The role of Gen AI in the built environment – Are we there yet?
Innovation is at the forefront of every industry, and the built environment has to think of ways to build more sustainably. With the advent of machine learning and artificial intelligence, there has been many discussions pertaining to the role of these emerging technologies across different industries.
The time is ripe for change
There is no better time than now to reimagine the way we collaborate, automate and accelerate processes in the built environment. The role of AI and the likes of generative AI will complement the way we approach computational design.
Podium for Development (P4D) is one such platform that leverages AI to accelerate rapid prototyping of site layouts, including spatial and structural design. In this article, we will discuss the role that AI plays within Podium for Development.
At the core of P4D's design tool lies its common object model, which allows users to create a detailed virtual representation of a site layout optimised on multiple constraints and targets. The common object model accommodates the collection and combination of any data type involved in the development process, including spatial, structural, and MEPF elements.
This enables incubating generative AI capabilities, where P4D employs advanced machine learning algorithms to analyse vast datasets of architectural designs captured from Lendlease’s decades of applied experience.
The role of AI
P4D's AI capabilities allow for the generation of innovative and efficient design suggestions tailored to the specific constraints and targets of the project. This significantly accelerates the design process, allowing designers and architects to focus on the creative aspects of the design while AI takes care of the more technical details, which are often than not repeatable and replicable. P4D's AI algorithms analyse data from various sources, including environmental, financial, and regulatory factors, to generate designs that meet specific project requirements.
To further enhance its AI capabilities, P4D is working with Google Cloud to bring AI/ML workflows into Podium. By leveraging the power of Google’s managed ML platform, Vertex AI, and integration with BigQuery, P4D can perform end-to-end data analysis.
Vertex AI workbench is used to drive data visualisation, data cleaning, and exploratory data analysis (EDA). In regard to production, P4D uses Vertex AI Pipelines for training, monitoring, and deploying models via a sequence of containerised pipeline components.
One of the reasons why P4D chose to work with Google Cloud is because of their investment in the enterprise model. With Vertex AI, Google is not just investing in a generic world model but is also investing in bringing outside and inside models together to get the best of both approaches. This allows P4D to invest in developing solutions that protect customers' data and intellectual property without sacrificing coverage.
AI plays a significant role within Podium for Development, enabling key players to design and build more efficiently, sustainably, and intelligently. P4D's AI capabilities are based on its common object model, which accommodates the collection and combination of any data type involved in the development process.
Emerging applications in AI
Imagine a world where we could ingest a 200-page project tender and translating the requirements into computational designs within minutes?
A decade ago, this would have been the impossible. Fast forward to today, we are looking at the inflection point for change. The time is now where we see the relevance of AI in complementing existing methods of construction.
As AI and emerging technologies continue to evolve, we can expect to see more real-life applications to alleviate pain points faced by key players across the supply chain. Emerging technologies will continue to present boundless opportunities for platforms like P4D to incorporate features and elements that could greatly change our approach to building design.