Robots have transcended the realm of sci-fi fantasy and are now making revolutionary waves in several industries. Industries that deal with complex, life-threatening tasks have been enjoying tremendous benefits from robots. From being controlled by a human operator to now being fully autonomous, robotics has vastly grown. Equipped with cutting-edge technologies, some robots today are designed such that they closely emulate human intelligence, in one form or another. Due to this, we see the use cases of robots in areas that need human intelligence and decision-making capabilities.
Retail Industry is looking at Artificial intelligence (AI) and machine learning (ML) as a solution to take their organization to the next level of productivity and customer experience. To explain this better, let us look at it this way – Retail companies have access to a massive amount of data about their customers and their shopping preferences. It is difficult for the companies to drill down into these huge mines of useful data and analyze it properly and derive actionable insights in real time. Therefore, massive amounts of this useful information could go waste which would otherwise have helped in increasing sales conversion rates or enhancing the customer satisfaction. With the help of AI and ML, the huge amount of big data could be used in creating web shops that take customer information and turn it into targeted shopping experiences or online chatbots that can easily answer questions and assist customers, or in-store intelligence to make the customer experience even more interactive.
"I have several books on data science and R, as well as other similar subjects and programming languages, in my personal library. However, this book is a great blend of important data science topics and R programming that will make it a great reference for anyone working in this important and immensely popular area. I highly recommend this book for college students learning what it takes to start their career in data science or even current professionals wanting to make a career change or who just want to know more about the subject (and do some R programming as well)." "Due to the self-contained introduction to many of the features of R and RStudio, Graham J. Williams The Essentials of Data Science, Knowledge Discovery Using R would make an excellent recommended or supplementary text for a course that plans to use the rattle package. This book would also serve as a great resource for those with an interest in data science who would like a hands-on approach to learning R and gettting a flavor for a handful of topics within data science."
One of the hot trends in artificial intelligence (AI) revolves around the use of deep learning (DL) technologies for image and video classification. These AI-driven applications use computer vision to classify or categorize an image or video file on the basis on its visual content. So, what is deep learning? In a few words, DL is a subset of machine learning (ML), and one of the key building blocks for AI solutions. It uses artificial neural networks as the underlying architecture for training algorithms, or models.
An automatic-speech-recognition system -- such as Alexa's -- converts speech into text, and one of its key components is its language model. Given a sequence of words, the language model computes the probability that any given word is the next one. For instance, a language model would predict that a sentence that begins "Toni Morrison won the Nobel" is more likely to conclude "Prize" than "dries". Language models can thus help decide between competing interpretations of the same acoustic information. Conventional language models are n-gram based, meaning that they model the probability of the next word given the past n-1 words.
This chart shows AI use by retail organizations worldwide in 2018, by operating model. When it comes to artificial intelligence, machine learning is retailers go-to AI use across all business types, according to Capgemini. Artificial intelligence is an umbrella term, encompassing a wide variety of automated technologies. Machine learning refers to the process of building a system where a user can feed it new information and it can process that information based on previous data the machine has received, making decisions and taking actions without being explicitly programmed to do so. The study also found that retailers are primarily using AI for consumer-facing projects.
According to a Deloitte report, "A strong customer experience can not only lead to stronger financial performance but also form the basis for competitive differentiation. Successfully differentiating the brand both in terms of products and the experience can have a positive impact on a company's bottom line with higher conversion rates and increased customer loyalty." Not surprisingly, Gartner has predicted that over 50% of organizations will redirect their investments to CX (customer experience) innovations in 2019. But where should you start -- is that the question echoing in your mind as you read these words on your screen? Well, if you ask us, investing in customer support technology can give you great results in terms of improving your CX.
When it comes to artificial intelligence, machine learning is retailers go-to AI use across all business types, according to Capgemini. Artificial intelligence is an umbrella term, encompassing a wide variety of automated technologies. Machine learning refers to the process of building a system where a user can feed it new information and it can process that information based on previous data the machine has received, making decisions and taking actions without being explicitly programmed to do so. The study also found that retailers are primarily using AI for consumer-facing projects. Seventy-four percent of AI use cases are for customer-facing projects, while only 16 percent are dedicated to operations.