New Deepseek, human genome map, Navier Stokes, GPT finance, Suno v6, YuE2: AI NEWS
For creators blending AI with 3D pipelines, open-source models like Marigold V2 and Unimate drastically streamline depth map extraction and non-human character rigging from single images and text prompts.
What this lesson covers
This AI news roundup highlights key releases across 3D computer vision, animation, world generation, genomics, and robotics. Key filmmaking-relevant tools include Marigold V2 for pixel-level depth and normal map extraction, Unimate for animating arbitrary 3D skeletons with text, and Lingbot World 2 for real-time interactive world modeling.
Key takeaways from the creator
AI-extracted notes, not independently verified product claims. Timestamp links let you check each point in the original video.
- 01:04 ↗
Marigold V2 extracts high-resolution depth maps, surface normals, and albedo maps directly from single 2D images, requiring 17 GB to 29 GB VRAM for local inference.
- 02:31 ↗
Unimate generates automated motion for non-human and arbitrary rigged 3D skeletons (such as animals, creatures, and inanimate objects) directly from text prompts without additional retraining.
- 05:32 ↗
Lingbot World 2 delivers real-time interactive world generation at 720p 60fps, supporting continuous generation over an hour with interactive NPC agents and memory caching.
- 07:05 ↗
Isaac 0.5 is a 36B sparse open-source foundation model trained on multimodal inputs across 35 robot systems to predict physical movements and environment states.
Workflow outlined in the video
- Clone the Marigold V2 repository from Hugging Face/GitHub to generate surface normal and depth passes from 2D production stills for 3D compositing.
- Ensure your local workstation has at least 17 GB to 29 GB of VRAM available for running high-resolution Marigold V2 inference.
- Import custom rigged 3D models into Unimate and apply text prompts like walking or slithering to automate character animation without manual keyframing.
- Deploy Lingbot World 2 locally using either the 1.3B lightweight variant or the 14B quality variant to generate interactive 3D virtual environment backdrops.
Before you use this workflow
These notes describe the source video at its publication date. Model access, pricing, connectors and interfaces may have changed. Check the original source and the provider’s current documentation before installing an add-on, connecting an account or spending credits.
ReelStack has not independently tested this workflow. Preview one representative shot and check motion, continuity and output quality before applying it to a full production. No result, cost saving or model capability is guaranteed.
Explore the tools
How to interpret the numbers
361,566 views captured 15 September 2026. ReelStack recommendation score: 70/100. Formula: radar-v5. This is ReelStack’s calculation, not a YouTube rating or a measure of factual accuracy.
Show the calculation
- 65% performance: 2.17× current views vs the channel's recent median; same-age history is not yet available. View-evidence factor 100% (views / (views + 1,000))
- 25% freshness: 90/100 with a 14-day half-life
- Momentum pending: collecting daily snapshots; its 20% weight goes to observed performance, not free points
- 10% engagement: 36/100; likes + 4× comments, smoothed with a 500-view neutral prior