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A practitioner's guide based on experience setting up and operating sensor development and characterisation labs at CERN, LBNL, DESY, and the University of Bergen.
The majority of this guide applies to any lab doing experimental physics, electronics development, or instrumentation work. Sensor-specific sections are clearly marked.
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A basic test of OpenAI's Structured Output feature against financial disclosure reports and a newspaper's police blotter. Code examples use the Python SDK and pydantic for the schema definition.
Extracting financial disclosure reports and police blotter narratives using OpenAI's Structured Output
tl;dr this demo shows how to call OpenAI's gpt-4o-mini model, provide it with URL of a screenshot of a document, and extract data that follows a schema you define. The results are pretty solid even with little effort in defining the data — and no effort doing data prep. OpenAI's API could be a cost-efficient tool for large scale data gathering projects involving public documents.
OpenAI announced Structured Outputs for its API, a feature that allows users to specify the fields and schema of extracted data, and guarantees that the JSON output will follow that specification.
For example, given a Congressional financial disclosure report, with assets defined in a table like this:
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Pull H3s for Overture's Places Dataset for May 2024
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Merge a directory of PMTiles files into a single file
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Compile ffmpeg 6.0 with NVIDIA hardware acceleration
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SQL to generate Voronoi Polygons to determine National Park catchment areas.
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