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Smart Model Ensembles for Smarter Construction

Posted Oct 18, 2022 | Views 873
# TransformX 2022
# Breakout Session
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Oleksandr Paraska
CTO @ Togal.ai, Admissions @ Tribe AI

Oleksandr has worked as a software and data architect for 15+ years. He’s currently CTO at Togal.ai, a startup bringing AI to the construction industry. Oleksandr started his current role as a consulting engagement through Tribe AI – a network of top global technical talent that’s changing how companies do machine learning – where he now heads up network admissions.

Through his career, Oleksandr brings deep experience working on ML systems and leading teams. At Adblock Plus, he built and led a team of engineers and researchers to deploy ML to millions of devices. At Captcha, he built a highly scalable system for bot classification running over 100k requests per second with real-time insights into model performance and data drift.

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SUMMARY

AI is spurring a new wave of companies in construction tech that are transforming this $10 trillion-a-year industry. There’s substantial margin risk in construction when projects aren’t well planned, and this eats into economic growth, because construction represents 14% of the world’s GDP. The beginning of a project, known as “take-off,” is critical. Oleksandr Paraska, CTO at Togal.ai, discusses how some of the best machine learning and computer science experts are improving efficiency in construction. Oleksandr talks about his journey in guiding his startup by integrating domain experts (i.e. architects) and engineering skill sets when building models. He also explains how the nuances in floorplan (architecture) diagrams require object detection, classification, and segmentation to make sense of. He also shares the challenges of scaling up processing volumes, in spite of the limits of GPUs, inference times, infrastructure cost and MLOps resourcing.

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