED locally and then use Pinggy to make it accessible from anywhere on the internet. This setup is perfect for developers, IoT builders, automation engineers, and anyone who wants to access their Node-RED flows remotely or receive webhooks from external services.

Face swapping technology has become increasingly popular for creative projects, entertainment, and exploring the capabilities of AI-powered image manipulation. While there are many commercial face swap applications available, building your own gives you complete control over the process and costs nothing to run. In this guide, we’ll show you how to create a fully functional face swap application using Google Colab and make it publicly accessible using Pinggy. This setup leverages InsightFace’s powerful face detection and swapping models along with a Gradio-based user interface, all running on Google Colab’s free GPU resources.

AI video generation has transformed from a novelty into a production-ready tool in 2026. What began as blurry, seconds-long clips with obvious artifacts has evolved into cinematic-quality footage with realistic physics, coherent motion, and synchronized audio. Whether you’re a filmmaker exploring new creative possibilities, a marketer scaling content production, or a developer building video-powered applications, today’s AI video models offer capabilities that were unimaginable just two years ago. The most significant developments this year include native 4K output, videos extending to 20+ seconds, synchronized audio generation, and dramatically improved physics simulation.

The command line has always been the natural habitat for developers who value speed, efficiency, and control. In 2026, CLI-based AI coding agents have evolved from simple code completion tools into sophisticated autonomous assistants that can plan, write, debug, and deploy entire features directly from your terminal. Unlike IDE-based extensions that require switching between windows and interfaces, CLI coding agents integrate seamlessly into terminal-first workflows. They understand your entire codebase, execute commands, manage Git operations, and coordinate changes across multiple files all while you stay in the environment you know best.

n8n has become a popular choice for workflow automation, offering a fair-code approach that gives developers the flexibility of code with the speed of no-code. With over 500+ integrations and native AI capabilities, it’s helped countless teams automate their processes. However, as your automation needs grow or change, you might find yourself looking for alternatives that better fit your specific requirements. Whether you’re seeking simpler setup, more integrations, better pricing, or enhanced enterprise features, there are several excellent alternatives to n8n available in 2026.

Cloud-based note-taking apps are convenient, but they come with trade-offs: recurring subscription fees, privacy concerns, and vendor lock-in. What if you could have a powerful, modern note-taking experience while keeping complete control of your data? That’s exactly what Memos offers an open-source, self-hosted note-taking service that puts privacy first. In this guide, we’ll walk through setting up Memos using Docker and then use Pinggy to make it accessible from anywhere on the internet.

Building a payment integration with PayPal requires handling webhooks to receive real-time notifications about transactions, disputes, subscriptions, and other payment events. However, testing webhooks during local development presents a significant challenge: PayPal needs to send HTTP requests to your server, which means your localhost isn’t directly reachable. In this guide, you’ll learn how to set up and test PayPal webhooks locally using Pinggy, a simple tunneling tool that exposes your local server to the internet with just one command.

Scientific research has entered a new era with AI models that can search, analyze, and synthesize research papers at unprecedented speed. Whether you’re conducting a literature review, writing a research paper, or trying to understand complex scientific findings, these AI tools can dramatically accelerate your workflow while maintaining academic rigor. The key differentiator for research-focused AI tools is their deep research mode the ability to autonomously search through academic databases, analyze multiple papers, identify patterns across studies, and synthesize findings with proper citations.

Text-to-speech (TTS) technology has become incredibly powerful, but accessing high-quality voice synthesis usually means paying for expensive APIs or running resource-intensive models on local hardware. What if you could build and host your own TTS application with studio-quality voices, all running for free in the cloud? That’s exactly what we’ll accomplish using Google Colab, Kokoro TTS, and Pinggy. In this guide, we’ll build a complete text-to-speech web application using the Kokoro TTS model - a lightweight yet powerful model that delivers natural-sounding speech across multiple languages and voices.

The internet was designed with a simple, elegant principle: every device should be able to communicate directly with every other device. This “end-to-end principle” formed the foundation of the original internet architecture, enabling innovation and seamless connectivity. However, the explosive growth of internet-connected devices quickly exhausted the limited IPv4 address space, forcing the adoption of Network Address Translation (NAT) as a stopgap solution. While NAT allowed the internet to continue functioning, it fundamentally broke the end-to-end model and introduced a host of complications for modern applications.