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"Scene recognition is one of the hallmark tasks of computer vision, allowing defining a context for object recognition. Here we introduce a new scene-centric database called Places, with 205 scene categories and 2.5 millions of images with a category label. Using convolutional neural network (CNN), we learn deep scene features for scene recognition tasks, and establish new state-of-the-art performances on scene-centric benchmarks. Here we provide the Places Database and the trained CNNs for academic research and education purposes."

"IMAGE AND VIDEO RECOGNITION API Artificial Intelligence with a Vision. Build smarter apps that see the world like you do."

Machine learning is the science of getting computers to act without being explicitly programmed. In the past decade, machine learning has given us self-driving cars, practical speech recognition, effective web search, and a vastly improved understanding of the human genome. Machine learning is so pervasive today that you probably use it dozens of times a day without knowing it. Many researchers also think it is the best way to make progress towards human-level AI. In this class, you will learn about the most effective machine learning techniques, and gain practice implementing them and getting them to work for yourself. More importan

'XNOR.ai is, essentially, a bit of clever computer-native math that enables AI-like models for vision and speech recognition to run practically anywhere. It has the potential to be transformative for the industry.'

"api.ai equips developers with a simple way to make their products listen, understand, and talk to users. The api.ai platform combines natural language understanding with speech recognition and synthesis, enabling speech interfaces to be easily added to any solution."

"A face is all that's needed. AI Powered Face Recognition & Digital Identity Verification Solutions."

"Conversational UX Platform.™ Now we're talking! Build brand-unique, natural language interactions for bots, applications, services, and devices"