Artificial intelligence in Construction

Artificial intelligence in construction

Patrick Murphy is founder and CEO of Togal.AI Founder and CEO a construction technology company in Miami.

How is AI going to change the construction industry in 2024 and beyond and how is that change going to affect the industry?
Patrick MurphyCourtesy image

So much of construction is documentation these days. Everything from a set of plans to what we call a specification book which will go into an in-depth description of all the specs — the exact closet drawer, the millwork color, the type of tile in Bedroom A versus Bedroom B. Every single specification all written out in 1,000-page documents. Your estimates, your schedules and bid books, all the contracts, not only with the owner but with your vendors and your subcontractors. Thousands of contracts. My point is, on commercial jobs or large residential jobs, 10s and 10s of 1,000s of pages of information go into each of those. And it’s very hard for any single human to read, interpret, understand, memorize all that information and see that how they interrelate.

Large language models are great at that. The user just has a conversation and says,

'Hey, who's responsible for installing the windows on the 10th floor? What's the appliance package in the penthouse? What are the current parking curbs to be installed?' Whatever the question is, you get answers based on the information that you uploaded in human terms that actually make sense. That's going to continue to improve. And the large language models will continue getting better and understanding each industry better and better. So obviously, we're talking construction here, but the same will be true for medical, for insurance, for hospitality. Whatever you name, it will keep getting better and better. Construction in particular, because it's so text heavy and documentation heavy, will really progress with large language models. Just take one thing in particular. Construction contracts take a lot of time. I think that'll be dramatically improved going forward because of this deeper understanding of large language models.

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