7 posts
NVIDIA just dropped a pre-trained model that outperforms supervised ML on relational databases—no feature engineering, no training. It's few-shot, it's fast, and it might finally kill the XGBoost pipeline.
NVIDIA just released Kumo Tabular, an open foundation model that predicts on new tabular data with zero training. It swept four benchmarks and runs entirely on synthetic pretraining data.
IBM's new Granite Time Series PatchTST-FM-r2 hits #1 among commercially licensed zero-shot forecasters on GIFT-Eval. 385M params, conformer blocks, and actual permissive licensing.
IBM's Granite time series models are now native in Confluent Cloud, bringing forecasting and anomaly detection directly into streaming pipelines with zero infrastructure overhead.
Allen AI's new embedding exports turn complex Earth observation into surprisingly simple linear algebra. No training data, just dot products and mangrove maps.
Ai2 ships a continent-scale geospatial inference platform that processes dozens of terabytes in ~24 hours. The infrastructure choices reveal hard truths about production ML.
NVIDIA just shipped a 4-billion-parameter world action model designed for edge devices—robots, Jetsons, RTX GPUs. It's one model that predicts, simulates, and acts in real time.