In the past months, we smashed all the state-of-the-art image and video models to make them x2-x10 faster! We compressed All models from Black Forest Labs, HiDream, and Alibaba on @replicate.com 👇 We even created it the super high resolution Wan Image which can make cinematic images in seconds ;)

From Wan video to Wan Image: We built the fastest endpoint for generating 2K images! - Accessible on @replicate.com: replicate.com/prunaai/wan-... - Check details, examples, and benchmarks in our blog: www.pruna.ai/blog/wan-ima... - Use Pruna AI to compress more AI models: docs.pruna.ai/en/stable/

Happy to announce the "Awesome AI Efficiency" repo gathering 100+ curated materials on efficient AI It is designed for a large audience and includes diverse materials. It is an ongoing project. Do not hesitate to share your feedback/suggestions and star the repo! 🌟 github.com/PrunaAI/awes...

🚀 𝟭𝟬,𝟬𝟬𝟬 𝗠𝗼𝗱𝗲𝗹𝘀 𝗦𝗺𝗮𝘀𝗵𝗲𝗱 𝗼𝗻 @hf.co 🤗 (+2,500 in just the last two months 📈 all of you are keeping us busy!) To celebrate, we gave our HF space a little makeover… and snuck in an Easter Egg 🥚 👀 Think you can find it? Drop a comment if you do!

Very clear example of how two (Bayesian) agents with wrong prior beliefs can lead to belief polarization even when seeing the same evidence! 👏

Super excited to share that the MatterGen code is now public on GitHub! github.com/microsoft/ma...

Big news for the AI community! Pruna AI is now free(mium)! 🎉 It takes a based model as input and returns a compressed model as output with various compression methods. You can access via: - Self-hosted w/ CLI (docs.pruna.ai/en/latest/se...) - Cloud hosted w/ AWS: aws.amazon.com/marketplace/...).

“Shaving Weights with Occam’s Razor: Bayesian Sparsification for Neural Networks using the Marginal Likelihood” is at #NeurIPS2024! This would not have been possible without Rayen Dahri* who lead the project, Alex Immer, Stephan Günnemann, and @vincefort.bsky.social ! 1/3

This was a super fun collaboration, led by my master's student Rayen Dhahri with Alex Immer, @bertrand-sharp.bsky.social, and Stephan Günnemann

“Expected Hierarchical Clustering” is at #NeurIPS2024! This would not have been possible without Marcel Kollovieh* who lead the project, @danielzuegner.bsky.social and Stephan Günnemann ! 1/4

@prunaai.bsky.social has raised $𝟲.𝟱𝗠 to make AI accessible to everyone 👥 and sustainable for the planet 🌍! #EfficientAI #AccessibleAI #SustainableAI #TechForGood