What’s next for artificial intelligence? Step into NYU’s Data Future Lab and you will find the answer amongst five stellar startups that are poised to change the world. Last Friday, the Lab graciously invited our CDS students to tour their offices and discover the career opportunities are waiting for them at the startups and the Lab.
1. Wade And Wendy
Every graduate’s headache after tossing their graduation cap in the air is how to clinch a full-time job. Luckily, ‘Wade and Wendy’ is here to improve the recruiting process using machine intelligence. They are named after two artificially intelligent personalities. ‘Wade’ is a career guide for applicants: he presents available employment options based on the applicant’s wants and needs. Wade’s conversational interactions with the user explain why his technical strengths are understanding unstructured text, participating in dynamic, real-time conversations, and developing an engaging personality.
‘Wendy’, however, assists hiring managers with filling open positions. Her technical strengths are sourcing and screening data, clarifying role descriptions, gathering and summarizing feedback, and coordinating interviews. Key to her role is aggregating data from Wade and the company’s hiring manager to build models that can assess which applicants are an ideal fit for the job. Crucially, ‘Wade and Wendy’ does not replace HR recruiters: in fact, their people-centered philosophy means that they greatly depend on recruiters to train both robots.
2. Paperspace
The technology space is crowded with new computers and operating systems that are coming out every day. How can we keep track of our data and information as we leap back and forth between desktops, PCs, and tablets? The answer: Paperspace, a new cloud-based computer that can be accessed anywhere on any device. Harnessing the power of GPU (Graphic Processing Unit), Paperspace is a powerful virtual desktop that can run demanding applications quickly making it an ideal fit for personal use, businesses, or educational institutions.
3. FindMine
A major challenge facing online shopping is demonstrating how a product can be integrated in the user’s life, especially when it comes to fashion. A pair of boots may seem appealing on screen, but would they match what you have in your wardrobe? While online stores use algorithms to generate ‘similar items’ lists for customers, recommendations about other products that complement the selected item are still generated manually.
FindMine automates this process for retailers by using powerful and scalable machine learning techniques. Its complex algorithms analyze the brand’s aesthetics and the user’s tastes to create a personalized shopping experience. FineMine’s three-month pilot for menswear company John Varvatos shows promising results: average orders and the amount of time spent on the site increased by 74% and 107% respectively, and their overall revenue increased by 6.7%.
by Cherrie Kwok