Author: GW Alger

Curious about how Generative AI models like Stable Diffusion work? Join me for a short whiteboard animation where we will explore the basics. In just under 10 minutes, we’ll discuss how Deep Learning and Neural Networks are employed to train these models, and how they generate images. Whether you’re new to the field or seeking a deeper understanding of these models in a non-mathematical way, this video provides an accessible overview of Stable Diffusion’s fascinating mechanisms.

Break free from closed-source projects like Adobe Firefly, DALL-E, and Midjourney and discover the open-source revolution that empowers creativity. Join me on a captivating journey into the heart of innovation with ComfyUI and Stable Diffusion!

AI was supposed to make smarter decisions. Instead, it may be making leaders more dangerous.

Studies from Harvard and MIT found that professionals using AI often performed worse when tasks moved outside the AI’s comfort zone. Why? Because models like ChatGPT, Gemini, and Grok aren’t optimized for truth. They’re optimized for engagement. Rather than challenging bad ideas, they frequently reinforce them, acting less like expert advisors and more like digital yes-men.

From lawyers submitting AI-generated fake court cases to executives using chatbots to validate flawed business strategies, the problem keeps repeating itself. The more confident the user, the more convincing the AI becomes. It mirrors assumptions, amplifies biases, and presents speculation as fact.

In this video, we’ll uncover how AI companies accidentally trained their models to prioritize approval over accuracy, why businesses are becoming increasingly worried about AI-driven decision making, and how a technology designed to help humans think may actually be making critical mistakes harder to spot.

The biggest threat isn’t that AI becomes smarter than us. It’s that we stop questioning it.

Max Novak provides a comprehensive walkthrough on setting up the open-source, node-based ComfyUI environment locally. This guide details essential hardware requirements, the installation of the manager and custom nodes, and demonstrates how to navigate various workflows for efficient AI-powered image and video generation.

Theoretically Media explores the latest technical specifications of Seedance 2.5, including extended shot lengths and enhanced multimodal reference capabilities. Alongside this, the segment details the rollout of native 4K generation for Seedance 2.0 and previews Omni Director, a promising research-based feature for advanced camera control coming to the platform.

Learn how to use ComfyUI step by step in this beginner-friendly tutorial. ComfyUI is one of the most popular free and open-source AI tools for generating images, creating videos, enhancing photos, and building powerful AI workflows using a visual node-based interface.

In this tutorial, you’ll learn how to install ComfyUI, download and set up your first AI model, generate AI images from text prompts, understand how nodes and workflows work, add an image upscaling node, save custom workflows, and explore the built-in template library.

Whether you’re completely new to AI image generation or looking to understand how ComfyUI workflows are built, this guide will help you get up and running quickly.

Kyle Cook examines the “doorman fallacy” to illustrate how misjudging the core value of professional roles can harm long-term organizational success. By comparing software development to hotel management, this analysis highlights why prioritizing technical quantity over architectural strategy often leads to significant, hidden costs.

In this video, you’ll learn about the top free AI image upscalers of 2025, tested side by side to find the best results. We compare tools like ILoveIMG, Upscale Media, and Upscayl to evaluate their quality, features, and ease of use. Each tool is tested against a premium $200 image upscaling software to see how they measure up. Whether you’re looking for a quick online solution or a feature-packed desktop app, this guide will help you choose the best free upscaler for your needs!

Over the past few months our team has been building the Kiraa Engine and the missing software framework that lets Apple silicon do what it’s actually capable of. Apple has the best hardware on the market, but the software gap has been holding it back. So we wrote hundreds of thousands of lines of optimised code to close it.

Now we’re releasing two projects as open source, and inviting you to build with them.

SwiftPandas is a native port of Python’s pandas, with performance uplifts of up to 80x. Jobs that used to take days now take hours.
Project Onyx is a lightweight LLM that runs entirely on device. It proves you can get solid output quality and fast response times without ever touching the cloud.

We’re opening these up because the more developers building on device, the faster the world realises that cloud AI is a bad idea. Expensive, risky, and unnecessary when fast, cheap and secure models can run right on your own hardware.

If you’re building something interesting with SwiftPandas or Project Onyx, I want to see it. Accelerated an old pandas workflow?