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I keep hearing AI in Construction framed like it just arrived.
It didn't.
It's been in predictive analytics and machine control for years. What's changed is how usable it is in the field.
Datumate captured a conversation I had with Tom Jennings and Dr. Florent Poux on exactly that shift. Three things stood out to me:
- Autonomous machine control first introduced mid 1990's for use with less skilled Equipment Operators and AI-assisted ground control are saving real time, not demo time.
- Point clouds stop being pretty scans when you inject knowledge into the data. Then they become decisions.Using a GEOSPATIAL OS in your Framework Anchor
- Disparate data is no longer the blocker. RAG and vector databases can piece it together from across your repositories.
My take, same as it was in that conversation:
Start small. Start with classical approaches. Use deep learning only when those fail.
Frameworks and Automation Pipelines are your Foundation to Build on.
You will fail at first. Test it rigorously anyway. Then you'll have something solid.
Where are you actually using AI on a job right now, not just talking about it?
Leave a comment below.
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