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...

GitHub - PrunaAI/awesome-ai-efficiency: A curated list of materials on AI efficiency

A curated list of materials on AI efficiency. Contribute to PrunaAI/awesome-ai-efficiency development by creating an account on GitHub.

github.com

🚀 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! 👏

Andreas Kirsch@blackhc.bsky.social · 2y ago

This might seem counterintuitive, but it does align with real-world phenomena observed such belief polarization or the "backfire" effect. The good news: With enough high-quality evidence, rational agents will eventually converge on the truth. But the path there might be bumpy!

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

GitHub - microsoft/mattergen: Official implementation of MatterGen -- a generative model for inorganic materials design across the periodic table that can be fine-tuned to steer the generation towards...

Official implementation of MatterGen -- a generative model for inorganic materials design across the periodic table that can be fine-tuned to steer the generation towards a wide range of property c...

github.com

Microsoft Research@msftresearch.bsky.social · 2y ago

Microsoft researchers introduce MatterGen, a model that can discover new materials tailored to specific needs—like efficient solar cells or CO2 recycling—advancing progress beyond trial-and-error experiments. www.microsoft.com/en-us/resear...

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

Vincent Fortuin@vincefort.eurosky.social · 2y ago

📢 Excited to present our work at #NeurIPS2024! 📄 "Shaving Weights with Occam's Razor: Bayesian Sparsification for Neural Networks using the Marginal Likelihood" Read it here: arxiv.org/abs/2402.15978 Details in 🧵

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