RIP Claude Fable, open-source AI unleashed, full body avatars, new Google models, new TTS: AI NEWS
Open-source motion transfer and real-time translation tools like Scale-2 and Gemini 3.5 Live Translate expand the technical capabilities accessible to indie AI filmmakers.
What this lesson covers
This video covers major AI updates, highlighting Scale-2 for open-source motion transfer and Google's Gemini 3.5 Live Translate. It also explores new 3D world models and open-source releases from labs like ZAI and Minimax.
Key takeaways from the creator
AI-extracted notes, not independently verified product claims. Timestamp links let you check each point in the original video.
- 0:50 ↗
Scale-2 is an open-source model capable of transferring motion from a reference video onto target characters, including multiple subjects and non-human proportions.
- 6:21 ↗
Gemini 3.5 Live Translate provides real-time speech translation across 70 languages while preserving the speaker's original intonation and pacing.
Workflow outlined in the video
- Visit the Scale-2 GitHub repository to review installation instructions and hardware requirements for local execution.
- Test Google's Gemini 3.5 Live Translate via AI Studio or Google Translate on mobile devices for voice localization workflows.
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.
How to interpret the numbers
134,062 views captured 23 October 2026. ReelStack recommendation score: 39/100. Formula: radar-v5. This is ReelStack’s calculation, not a YouTube rating or a measure of factual accuracy.
Show the calculation
- 45% performance: 1.10× views vs 9 other channel videos observed at a similar age. View-evidence factor 99% (views / (views + 1,000))
- 25% freshness: 0/100 with a 14-day half-life
- 20% momentum: 14 views/day vs 19 channel baseline (6 comparable uploads), with the same view-evidence factor
- 10% engagement: 75/100; likes + 4× comments, smoothed with a 500-view neutral prior