The training side: building datasets, synthetic data, pre- and post-training methods, compute and training cost.
CoreWeave announced that NVIDIA Vera Rubin NVL72 systems with Spectrum-X 102.4T Ethernet were available on CoreWeave Cloud, with Cognition becoming the first customer to run them in production.
Chipmaker AMD is acquiring World Labs, a startup focused on spatial intelligence. AI pioneer Fei-Fei Li will join AMD's leadership team as Executive Vice President and Chief Scientist. The all-stock deal is valued at about $8.2 billion, according to AMD. The transaction is expected to close by the end of 2026, pending regulatory approval.
AMD is acquiring World Labs, one of the leading developers of deep learning models intended to understand physical reality, in an $8.2 billion deal, the two companies said today. World Labs justified the deal in a statement saying that AI development required “close collaboration across model research, systems and compute.”
NVIDIA released Kumo Tabular, an open-source tabular foundation model that predicts labels for new rows in a single forward pass given labelled rows, without training, tuning or feature engineering. It supports classification and regression, offers three sizes from 28M to 215M, and was pretrained solely on artificially generated tables. It uses the commercially usable OpenMDW-1.1 licence and ranks first on TabArena, BeyondArena, TALENT and ScoringBench.
Microsoft Research released Quine, an AI research system for biological complexity, comprising a biological world model trained on multimodal data spanning sequences, structures, functions, cell states and imaging, and an interactive harness connecting the model, scientific tools, literature and experimental researchers.
NVIDIA joined a global research consortium including Google DeepMind and EMBL-EBI to release predicted 3D protein complex structures for over 2,800 viruses through the AlphaFold Database, free for any scientist to use.
Xiaomi released the MiMo-V2.6 family, including omnimodal models MiMo-V2.6-Pro and MiMo-V2.6-Flash, plus MiMo-V2.6-Pro-UltraSpeed with up to 20 times faster output.
Salesforce unveiled its first CRM reasoning model, Koa, at Dreamforce. Post-trained on NVIDIA Nemotron 3 Super, it uses a proprietary synthetic dataset derived from nearly three decades of enterprise CRM deployments across more than 14 industries, including manufacturing, financial services, healthcare and travel.
NVIDIA announced several advances for Vera Rubin and the DSX platform at AI Infra Summit, focusing on energy-efficiency improvements in token throughput per megawatt.
Google DeepMind launched AlphaGenome Atlas, a platform containing predicted effects for 9 billion single-nucleotide variants across the human genome. At 1 PB, it is over 30 times the size of the AlphaFold Database.
Google Research partnered with HHMI Janelia, the University of Cambridge and others to publish in Cell a complete connectome of a male fruit fly’s brain and central nervous system. It contains over 166,000 neurons and 125 million synaptic connections, making it the largest brain map to date by neuron count.
Google Research introduced the experimental Planetary Prediction Engine (PPE) under Google Earth AI. From a natural language query, it autonomously discovers geospatial data, engineers features, trains and evaluates models and produces reports, compressing weeks of manual data engineering into minutes.
Sentence Transformers v6.0 adds a fourth model type, MultiVectorEncoder, for ColBERT-style late-interaction retrieval, with a complete training approach.
Multiverse Computing published a paper proposing Quantization-Aware Healing (QAH). After compressing GPT-OSS 120B to 60B parameters and quantising it to MXFP4, the method distils directly from the original uncompressed model rather than a reconstructed bfloat16 checkpoint.
IBM Research published ALTK-Evolve research on the Hugging Face blog. Tests of eight models on 585 multi-step AppWorld tasks found agent memory is not an on/off switch but a dosage requiring model-specific calibration.
Hugging Face published its open-source model observatory report for January–August 2026. Hub data shows Chinese labs released the largest open-source models by parameter count in most months, with Chinese monthly peaks between 754 billion and 2.78 trillion parameters, while US models stayed below 130 billion in five of seven months.
Google DeepMind released the WeatherNext AI model, achieving state-of-the-art cyclone track, intensity and wind-field structure forecasts and adding an average extra day of warning, equivalent to roughly a decade of meteorological progress.
Microsoft Research proposed Echoverse, constructing twelve training worlds for computer-use agents: ten deep domain worlds and two capability worlds. Code, data and scorers for four worlds are open-sourced.
Google Research and Google DeepMind proposed SensorFM, a large sensor foundation model learning directly from unlabelled wearable data. Pretraining uses over 1 trillion minutes of multimodal sensor signals from 5 million consenting participants across more than 100 countries and over 20 Fitbit and Pixel Watch devices.
Google Research released TabFM for tabular classification and regression. It reframes table prediction as in-context learning, producing predictions in one forward pass without manual training, hyperparameter tuning or feature engineering.