News, insight and updates from the world of FoxyAI.
Training a visual machine learning model first involves labeling a set of images. The labels indicate what is present in an image, and in some cases, its bounding box or polygon.
When viewing photos and/or visual media of a property, there is an abundance of knowledge inherent in the photos that can be learned about the space. For example, it can be determined if there is a bathtub, the state (condition) of the kitchen, or if there are hardwood floors in the living room.
FoxyAI, a B2B proptech startup providing real estate visualization and property intelligence services, announced today a partnership…
The “Uber” of Property Photos and Data Teams Up with B2B PropTech Leader in Visual Property Intelligence to Transform Real Estate…
Artificial intelligence (AI) has become ubiquitous. From Netflix recommendations to smart speakers, it seems like every day brings new innovations from the field of artificial intelligence. However, today, no AI is 100% accurate. In fact, AI may never be perfect. Understanding this is key to successfully deploying any AI in your business. When considering applying AI to your business, how should you think about accuracy?
After almost a decade of steady growth, the economy is slowing. Interest rates are up, and inflation is at its highest since 1980. Budgets have been cut and spending frozen. We’ve seen several rounds of layoffs from top startups who’ve raised millions of dollars.
On June 22, 2022 the Joint Center for Housing Studies of Harvard University published its annual state of the nation’s housing report. We read all 48 pages so you don’t have to. Here are 7 quick takeaways to bring you up to speed.
Computer Vision is a field of artificial intelligence (“AI”) that enables a computer algorithm to interpret and understand images and videos. This technology has been around in some form since the 1950s.
At FoxyAI we believe that just as a home buyer scrupulously inspects the visual quality of a property, so should the machines.
