25% of customer service and support operations will integrate virtual customer assistant (VCA) or chatbot technology across engagement channels by 2020, according to Gartner.
The digital landscape has changed remarkably over the past decade. Almost every business, irrespective of the industry is realizing the digitization benefits and embracing it as well. With this, digital data is generated, faster than ever. In fact, some of the industries are at a point where manual data analysis is a next to impossible job. This has driven the rise of Machine Learning (ML), which is the ability of machines to analyze big data and extract information, just like humans do.
The accelerated market hype around Artificial Intelligence has made it a buzzword of almost every industry. Businesses, irrespective of their industry are interested to invest in the potential of AI to automate, assist, and augment various value-based tasks.
The ever growing interest of businesses and the market hype for Artificial Intelligence (AI) is making it one of the predominant element of tech-industry. AI, essentially is a broad term that defines the ability of machines to exhibit human intelligence. While real-AI is a near future, the current AI technologies are still offering a level playing field to almost every industry today, including healthcare, manufacturing, transportation, and many others.
Artificial Intelligence (AI) remained the driving force of various industries in 2017. With so many tech giants and startups already delving into the AI ecosystem, it is expected to grow with better use cases in the year 2018. Considering the acceptance, development, and applications of AI, here we are with significant opportunities and perils that this ingenious technology will put forth in 2018.
Can you imagine a mobile app automating and controlling a number of tasks for the users, without being explicitly programmed for it. Well, that might sound fanatic, but it’s a practicable model today. Thanks to Machine Learning!
Machine Learning (ML) is subset of Artificial Intelligence (AI) that analyses a set of data, builds an analytical model, and then predicts accordingly. By implementing ML to mobile apps, businesses can ensure better experience to the existing and anticipated users.
Machine Learning (ML) has turned out to be one of the profound applications of Artificial Intelligence (AI). From Virtual Assistants to traffic predictions, ML is refining the way some of the conventional tasks are performed. With ML holding its strength in pattern recognition and cognitive learning, it has found its significance in intelligent application development.
Artificial Intelligence (AI) is everywhere. Possibility is that you are using it in one way or the other and you don't even know about it. One of the popular applications of AI is Machine Learning (ML), in which computers, software, and devices perform via cognition (very similar to human brain). Herein, we share few examples of machine learning that we use everyday and perhaps have no idea that they are driven by ML.