Tag: AI

Your ideas matter more than your prompts! This tutorial will show you how to use the documentation from a variety of AI video models to be able to write better prompts for text-to-video generators. Pour your creative energy into your ideas and storytelling rather than crafting a prompt. In this tutorial, I show how to use DeepSeek, ChatGPT, and Google Gemini to write better AI video prompts using documentation from Runway, Veo, Hailuo, Kling, Luma Dream Machine, and Vidu. This workflow keeps me focused on what matters most — the idea, the perspective, the story.

The noise problem that made quantum computers too unstable for real-world use? SOLVED. MIT and the Niels Bohr Institute just cracked real-time noise correction that could unleash quantum systems with MILLIONS of qubits.

We’re talking about computational power that makes today’s supercomputers look like pocket calculators. Drug discovery, climate modeling, financial predictions – everything is about to change.

This isn’t sci-fi speculation. This is happening RIGHT NOW, and the companies who move first will own the next decade.

I’ll walk you through how Marble works, show off examples (from noir detective offices to wild vacation spots I can’t afford), and even break down how I built a short film entirely inside World Labs. You’ll see the workflow—from environments and characters, to AI clean-up tools like Rev, Vo3, and Topaz Astra, all the way into Premiere Pro.

Get the LLM to help you optimize prompting.

In this video, I’ll walk you through my favorite workflows using tools like Veo 3, Heygen, and Runway Act Two. Whether you’re making short clips, dubbing videos, or testing out realistic character animation, these methods will help you create believable lip sync results with AI.

The AI video and image space just keeps getting wilder—Reve drops conversational image editing, Veo-3 “goes free” (sort of), and even HiggsField joins the free train. Today we’re diving into all of it: from cinematic image tests to recreating movie shots, face swaps, community showcases, and new features you don’t want to miss.

If you’re into AI filmmaking, image editing, or creative workflows, this breakdown is packed with examples, tips, and behind-the-scenes tests you can apply to your own projects.

Humanoid robots are suddenly everywhere, but why? In this episode, we explore the state of the art in both the US and China.

AI is here to stay, but has the current generation of Large Language Models caused an AI bubble? In today’s video I have five signs that the answer to this question is “yes”.

Google just shocked the AI world with a model that’s tiny, offline, and still breaking records. EmbeddingGemma has only 308 million parameters but beats models twice its size on the toughest benchmarks. It runs in under 200MB of RAM, works fully offline on phones and laptops, and understands over 100 languages — all while delivering blazing-fast embeddings in under 15 milliseconds. With Matryoshka learning, it scales down vectors without losing power, making it perfect for private search, RAG pipelines, and fine-tuning on everyday GPUs. This might be Google’s most practical AI release yet.

Example of an AI host promoting self-employment and her own course.