In the last article, we learnt about LUIS - Language Understanding Intelligent Service provided by Azure and then learnt to create a conversation app. This was fundamental to create a cognitive service in Azure such that we can obtain a subscription key and endpoint to use in our application. This article focuses on following up on the app created in Azure to make a full-fledged AI Chatbot. We can learn about all these services provided in Azure for Machine Learning through the article, Azure Cognitive Services. Also read the last article, Luis – Create a conversation app this follows up on.

Andrés Pérez Soderi has a joke he likes to tell when asked to describe how his company came together. "A Russian, a Chinese and a Venezuelan walked into a bar, and they end up making software so they can understand each other," Soderi says. Venezuelan-born Soderi is one of the three founders of US-based artificial intelligence startup, Sanas. Together with Chinese-born co-founders, Shawn Zhang, and Russian-born, Maxim Serebryakov, and their team, he has been working to unpick the nuances of accents to make communication easier for people from different backgrounds. That could have huge implications for any marketer who wants to improve customer experience through voice channels by helping both customers and staff be better understood.

Researchers have found a way to marry human creativity and artificial intelligence (AI) creativity to dramatically boost the performance of deep learning. A team led by Alexander Wong, a Canada Research Chair in the area of AI and a professor of systems design engineering at the University of Waterloo, developed a new type of compact family of neural networks that could run on smartphones, tablets, and other embedded and mobile devices. The networks, called AttoNets, are being used for image classification and object segmentation, but can also act as the building blocks for video action recognition, video pose estimation, image generation, and other visual perception tasks. "The problem with current neural networks is they are being built by hand and incredibly large and complex and difficult to run in any real-world situation," said Wong, who also co-founded a startup named DarwinAI to commercialize the technology. "These on-the-edge networks are small and agile and could have huge implications for the automotive, aerospace, agriculture, finance, and consumer electronics sectors."