Part of TRANSFORM 2019, VentureBeat recently presented the AI Innovation Awards, which recognise innovation in the field of Artificial Intelligence. The awards were presented on July 11th in San Francisco by Ople, a startup focused on “using AI to build AI” and which aims to make AI as ubiquitous and achievable as possible.
Distinguishing valuable contributions to the field, the five categories for the AI Innovation Awards included NLP/NLU, Computer Vision, Business Application, AI For Good and Startup Spotlight. Here were the winners:
Corti (NLP/NLU Winner)
Based in Denmark, Corti uses AI to help emergency call operators determine whether a severe cardiac event occurred. Corti’s technology takes into consideration both verbal and nonverbal cues before a decision is reached, and has already proven to be more accurate than humans and recognise cardiac events quicker. It is currently being utilised in Europe.
Vue.ai (Computer Vision)
Vue.ai is based in Fremont, California, and applies AI to identify thousands of different fashion products. The company has already experienced tremendous growth, and boasts high-profile clients such as Macy’s, Levi’s, Diesel, Tata, and more. Through AI, the company can identify consumer trends and preferences for an enhanced customer experience.
Bossa Nova (Business Application)
Hoping to use them to revolutionise the inventory management sector, Bossa Nova’s robots can help with customer insight and are also alerted when certain products need to be restocked. They are already deployed in Walmart stores.
Xnor (Startup Spotlight)
Based on a mantra of ‘AI everywhere, on every device’, Xnor’s goal is to prove that you can achieve strong deep learning performance on the edge with extremely low-power and inexpensive devices. Its AI2Go platform is designed to offer optimised, prebuilt models for on-device AI.
Joy Buolamwini, Timnit Gebru, and Inioluwa Raji (AI for Good)
Relating to the ethical and technical issues around facial recognition software, AI researchers Joy Buolamwini, Timnit Gebru, and Inioluwa Raji have been focusing on the significant problem of algorithmic bias in identifying gender and people with dark skin. Their concerns were detailed in a study of Amazon’s Rekognition.
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