Daily AI news, sourcedOfficial news, first rumor reports and substantive progress. Each entry keeps the information published at that time.
- NVIDIA open-sources Auto Ontology, a semantic layer that grounds agent SQL
NVIDIA released Auto Ontology under Apache 2.0: an open library that builds a semantic / ontology layer from enterprise metadata, reconciles definitions across systems, and exposes trusted metrics and lineage to agent harnesses through MCP, CLI, and API (with NL-to-SQL over connected warehouses). It complements existing semantic models rather than replacing them.
- NVIDIA and C-BRAIN deploy open-source AI tools to accelerate dementia and neurodegeneration research
NVIDIA’s blog says the Consortium for Biomedical Research and AI in Neurodegeneration (C-BRAIN) is working with NVIDIA to deploy open-source AI tools that help researchers synthesize large biomedical datasets for Alzheimer’s and other dementias, aiming to speed discovery where data volume outpaces expert review.
- NVIDIA and IIT Madras' AI4Bharat introduce Nemotron-pretraining-Indic-v1, about 2.8 trillion tokens across 22 Indian languages
NVIDIA, with IIT Madras and its AI4Bharat lab, introduced Nemotron-pretraining-Indic-v1, roughly 2.8 trillion tokens covering India's 22 constitutionally listed languages, with native-script data for all 22 and romanized text for twelve. The corpus is releasing soon alongside the open, GPU-accelerated pipeline that made it by translating curated English math, code and Q&A documents, then running quality assessment and targeted repair. NVIDIA says a 100-billion-token continued-pretraining stage with 10% Indic data raised Nemotron 3.5 Super VL by 4.98 to 9.82 points on five Indic knowledge and reasoning benchmarks.
- NVIDIA researchers unveil PivotOPD to help AI agents recover from early mistakes
NVIDIA AI said its researchers built PivotOPD to teach agents how to avoid early mistakes that send a task in the wrong direction, and how to recover when they happen. During training, a teacher model shows the agent a better action and how to get back on track over the next few steps. The paper and a demo are on NVIDIA Research's site.