Peter Gray

Apple’s new language model can write long texts incredibly fast In a new study, Apple researchers present a diffusion model that can write up to 128 times faster than its counterparts. Here’s how it works. more…

Apple’s new language model can write long texts incredibly fast

Apple researchers develop SimpleFold, a lightweight AI for protein folding prediction Google DeepMind’s work with AlphaFold has been nothing short of a miracle, but it is computationally expensive. With that in mind, Apple researchers set off to develop an alternative method to use AI to predict the 3D structure of proteins, and it shows promise. Here are the details. more…

Apple researchers develop SimpleFold, a lightweight AI for protein folding prediction

tl;dr: some parameters are much more important than others, and in some cases removing just 1 can turn an LLM's output to nonsense

The A recent paper from Apple researchers,

New Apple #ML Research Highlight: The "Super Weight:" How Even a Single Parameter can Determine an #LLM's Behavior machinelearning.apple.com/research/the...

GitHub - apple/ml-fastvlm: This repository contains the official implementation of "FastVLM: Efficient Vision Encoding for Vision Language Models" - CVPR 2025 This repository contains the official implementation of "FastVLM: Efficient Vision Encoding for Vision Language Models" - CVPR 2025 - apple/ml-fastvlm

The inference code, model checkpoints, and an iOS/macOS demo app based on MLX are available here: github.com/apple/ml-fas...

How fast is it? Here's the demo app running FastVLM 0.5B model on iPhone 16 Pro. Time to first token is shown on the screen, highlighting near real-time performance.

FastVLM: Efficient Vision Encoding for Vision Language Models Vision Language Models (VLMs) enable visual understanding alongside textual inputs. They are typically built by passing visual tokens from a…

New Apple #ML Research Highlight: "FastVLM: Efficient Vision Encoding for Vision Language Models" machinelearning.apple.com/research/fas...

Apple Intelligence Foundation Language Models Tech Report 2025 We introduce two multilingual, multimodal foundation language models that power Apple Intelligence features across Apple devices and…

New paper: 'Apple Intelligence Foundation Language Models Tech Report 2025' provides technical details for two multilingual, multimodal foundation language models that power Apple Intelligence features across Apple devices and services:
machinelearning.apple.com/research/app...

And for a comprehensive overview of Apple research at the conference - including the complete schedule of orals, posters, workshops, booth programming and more - see this post: machinelearning.apple.com/updates/appl...

Next week at #ICML2025, Apple researchers will present many new papers across a range of topics in #AI & #ML - check out this post for some highlights: machinelearning.apple.com/research/icm...

Updates to Apple's On-Device and Server Foundation Language Models With Apple Intelligence, we're integrating powerful generative AI right into the apps and experiences people use every day, all while…

New post: "Updates to Apple's On-Device and Server Foundation Language Models" - details the architectures, training data and recipes, inference optimization techniques, and evaluation results compared to comparable models: machinelearning.apple.com/research/app...

An LLM-Based Approach to Review Summarization on the App Store Ratings and reviews are an invaluable resource for users exploring an app on the App Store, providing insights into how others have…

New Apple #ML Research Highlight: "An LLM-Based Approach to Review Summarization on the App Store" - details the multi-step #LLM workflow for generating high quality summaries from diverse crowdsourced reviews in a dynamic environment: machinelearning.apple.com/research/app...

Apple Machine Learning Research at ICLR 2025 Apple researchers are advancing machine learning (ML) and AI through fundamental research that improves the world’s understanding of this…

New post: "Apple Machine Learning Research at #ICLR 2025" - highlighting a selection of the many Apple #ML research papers to be presented at @iclr-conf.bsky.social this week: machinelearning.apple.com/research/icl...

Accepted as a Spotlight at @iclr-conf.bsky.social the work shares a new method for fine-grained control over #genAI output - without the computational overhead, complexity, and volume of data needed by #RLHF or fine-tuning, and with more reliable results than prompt engineering.

Controlling Language and Diffusion Models by Transporting Activations Large generative models are becoming increasingly capable and more widely deployed to power production applications, but getting these…

New Apple #ML Research Highlight: "Controlling Language and Diffusion Models by Transporting Activations” machinelearning.apple.com/research/tra...

Inside arXiv—the Most Transformative Platform in All of Science Modern science wouldn’t exist without the online research repository known as arXiv. Three decades in, its creator still can’t let it go.

Modern science wouldn’t exist without the online research repository known as arXiv. Three decades in, its creator still can’t let it go.

Very cool work from an international team of researchers including @www.helmholtz-munich.de and Apple: applying optimal transport to give scientists a new ability to observe millions of cells simultaneously, as they develop across time and in space

Today is a great day for optimal transport 🎉! Lots of gratitude 🙏 for all folks who contributed to ott-jax.readthedocs.io and pushed for the MOSCOT (now @ nature!) paper, from visionaries @dominik1klein.bsky.social, G. Palla, Z. Piran to the magician, Michal Klein! ❤️

www.nature.com/articles/s41...

Congratulations!

Aging hipster targeted marketing

A tall robot with googly eyes in the produce section of a supermarket

Supermarket bot on patrol in suburban NJ

Devs can now benefit from faster inference for their production LLMs on NVIDIA GPUs - benchmarking shows 2.7x acceleration in token generation 5/5

NVIDIA TensorRT-LLM Now Supports Recurrent Drafting for Optimizing LLM Inference | NVIDIA Technical Blog Recurrent drafting (referred as ReDrafter) is a novel speculative decoding technique developed and open-sourced by Apple for large language model (LLM) inference now available with NVIDIA TensorRT-LLM...

o make this advancement production-ready for NVIDIA GPUs, the team collaborated with NVIDIA to integrate ReDrafter into the NVIDIA TensorRT-LLM framework: developer.nvidia.com/blog/nvidia-... 4/5

Earlier this year, Apple Machine Learning researchers published & open sourced ReDrafter, a novel approach to speculative decoding: machinelearning.apple.com/research/rec... 2/5

Accelerating LLM Inference on NVIDIA GPUs with ReDrafter Accelerating LLM inference is an important ML research problem, as auto-regressive token generation is computationally expensive and…

New #Apple Machine Learning research highlight: “Accelerating LLM Inference on #NVIDIA GPUs with ReDrafter” - a story of impactful, production-relevant #ML research: machinelearning.apple.com/research/red... 1/5

Apple Machine Learning Research at NeurIPS 2024 Apple researchers are advancing the field of ML through fundamental research that improves the world’s understanding of this technology and…

Apple Machine Learning Research at NeurIPS 2024

machinelearning.apple.com/research/neu...

Neural Information Processing Systems (NeurIPS) 2024 Apple is presenting new research at the annual conference on Neural Information Processing Systems (NeurIPS), which takes place in person in…

The highlight post covers just a selection of accepted papers, and a comprehensive overview of Apple’s participation at #NeurIPS2024 is available here: machinelearning.apple.com/updates/appl... 3/3

This includes new works advancing #privacy-preserving ML, making #multimodal models more capable, improving #LLM pretraining, exploring LLMs’ ability to reason, and understanding self-supervised learning. 2/3

Apple Machine Learning Research at NeurIPS 2024 Apple researchers are advancing the field of ML through fundamental research that improves the world’s understanding of this technology and…

New post: Apple Machine Learning Research at #NeurIPS2024 - highlighting a handful of the many papers #Apple’s #ML researchers will present next week, across a variety of topics: machinelearning.apple.com/research/neu... 1/3