AI image models are insanely good now. But they still can’t reliably draw one thing... Hands. Seriously! Ask your favorite AI tool to generate a picture of a human hand. WHY DOES IT HAVE SIX FINGERS?! Ok, sometimes AI gets it right… But hands and fingers are still one of the most consistent failures in image generation. And that actually tells us something important about how these models work. You see, AI image tools don’t “draw” images. They don’t search Google. And they don’t copy-paste anything. So then what are they actually doing? Well, they’re built using something called diffusion models. It’s a bit complicated, but basically diffusion models learn to remove noise. Here's how: Take a real image. Add static. More static. MORE. Usually 50 layers of static until you’re left with pure TV noise. The AI uses math to model each step of that static layering process. But it also uses math to figure out how to run this process in reverse. Static in → image out. So when you ask ChatGPT to gender-swap your friend, it starts with total static, and removes it layer by layer until you get something… good?? And faces? Easy. Two eyes. A nose. A mouth. Roughly the same layout across millions of photos. The model has seen so many faces that it basically has them memorized. But hands?? 27 bones. 29 joints. A million valid poses. The statistical map for "hand" is enormous, which makes the mathematical variance high. So when AI reconstructs fingers from static… It’s not “drawing” them. It’s guessing what should exist based on probability. And sometimes, probability gives you six fingers... AI model labs are actively working on this problem. #AI #MachineLearning #DiffusionModels #GenerativeAI #TechExplainers

Before you containerize your SaaS, watch this. 🛑 I made a quick video explaining exactly what a container is and why your application needs one. Scale faster, deploy smoother. 📺#SaaS #Coding #TechExplainers #aivideo

8 (Closing): So no — compression isn’t “boring infra.” It’s the quiet tech keeping your favorite blockchain usable. Build smarter. Compress better. #BuildInPublic #BlockchainDev #TechExplainers #SimpleTech

Don’t start your blockchain project with “decentralize everything.” Start with: “who needs to trust who?”#SimpleTech #TechExplainers #BlockchainSimplified

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As #tech keeps evolving, it's important to have an understanding of different technologies and how they work. You can learn more about #blockchain technology in our #TechExplainers at buff.ly/43vUN7M

Greater knowledge of #tech issues leads to better #techpolicy! That's why our #TechExplainers are a fantastic resource for policymakers. Gain understanding about #quantamcomputing w/ Michelle Simmons @CQC2T_ on our website or #TechMirror pod! techpolicydesign.au/tech-exp…

And how is @Twitter deciding what you see right now? #TechExplainers georgetownlawtechreview.org/…