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L123 : How AI and Computer Vision Are Transforming Construction PM with Prof. Mani Golparvar-Fard

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Manage episode 477979371 series 3660361
Content provided by Mayur M Mistry. All podcast content including episodes, graphics, and podcast descriptions are uploaded and provided directly by Mayur M Mistry or their podcast platform partner. If you believe someone is using your copyrighted work without your permission, you can follow the process outlined here https://ppacc.player.fm/legal.

An interview with Mani Golparvar, co-founder and CTO of Reconstruct, a software platform for construction project management. Mani discusses how Reconstruct uses AI and computer vision to generate 3D models from images and video captured on construction sites. This allows stakeholders to remotely monitor progress and compare as-built reality to design models. Benefits include reducing travel costs, improving project visibility, and verifying installed work. Mani also shares his experience as a professor researching AI for construction at the University of Illinois. He provides insights on construction vs design workflows for AI, challenges acquiring training data, and emerging techniques like synthetic data. Overall, the interview explores AI's transformative potential in construction through Mani's dual lenses as an academic researcher and technology entrepreneur. Chapters : 00:09 - Introduction00:17 - About Reconstruct01:00 - Using visual data in construction02:00 - Background 04:13 - Managing time as professor and startup founder 07:00 - Challenges faced 09:00 - From research to entrepreneurship11:00 - Rule-based vs data-driven AI techniques in construction16:00 - Using computer vision for construction safety23:00 - Short vs long term AI research needs in construction 24:00 - Getting industry data for AI research31:00 - Potential data licensing models 32:00 - Tapping into existing hardware and data38:00 - Receptiveness to robotics in construction39:00 - Multimodal models with schedule, images, 3D40:45 - Rapid fire questions#contech #aectech #computervision

  continue reading

100 episodes

Artwork
iconShare
 
Manage episode 477979371 series 3660361
Content provided by Mayur M Mistry. All podcast content including episodes, graphics, and podcast descriptions are uploaded and provided directly by Mayur M Mistry or their podcast platform partner. If you believe someone is using your copyrighted work without your permission, you can follow the process outlined here https://ppacc.player.fm/legal.

An interview with Mani Golparvar, co-founder and CTO of Reconstruct, a software platform for construction project management. Mani discusses how Reconstruct uses AI and computer vision to generate 3D models from images and video captured on construction sites. This allows stakeholders to remotely monitor progress and compare as-built reality to design models. Benefits include reducing travel costs, improving project visibility, and verifying installed work. Mani also shares his experience as a professor researching AI for construction at the University of Illinois. He provides insights on construction vs design workflows for AI, challenges acquiring training data, and emerging techniques like synthetic data. Overall, the interview explores AI's transformative potential in construction through Mani's dual lenses as an academic researcher and technology entrepreneur. Chapters : 00:09 - Introduction00:17 - About Reconstruct01:00 - Using visual data in construction02:00 - Background 04:13 - Managing time as professor and startup founder 07:00 - Challenges faced 09:00 - From research to entrepreneurship11:00 - Rule-based vs data-driven AI techniques in construction16:00 - Using computer vision for construction safety23:00 - Short vs long term AI research needs in construction 24:00 - Getting industry data for AI research31:00 - Potential data licensing models 32:00 - Tapping into existing hardware and data38:00 - Receptiveness to robotics in construction39:00 - Multimodal models with schedule, images, 3D40:45 - Rapid fire questions#contech #aectech #computervision

  continue reading

100 episodes

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