🚀 We're hiring a Research Scientist, Machine Learning Research (MLR), Barcelona ☀️ 👉 Apply here: jobs.apple.com/en-us/detail... #MachineLearning #MLResearch #AI #Hiring #Apple #Barcelona #ResearchScientist #DeepLearning

AIML - Machine Learning Researcher - MLR - Jobs - Careers at Apple

Apply for a AIML - Machine Learning Researcher - MLR job at Apple. Read about the role and find out if it’s right for you.

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Today we have released the code and a demo iOS application for FastVLM - our extremely efficient and fast vision language model which runs on your device using MLX! You can check out the code and the app here: github.com/apple/ml-fas...

#ICLR #TrainBetterLM I am at ICLR, come to our posters for improved language model training! Recycle gradients for faster neural net training with AdEMAmix iclr.cc/virtual/2025... (Fri Apr 25, 10 am). 1/3

Check our Pau and his Apple MLR team's blogpost on activation transport! Soon to be featured as a spotlight at ICLR :)

Pau Rodriguez@paurodriguez.bsky.social · last yr.

Our work on fine-grained control of LLMs and diffusion models via Activation Transport will be presented @iclr_conf as spotlight✨Check out our new blog post machinelearning.apple.com/research/tra...

More scaling laws? Mustafa and his team at Apple MLR have you covered at least when ti comes to native multimodal models scaling laws :)

Josh Susskind@kindsuss.bsky.social · last yr.

Check out our Apple research work on scaling laws for native multimodal models! Combined with mixtures of experts, native models develop both specialized and multimodal representations! Lots of rich findings and opportunists for follow up research!

Calling all SSL practitioners -- check out this library done by the amazing \alpha-Req crew

Arna Ghosh@arnaghosh.bsky.social · last yr.

Are you training self-supervised/foundation models, and worried if they are learning good representations? We got you covered! 💪 🦖Introducing Reptrix, a #Python library to evaluate representation quality metrics for neural nets: github.com/BARL-SSL/rep... 🧵👇[1/6] #DeepLearning

Paper🧵 (cross-posted at X): When does composition of diffusion models "work"? Intuitively, the reason dog+hat works and dog+horse doesn’t has something to do with independence between the concepts being composed. The tricky part is to formalize exactly what this means. 1/

Preetum Nakkiran@preetumnakkiran.bsky.social · 2y ago

finally managed to sneak my dog into a paper: arxiv.org/abs/2502.04549

Excited to share Soup-of-Experts, a new neural network architecture that, for any given specific task, can instantiate in a flash a small model that is very good on it. Made with ❤️ at Apple Thanks to my co-authors David Grangier, Angelos Katharopoulos, and Skyler Seto! arxiv.org/abs/2502.01804

🚨 Apple Machine Learning Research Internship opportunity! My colleagues in Apple MLR are looking for a PhD research intern with a strong interest in reinforcement learning/post-training for LLMs. If interested, apply by sending an email to Etai Littwin (elittwin at apple dot com)

Mixture of experts is an interesting architecture or so @samiraabnar.bsky.social told me when I joined the project last year. After some brilliant work from @harshay-shah.bsky.social and @samiraabnar.bsky.social , we have a scaling law paper!

Samira@samiraabnar.bsky.social · 2y ago

🚨 One question that has always intrigued me is the role of different ways to increase a model's capacity: parameters, parallelizable compute, or sequential compute? We explored this through the lens of MoEs: