This Just In: How Machine Learning is Transforming Home Makeovers

Artificial intelligence in science fiction tends to come in one of two flavours: helpful androids like WALL-E or malevolent, homicidal robots à la HAL 9000. Few narratives of the genre conceived of a future where computers would be programmed to master the art of interior design. But that probability is no longer far off from reality due to the efforts of present-day researchers.

Introducing machine learning, a subset of AI that is able to make data-driven predictions and decisions without being explicitly coded to perform them. What was once the domain of such applications as medicine and engineering has been infiltrated by decorators keen on using its potentialities for sentiment and behavioural analytics to better cater to their clientele’s tastes.

Check out how these expert systems are now changing the world of style.

#1 Increase house appeal. Similar to how Google and Facebook show you advertisements that correspond to your web activity, Airbnb uses a series of algorithms to pair users with rooms they might adore, and in the same vein, push listings that have the biggest allure. Building upon this development, the home-sharing platform is in the midst of working on a digital designer that is aimed at improving the image of host residences and boosting bookings by recommending the most in-demand cosmetic enhancements. The technology, as well as others identical to it, has the power to approximate looks that perfectly fit individual inclinations. Say goodbye to spending hours trawling Pinterest and flipping through glossies to find a loose representation of your décor desire. A few clicks is all it takes.

#2 Preview changes before taking the plunge. Currently serving the retail industry, UK company DigitalBridge offers a visualisation tool that enables customers to try on products in their dwellings prior to purchase. The process is as straightforward as they come: just snap a photo of the chosen room, which is processed via computer vision to produce an accurate 3D recreation. You can then drag and drop items from the store’s catalogue, in addition to removing or replacing existing furnishings, wall coverings, flooring, and accessories.

#3 Generate well-organised layouts. Ashutosh Saxena and his team at Cornell University are teaching robots to ‘imagine’ what humans would do or prefer when putting together a roomful of objects. For example, someone would want a remote control nearby and not directly next to the television, which is where a robot would logically place the two related things. Saxena’s algorithms study these relationships and determine the efficiency of the locations in a given area based on how easy it is for a person to access daily implements without moving too much.

Interested? Book an appointment at our website and find out how we’re using technology to revolutionise home design.


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