Six Technology Trends that are going to redefine AI

by February 13, 2017 0 comments

The market for artificial intelligence (AI) technologies is growing at a rapid pace and startups working in this particular area are getting acquired by the internet giants. There is a significant increase in investment and adoption by enterprises. Forrester Research predicted a greater than 300% increase in investment in artificial intelligence in 2017 compared with 2016. IDC estimated that the AI market will grow from $8 billion in 2016 to more than $47 billion in 2020.

Coined by John MacCarthy in 1955 to describe a new computer science sub-discipline, “Artificial Intelligence” today includes a variety of technologies and tools.

Artificial intelligence (AI) is more relevant than ever and businesses are using AI to provide better services to customers. According to Gartner, “Artificial intelligence (AI), a topic of interest for over 20 years, is, at last, finding a rapid uptake as a tool to provide better customer service.” The future of AI can seem scary, but businesses can harness the power of AI to deliver better customer support and to treat customers more like humans.

Let’s take a look at top trends which are going to dominate AI in the coming years.

Natural language generation

Natural Language Generation is a subfield of artificial intelligence (AI) which produces language as output on the basis of data input. This technology has being employed, primarily to improve human productivity, customer engagement, and operational efficiency.

With the explosion of big data enterprises are under tremendous pressure to interpret and analyze the data in real-time. A machine can communicate ideas from data at extraordinary scale and accuracy in a particularly articulate manner.  NLG is the basic necessity for developing an AI technology which has the potential to understand and decipher the vast amount of data.

Intelligent apps

By 2018, Gartner expects most of the world’s largest 200 companies to exploit intelligent apps and utilize the full toolkit of big data and analytics tools to refine their offers and improve customer experience.

Intelligent apps and digital assistants have the potential to transform the workplace by making everyday tasks easier. According to Gartner, intelligent apps are not limited to new digital assistants and in the future, every existing software category from security tooling to enterprise applications such as marketing or ERP will be powered with AI enabled capabilities. Using AI, technology providers will focus on three areas — advanced analytics, AI-powered and increasingly autonomous business processes and AI-powered immersive, conversational and continuous interfaces.

Connected things

With the advent of IoT, the connected ecosystem will become intelligent things delivering the power of AI enabled systems everywhere including the home, office, factory floor, and medical facility.

As intelligent things evolve and become more popular, they will shift from a stand-alone to a collaborative model in which they will communicate with one another to accomplish tasks.

AI-optimized hardware

Like any other technology, AI will be having its own ecosystem and we will see Graphics processing units (GPU) and appliances designed specifically to efficiently run AI-oriented computational jobs. We all have witnessed how Nvidia went from powering video games to revolutionizing artificial intelligence.

According to an estimate by Forbes, there are an estimated 3,000 AI startups worldwide, and many of them are building on Nvidia’s platform. They’re using Nvidia’s GPUs to put AI into apps for trading stocks, shopping online and navigating drones. There’s even an outfit called June that’s using Nvidia’s chips to make an AI-powered oven.

Deep learning platforms

Deep Learning has enabled many practical applications of machine learning. AI is the future of human civilization and with deep learning’s help; AI has the potential to break new grounds.

Deep learning is a special type of machine learning consisting of artificial neural networks with multiple abstraction layers. Right now it is currently used in pattern recognition and classification applications supported by very large data sets.

Virtual agents

We’re all familiar with Siri, Google Now, Cortana and Alexa. From simple chatbots to advanced systems that can network with humans, virtual assistants are hot these days. They are currently used in customer service and support and as a smart home manager.

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