Tech Tips, Tricks & Trivia

If you directly paste raw Markdown syntax (like bold or # Heading), Word treats it as plain text. To get properly styled text (headings, bold, lists, tables), you need to convert or render the Markdown first. Here are some ways to maintain formatting when copying Markdown content into Microsoft Word: 1. The Preview / Rich Text Method  If you use a Markdown editor (such as VS Code, Obsidian, Typora, or Joplin), you can use its rendered preview to copy formatted text. Open your Markdown file in your editor. Toggle the Preview Mode (in VS Code , press Ctrl + Shift + V or Cmd + Shift + V). Select and highlight the rendered text in the preview pane. Copy it (Ctrl + C) and paste it directly into Microsoft Word (Ctrl + V). Word will recognize it as Rich Text, converting headers, lists, and bold text perfectly. 2. Using an Online Converter (Quickest for one-offs) If you don't use a dedicated Markdown editor, you can let a web browser do the heavy lifting: Copy your raw Markdown text. Paste...

This Week I Learned -  * Vertex AI has been rebranded and evolved. Google officially replaced and expanded it under the name Gemini Enterprise Agent Platform.  This change marks a major structural shift for Google Cloud, moving away from a traditional MLOps platform (focused on training and deploying standalone models) toward an "Agentic AI" ecosystem.   * Turkey based HubX Studios used Gemma 4 to build BetterSpeak, an AI English tutoring platform that uses the Gemma 4 E2B model as the reasoning engine for its on-device pipeline — enabling private, low-latency tutoring without the need for an internet connection. HubX deployed the 4-bit quantized version of the model to handle tasks like grammar explanations and progress monitoring across languages. By using Gemma 4’s native audio input capabilities, HubX’s app is able to support direct speech-to-speech learning , while reducing costs and ensuring privacy. * Midjourney, the AI lab best known for image generation...

The term "Big Data" peaked as a buzzword around 2012-2015 and has since faded into background terminology. It followed the classic Gartner hype cycle: explosive marketing, overpromises, disillusionment, and normalization. It's not "dead" in substance. Data volumes keep exploding, processing tools improved, and organizations still handle massive datasets daily. Market projections show the big data tech sector growing robustly into the 2030s. Claims of total irrelevance ignore that petabyte-scale work is routine now. But the phrase lost pop-culture and consultant cachet. That's the real shift. Why the term declined: Hype exhaustion and failed prophecies. Early 2010s rhetoric promised a data cataclysm requiring exotic tools (Hadoop everywhere) for revolutionary insights. The apocalypse didn't arrive at predicted scale for most orgs; hardware/cloud scaled predictably, and "whatever doesn't fit on one machine" kept shrinking as single machines g...