“Democratizing access to good design is absolutely core to our mission of helping people make the world more beautiful…there are millions and millions of people out there who would like to have better design in their environments, but they can’t afford an interior designer, and for all of those people, Lexset will be a go-to,” says Leslie Oliver Karpas, co-founder of Lexset AI, a company that has built and applied an AI visual recognition system from 3D models of objects to the world of interior design.The team at Lexset has created a synthetic data generation engine of about 80,000 different objects of furniture imaged from thousands of different angles and in different lighting conditions in order to maximize the system’s ability to recognize those objects when presented with a photo or real-world space. The system is even able to distinguish between different styles of furniture (e.g. modernist vs. industrial) and materials (e.g. wood, stone, fabric). One of the use cases of this technology is a plug-in for furniture company websites through which images of what you’d like a space in your home to look like could be uploaded, scanned by Lexset AI, and compared to the products offered by that furniture company.Karpas offers an exciting and intriguing glimpse into what the future of interior design might look like, explaining in depth how their technology works, the positive effect of good design on people’s well-being, the objective versus subjective aspects of interior design, and use cases unrelated to interior design involving robotics.Tune in for all the details and visit https://www.lexset.ai/ to learn more.

PyData London 2018

Machine learning and data science applications can be unintentionally biased if care is not taken to evaluate their effect on different sub-populations. However, by using a “fair” approach, machine decision making can potentially be less biased than human decision makers.

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