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AI Helps Identify Drilling Regimes With a Projected Potential Increase in Drilling Speed of up to 68%

October 9, 2026
Artificial Intelligence
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A Skoltech study combining an LSTM model, SHAP explanations and the NSGA-III algorithm projects that better weight on bit, rotary speed and flow rate settings could raise the rate of penetration by up to 68.4% in one of three carbonate wells. We explain how the AI drilling optimization works, the results well by well, why a 68% faster speed means about 40% less drilling time, the study’s limits, and what its design offers industry beyond oil.

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A New AI Framework Could Help Cities Plan for Future Traffic

September 23, 2026
Artificial Intelligence
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Researchers at NYU Tandon have published a geospatial AI framework that pairs ARIMA and LSTM forecasting with H3 hexagonal hotspot analysis and a locally hosted LLaMA query portal, so planners can ask questions of fifteen years of New York traffic data in plain English. The neural model cut root mean square error to 342.56 vehicles per day against ARIMA’s 417.62, and the framework projects average daily volume rising from 12,540 in 2025 to 19,680 in 2029. This article works through the arithmetic, the quotes and the limits the authors state.