Independent research notes on artificial intelligence, computer science, geoscience, and Earth observation — with primary sources, stated limitations, and dates readers can check.
A self-hosted OSINT platform that normalises 48 public data sources into a single event schema, with a local LLM correlation layer on top. Here is what it does, what it does not do, and where the design trade-offs sit.
An 8,500 mAh silicon-carbon battery, 12 GB of LPDDR5X, and a 3 nm chipset make the X8 Pro Max a credible host for quantised local models. Whether you can actually run them depends on software support, not silicon.
GraphCast, Pangu-Weather, and FourCastNet showed that learned models can match or beat physics-based forecasts on reanalysis data. ECMWF now runs one of them operationally. The limits matter as much as the results.
The Python geoscience stack has settled into a stable core: labelled arrays, lazy computation, publication-quality maps, and geospatial machine-learning tooling. Here is what each library is for — and where the documentation lives.
