What are you folks using atm for uprezzing SD film transfers and SD video to HD other than Topaz?

I’d love to hear from everyone here. As this group continues to grow, I want to make sure we’re building something that is actually useful, practical, and worth your time. So here’s the question: What would you most like to get out of this community? I want your top 3. But Skool only lets you vote once. So please add a comment with your 2nd & 3rd choices. If something's missing, tell me. This community is yours as much as it's mine. I'd rather build what you'll actually use than guess. 😉 Thanks, Larry

Stop Fighting Your AI Video Tool — Use Structured Controls Instead If you've ever spent 20 minutes rewriting a prompt to get a dolly-in shot, this one's for you. Kling 3.0 dropped this week with an AI Director mode — and it's a different philosophy than what you're used to. Instead of describing camera moves in text and hoping the model interprets it correctly, you specify the shot: • Camera movement: Dolly, pan, tilt, crane (pick from a menu, not a paragraph) • Shot type: CU, MCU, wide, OTS (cinematographer language, not prompt engineering) • Scene transitions: Cut, dissolve, match cut (built-in storyboarding) • Character consistency: Plan a multi-shot sequence, lock the character across clips This isn't better or worse than Sora/Runway/Veo — it's built for a different workflow. If you're pre-visualizing a scene or prototyping a sequence, structured controls are faster. If you're exploring or generating B-roll, natural language prompts are more flexible. The lesson: stop forcing one tool to do everything. Match the tool to the task. Discussion question: Are you a "structured controls" filmmaker or a "natural language" filmmaker — and does your current tool match that? Founding Members get the full tool comparison breakdown (Kling vs Sora vs Runway vs Veo) with workflow decision trees and when to use which approach — skool.com/aiography/classroom

Hi everyone I keep seeing people get great results from Higgsfield, but then get stuck when they try to turn a single good image into something usable for video. A common issue I’ve run into (and hear from others) is: You generate a strong image, but when you animate it, the motion feels random or breaks the look. What helped me simplify this was: - Treating Higgsfield images as keyframes, not final shots - Locking the camera style and lighting first - Keeping motion prompts very minimal and consistent across frames - Thinking in short 3–5 second clips instead of full scenes Once I stopped trying to do everything in one prompt and focused on consistency over complexity, the outputs became way more usable for video work. Curious if others here have run into the same thing and how you’re handling animation flow with Higgsfield.

Three deep dives dropped this week that Founding Members got first: 🔧 Building a Local 4K AI Video Pipeline — Full NVIDIA + ComfyUI technical breakdown. No cloud costs, no waiting in queues. Your GPU, your footage, your workflow. 🎭 Real-Time AI Avatars with Runway Characters — How world models meet interactive media. Step-by-step build from zero to working avatar. 🎬 Daniel Kwan's AI Roadmap from SXSW — The "Everything Everywhere All at Once" director spent 3 years going deep on AI. His framework for filmmakers is the most practical thing I've seen from someone actually making films. We're past the halfway mark to 50 Founding Members. Once we hit 50, the price goes up and the door closes at this rate. So join TODAY! $29/month, locked for life → https://www.skool.com/aiography/classroom