The Universal Agent Evaluation Framework (UAEF) is a framework-agnostic system for evaluating AI agents. UAEF converts each framework's traces into one canonical format, scores them with 36 built-in metrics across 7 dimensions, and stores results so teams can compare agent versions and catch regressions.
Today we're introducing a framework for creating these environments; we call them FoundationWorlds. Our first foundation world is ToyBlocks : an open simulation framework built around a robot arm and blocks on a tabletop.
NVIDIA Cosmos world model development platform adds four new open-weight checkpoints to its Cosmos 3 model family for generating interactive world simulation and multi-sensor multi-view driving scenes. All four models are post-trained examples of Cosmos 3 Nano and have 16B trainable parameters. The models use OpenMDW1.1, permitting commercial and non-commercial use under its terms.
On July 30, 2026, Transformers enabled PyTorch's scaled dot-product attention (SDPA) for T5. As a side effect, UMT5's decoder could attend to future tokens.
Four open Granite models, one extensible forecasting interface, and less guesswork about which model to use. One recipe combines four complementary Granite architectures and returns median and quantile forecasts, with no retraining and no fitted ensemble weights.
SimReady Central Library brings together more than 2,000 simulation-ready (SimReady) OpenUSD assets on Hugging Face, giving developers a free, ungated starting point for physical AI training environments and AI factory digital twins.
Last November, we introduced AnyLanguageModel on this blog: a drop-in replacement for Apple's Foundation Models framework that lets you choose the model and provider your app uses. A year and dozens of releases later, AnyLanguageModel 1.0 is out, along with swift-huggingface 1.0 and swift-xet 1.0.
Beam by Reflection is out on Hugging Face! It is the first model from the new US lab, Reflection, and it’s open! It's a mixture-of-experts (MoEs) model with 501B parameters (23B active per token), supports text as input, has a context window of 1M tokens, and is released under the Apache 2.0 license.
Black Forest Labs FLUX.3 Image Klein is here, and it runs in Diffusers from day one. One model does text-to-image and multi-reference image-to-image, and it adds something new, the layout control.
We built AstaBrief 8B, a model that turns a research question and retrieved literature excerpts into a cited report. AstaBrief is available in Asta's Generate a report feature today as Fast mode alongside Claude-powered Thinking mode, and we're also open-sourcing it and the training data so other
Custom-made molecules are advancing medicine, materials, and agriculture, but producing them is slow and expensive. A new Nature paper highlights RetroChimera, a predictive model that helps accelerate chemical synthesis, helping researchers explore a wide range of molecules.
Hugging Face released tokenizers v1, preserving token IDs, APIs, vocabularies and merge ranks from v0.23 while increasing speed by up to tens of times.
Google Research released MilleMiglia, a C++ generator of realistic, privacy-preserving benchmark instances for middle-mile logistics delivery. Source and documentation are public on GitHub.
Children's Hospital of Philadelphia (CHOP) uses MONAI, the open-source medical imaging framework co-founded by NVIDIA, to reduce paediatric heart modelling from four hours to seconds, already supporting complex ventricular septal defect surgical planning.
Hugging Face launched NeoMME in 260M and 800M sizes. A single bidirectional Transformer handles text tokens and 32×32 image patches, trained from scratch with a masked discrete diffusion objective rather than pretrained vision towers or causal language models.
A public low-cost approach fine-tunes LFM2.5-350M with TRL GRPO using around 500 samples and 100 steps, raising IFStruct from 22.6% to 29.7%. Training fits free Colab or Kaggle GPUs, with local llama.cpp evaluation on a MacBook and code open on GitHub.
What if pathology foundation models could do more with less? GigaPath-Flash and GigaTIME-Flash cut computational demands while maintaining strong performance, opening the door to larger studies and broader exploration.
Hugging Face's OlmoEarth Studio now computes and exports embeddings. Users choose an area, period, encoder variant and resolution through UI or API and receive Cloud-Optimized GeoTIFF (COG) results.
Hugging Face released Grabette, an open-source system recording manipulation demonstrations with a handheld gripper and two cameras, producing robot-ready datasets without robots or teleoperation equipment. The handheld hardware costs about €490 in materials, with the accompanying motorised Gripette gripper around €120. Hardware CAD, Raspberry Pi collection software and browser-based processing are all open-source.
Hugging Face released ScarfBench (Self-Contained Application Refactoring Benchmark) to evaluate AI agents migrating enterprise Java applications between Spring, Jakarta EE and Quarkus.
Hugging Face proposed DiScoFormer (Density and Score Transformer), estimating a distribution's density and score simultaneously in one forward pass from a set of data points, without retraining for new distributions.
Google Research proposed MoGen (Neuronal Morphology Generation), using PointInfinity point-cloud flow matching to generate synthetic neuronal shapes and supplement PATHFINDER reconstruction training. It reduced reconstruction error by 4.4% on held-out mouse axons, mainly by reducing merge errors.