I’m thrilled and proud to share our model, Movie Gen, that we've been working on for the past year, and in particular, Movie Gen Edit, for precise video editing. 😍
Look how Movie Gen edited my video!
So proud to be part of the Movie Gen project, pushing GenAI boundaries!
Two key insights:
1. Amazing team + high-quality data + clean, scalable code + general architecture + GPUs go brr = SOTA video generation.
2. Video editing *without* supervised data: train a *single* model
We released 92 pages worth of detail including how to benchmark these models! Super critical for the scientific progress in this field :) We'll also release evaluation benchmarks next week to help the research community 💪
Excited to share our progress on Movie Gen, a SOTA model for video generation! 🎥✨
I worked on this project as part of a cutting-edge team 🔥, pushing the boundaries of video editing ✂️— all without supervised data.
Can’t wait to show you what’s next! 🚀🎬
So how did we get to these amazing videos for Meta Movie Gen? One of the things I’m proudest of is that we released a very detailed technical report (ai.meta.com/research/movie……)
Lets dive into a technical summary of what we did & learnt
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x.com/AIatMeta/statu…
Movie Gen claims to be the state-of-the-art in text-to-video generation, outperforming Sora, Kling, Gen3, and more. But how can you trust the results?
Today, we're releasing 1003 videos and their prompts - no cherry-picking allowed. Our goal? To set a new standard for evaluating
Two exciting updates on Movie Gen
(1) MovieGenBench containing thousands of *random* generations for benchmarking for video/audio tasks :)
(2) Folks in Hollywood (Casey Affleck, Blumhouse productions) took Movie Gen for a spin: ai.meta.com/blog/movie-gen…
VERY excited about the era of generative AR we're bringing to life. Check out this preview!
It's early but so damn promising — this isn't "AI slop"... it's unlocking Creators' imaginations on their own videos. Change your wardrobe, scene, lighting etc. with little expertise.
PS
🚀 Our latest work, VideoJAM, introduces a new method to enhance motion in any T2V model, significantly improving its motion and physics.
We also train a DiT model that, combined with VideoJAM, achieves a new SOTA in motion generation! 🔥
hila-chefer.github.io/videojam-paper…
Meta just dropped VideoJAM
Joint Appearance-Motion Representations for Enhanced Motion Generation in Video Models
comparison with openai sora and kling
This is extremely cool!
They find diffusion loss is not very sensitive to motion. Thus they fine-tune videogen models with additional explicit motion prediction, making the model generate much more coherent videos.
Also, Hila has been doing consistently good work, follow her!
Super excited to share 🧠MLGym 🦾 – the first Gym environment for AI Research Agents 🤖🔬
We introduce MLGym and MLGym-Bench, a new framework and benchmark for evaluating and developing LLM agents on AI research tasks.
The key contributions of our work are:
🕹️ Enables the
The longer reasoning LLM thinks - the more likely to be correct, right?
Apparently not.
Presenting our paper: “Don’t Overthink it. Preferring Shorter Thinking Chains for Improved LLM Reasoning”.
Link: arxiv.org/abs/2505.17813
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