Microsoft published RetroChimera, a retrosynthesis prediction framework, in Nature and open-sourced its implementation and weights. It combines the Transformer model R-SMILES 2 with GNN-based NeuralLoc, using a learned ensemble to rerank predictions. Chemists preferred its single-step reaction predictions in blind testing.
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. CHOP is working with NVIDIA to integrate Newton, an open-source physics engine based on NVIDIA Warp, into SlicerHeart, reducing cardiac-device simulation from up to four hours to near real time.
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.
Microsoft Research introduced GigaPath-Flash and GigaTIME-Flash, greatly reducing pathology compute requirements with a 22M-parameter ViT-S backbone distilled from the billion-parameter GigaPath encoder, open-source under Apache 2.0.
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.