If you are building a FiveM roleplay server, Discord Rich Presence is one of those small details that makes a big difference. It replaces the generic "Playing FiveM" status with your server name, logo, and player count. Every player on your server passively advertises your brand to their entire Discord friends list. The setup is straightforward but the implementation differs depending on your fram
The File Search tool in the Gemini API now supports multimodal retrieval by adding support for Gemini Embedding 2. This update allows images, such as charts, product photos, and diagrams, to be natively indexed and searched in the same store as your text-based documents. This post covers how to use the File Search tool end-to-end: creating a store, uploading documents and images, querying with gro
Hi everyone, my name is P Swyom Sanjog. Welcome back to my blog—I hope you’re all doing well. Today, I’m bringing a new topic: Virtual DOM. Let’s understand what the Virtual DOM is in simple terms. We’ll cover key questions like what it is, why it’s used, and how it works. So, let’s get started! Virtual Dom So, let’s break down the topic into “Virtual” and “DOM.” Virtual means something that exi
Your phone will connect to the strongest tower it hears. It does not ask for ID first. It assumes trust, and that assumption is the entire problem. I first noticed this in 2019 outside a security conference in Las Vegas. My test Android dropped from LTE to 2G for 47 seconds, then returned to normal. No user notification. The baseband logs showed a cipher downgrade to A5/0, a location area code tha
My first version of an LLM-powered Reddit reply agent generated this on a B2B SaaS post: "I've spent years helping companies like yours scale outreach and we've helped hundreds of teams achieve 70% time savings." Every word of that is fabricated. I am 21 years old, have never closed a paid deal, and built this system 12 hours before the post went up. The next 24 hours were spent making it not lie.
I Trained My Own LLM from Scratch in 2025: What That Viral HN Tutorial Doesn't Tell You About the Real Cost I was scrolling HN on a Tuesday night when I saw the post: "Train Your Own LLM from Scratch", 241 points, 87 comments, and an energy in the thread I recognized immediately — the same one from "I built my own email server" or "I replaced Docker with bash scripts" threads. A mix of genuine t
Entrené mi propio LLM desde cero en 2025: lo que el tutorial viral de HN no te dice sobre el costo real Estaba revisando HN un martes a la noche cuando vi el post: "Train Your Own LLM from Scratch", 241 puntos, 87 comentarios, y una energía en el hilo que reconocí de inmediato — la misma que tienen los threads de "construí mi propio servidor de email" o "reemplacé Docker con scripts de bash". Me
The Problem If you are building AI applications with LLMs, you know the pain: raw HTML is useless for training data. You need clean, structured Markdown. Most solutions like Firecrawl or Crawl4AI require setup, dependencies, and often paid plans. You could write your own parser: import re import urllib.request def html_to_markdown(url): html = urllib.request.urlopen(url).read().decode()