
Processing satellite and geospatial data at global scale enables new applications in climate monitoring, agriculture, and disaster response.
The OlmoEarth Platform is infrastructure that enables large-scale inference using Earth observation foundation models trained on satellite data, allowing organizations to process geospatial information across continent-sized areas. Most machine learning models process small amounts of data quickly, but satellite inference operates at a vastly different scale, requiring the acquisition and alignment of terabytes of imagery from multiple sources with different projections and resolutions, as well as the ability to stitch results into geographically consistent maps. The platform divides inference jobs into three hardware-matched stages: data acquisition and preprocessing on CPUs, model inference on GPUs, and postprocessing on CPUs, while partitioning geographic regions into independent work units that can be processed in parallel. Governments, NGOs, and environmental organizations are already using OlmoEarth models for applications including deforestation monitoring, food security assessment, and wildfire risk evaluation.

Long-horizon agents accumulate context faster than they resolve tasks. Every tool output, observation, and intermediate reasoning step stays in the window, and the two capabilities that matter — holding that context and staying coherent across it — have so far been available almost exclusively from cloud endpoints. That excludes regulated industries, public-sector institutions, and on-device applications, where the data is not permitted to leave the boundary at all. Pokee AI released Pokee-Isaa

Mistral AI has released Shieldstral 1.0 3B, an open-weights, policy-adaptive multimodal safety classifier that treats content moderation as a single yes/no question rather than a fixed taxonomy of harm categories. Most guardrail models bake their category list into the weights, so re-targeting one to a new deployment context means retraining — and the same content can be acceptable on a cybersecurity research tool while being harmful on a mental-health platform. Shieldstral inverts that: operat

NVIDIA Labs has open-sourced NOOA (NVIDIA Object-Oriented Agents), a model-agnostic Python framework for building AI agents. Agent development today is split across prompt templates, tool schemas, callback code, and workflow graphs. NOOA collapses all of it into one Python class. Methods are the actions the model can take. Fields are agent state. Docstrings are prompts. Type annotations are contracts the runtime enforces. A method whose body is ... is completed at runtime by an LLM-driven loop,
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