Emerging Technologies Automation with IoT and AI

1. Natural Language Generation Natural language generation is an AI sub-discipline that converts data into text, enabling computers to communicate ideas with perfect accuracy. It is used in customer service to generate reports and market summaries and is offered by companies like Attivio, Automated Insights, Cambridge Semantics, Digital Reasoning, Lucidworks, Narrative Science, SAS, and Yseop. 2. Speech recognition Siri is just one of the systems that can understand you. Every day, more and more systems are created that can transcribe human language, reaching hundreds of thousands through voice-response interactive systems and mobile apps. Companies offering speech recognition services include NICE, Nuance Communications, OpenText and Verint Systems. 3. Virtual Agents A virtual agent is nothing more than a computer agent or program capable of interacting with humans.  The most common example of this kind of technology is chatbots.  Virtual agents ar...

It is no doubt that the sub-field of machine learning / artificial intelligence has increasingly gained more popularity in the past couple of years. As Big Data is the hottest trend in the tech industry at the moment, machine learning is incredibly powerful to make predictions or calculated suggestions based on large amounts of data. Some of the most common examples of machine learning are Netflix’s algorithms to make movie suggestions based on movies you have watched in the past or Amazon’s algorithms that recommend books based on books you have bought before. So if you want to learn more about machine learning, how do you start?  Machine learning algorithms can be divided into 3 broad categories — supervised learning, unsupervised learning, and reinforcement learning.Supervised learning is useful in cases where a property ( label ) is available for a certain dataset ( training set ), but is missing and needs to be predicted for other instances. Unsupervised learni...

A Simple Way to Understand Machine Learning vs Deep Learning Understanding how today’s artificial intelligence works might seem overwhelming, but it really boils down to two concepts you probably have heard of before: “machine learning” and “deep learning”. Neither are brand new ideas, but the way they’re used to describe intelligent machines seems to constantly evolve. Machine learning and deep learning are how Netflix knows what you might want to watch next, or how Facebook can recognize your friends’ face in a photo, or  how a support agent can figure out if you’ll be satisfied with your customer service . So what are these buzzwords that still dominate the conversations about artificial intelligence, and how exactly are they different? And what do they mean for customer service?   What is machine learning? Here’s a basic definition of machine learning:  “Algorithms that parse data, learn from that data, and then apply what they’ve learned to make i...

The 5 Best Amazon Alexa Skills for Business Productivity Categories:  amazon ,  Amazon Alexa Digital assistants  like Amazon’s Alexa, which is the persona associated with the Amazon Echo, have made existing technology even more convenient. They’re most often used in smart homes, but the Amazon Alexa Skills kit has many uses for the office as well. How to Enable a Skill on the Amazon Echo You can enable Amazon Alexa Skills through three different methods: Voice:  Say “Alexa, open [name of skill.” This is the fastest method, but you obviously have to know the exact name of the skill in order to turn it on. App:  Open the navigation menu on the left-side of the Alexa app and tap “Skills.” From there, simply enable the skills you want to use. Website:  Find a skill you want to use on the Amazon website, install it and then click “Enable.” 5 Essential Amazon Alexa Skills you must Enable 1. Schedule Management As you’re jumping around fr...

Microsoft researchers have created technology that uses artificial intelligence to read a document and answer questions about it about as well as a human. It’s a major milestone in the push to have search engines such as Bing and intelligent assistants such as Cortana interact with people and provide information in more natural ways, much like people communicate with each other. A team at  Microsoft Research Asia  reached the human parity milestone using the Stanford Question Answering Dataset, known among researchers as  SQuAD . It’s a machine reading comprehension dataset that is made up of questions about a set of Wikipedia articles. According to the SQuAD leaderboard, on Jan. 3, Microsoft submitted a model that reached the score of 82.650 on the exact match portion. The human performance on the same set of questions and answers is 82.304. On Jan. 5, researchers with the Chinese e-commerce company Alibaba submitted a score of 82.440, also about the same as a human. Th...

To find success with artificial intelligence, banks and credit unions will need to cultivate new capabilities — from machine learning to natural language processing. Computer scientist and celebrated futurist Ray Kurzweil says artificial intelligence will match human intelligence by 2029, and that by 2045, it will have multiplied the human biological machine intelligence of our civilization a billion times. Predictions like this abound amid the hype surrounding AI. Real understanding however, is less common. Many enterprises are unclear about what constitutes AI, where it can be applied, and how to prioritize its use cases within the organization. In a survey commissioned by Infosys on the state of AI adoption, half of the 1,600 respondents said that not knowing where AI could assist was one of their biggest challenges. A good understanding of the technologies under the umbrella of artificial intelligence is key. Many of these technology pieces have seen rapid and impressive e...