The year 2016 has seen quite a lot of disruptions in the field of technology, breaking all the boundaries and rising above expectations. Ranging from the concept and trial run of driverless cars to Google's DeepMind platform, and AlphaGo, these technologies were not even expected in the coming decade. All of these run on an underlying concept of Artificial Intelligence, which has helped companies turn the impossible into reality. Things have only started to come into existence recently, but there is still a world of newer possibilities and modifications that will be witnessed in the coming years.
Artificial Intelligence has been a rage in A2016 in India as well, owing to its utility and advantages. Globally renowned companies have been incorporating AI into their systems, and aiming to tap newer audiences and attract more business. Seeing the current upward movement, it is an accepted fact that AI/Bots will replace workers, which will in turn have a quantum impact on the social, economic, and technical front. The hottest segment of this hottest trend is the market for chatbots. The movement towards conversational interfaces will accelerate in the coming years.
What next? Breakthrough in Emotional Understanding!
With increasingly accurate cameras, voice and facial recognition, computers are better able to detect our emotional state. With the help of Artificial Intelligence, all of this has been possible. It gives companies better understanding of their customers also, and insight into their like and dislikes. A similar attempt has been made by the famous outdoor clothing company The North Face, which announced a partnership with IBM Watson and e- commerce company Fluid to launch a new AI-powered shopping tool to make it easier to find the right item.
One major improvement that researchers wish to attain in the field of AI and ML in 2017 is Data Efficiency. This aims to reduce the amount of data that machine-learning systems require to successfully implement models with high accuracy. In other words, how to do more, with less data. Teaching a neural network to identify basic patterns currently needs thousands of data points, which makes the process complex and long. Organizations are taking note of this efficiency, predictability, increased productivity and business innovation that AI offers and are starting to slowly embrace the trend.
この記事は SME World の February 2017 版に掲載されています。
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この記事は SME World の February 2017 版に掲載されています。
7 日間の Magzter GOLD 無料トライアルを開始して、何千もの厳選されたプレミアム ストーリー、9,000 以上の雑誌や新聞にアクセスしてください。
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