Sidewalk Labs Launches Machine Learning Tool for Urban Design

Sidewalk Labs Launches Machine Learning Tool for Urban Design

Sidewalk Labs recently released Delve, a generative design tool powered by machine learning (ML), which helps developers, architects, and planners design urban neighborhoods. The ML algorithms can generate design options from minimal user input about the space and the goals of the project, while also measuring the impact of each design choice.

Sidewalk Labs recently released Delve, a generative design tool powered by machine learning (ML), which helps developers, architects, and planners design urban neighborhoods. The ML algorithms can generate design concepts from minimal user input about the space and the goals of the project, while also measuring the impact of each design choice.

Delve works by creating and ranking urban desigs based off of criteria such as budget, location, and size. The tool can generate high-fidelity designs by allocating individual housing units across a project site and evaluating the daylight for each unit, and optimizing for open space access, walkability and views. Every design comes with a predicted cost per building, street section and open space. Sidewalk’s sustainability team built models for estimating and optimizing electricity use, water, waste, and rooftop solar intake.

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