Hollywood has done a terrific job warning us about the dangers of artificial intelligence (AI). There is a much more benign side to artificial intelligence involving machine learning (ML) that is changing how businesses conduct their operations and many people live their daily lives. Nick Ismail (@ishers123) explains, “Machine learning’s development stems from the mid-20th century where it was defined by Arthur Samuel as a ‘field of study that gives computers the ability to learn without being explicitly programmed’.”[1] Bernard Marr (@BernardMarr) notes that Samuel was working at IBM during the 1950s and his “earliest experiments involved teaching machines to learn to play checkers.”[2] Dr. T. N. Swaminathan, Professor of Marketing at Great Lakes Institute of Management in Chennai, India, adds, “Machine Learning is a subfield of Artificial Intelligence which evolved from Pattern Recognition and Computational Learning theory. … Every time you visit Amazon — you see product recommendations — either what you searched online or bought the last time or what other people bought! Ever wondered how Amazon always has a recommendation that tempts you and finally lightens your wallet! Well, that’s a Machine Learning Algorithm called ‘Recommender Systems’ working in the backdrop. It learns every user’s personal preferences and makes recommendations based on a repeated set of activities.”[3]

Machine Learning and Your Business

Although machine learning has broad applicability in the business world, to leverage it for the greatest benefit companies need to understand how it can be used in specific circumstances. Ismail explains, “To successfully adopt in the style of companies like Amazon, businesses need to remember that machine learning doesn’t solve problems by itself. The technology delivers actionable insights to users based on the data they’ve been given. To get the most out of this technology businesses need a human touch, and a good, reliable data set. This will not only impact the delivery of services, but also drastically improve internal operations: bridging departments and producing business transparency.” As business leaders come to understand how machine learning can be applied across an organization, it will be become a ubiquitous tool in their kit. Vivian Rosenthal (@vivianrosenthal), founder of Snaps, writes, “Not everyone recognizes the increasingly vital role that machine learning and other artificial intelligence technologies are shaping our day-to-day lives right now. … Digital and real world businesses are leveraging this technology to drive business outcomes, applying machine learning to their owned data sets to bring the best consumer experiences to the forefront as quickly and efficiently as possible, and they’re getting incredible results.”[4] Ismail notes a few areas where ML has already made an impact. They are:

• Cyber Security. “It is vital cyber security companies adopt this type of technology to finally get ahead of the cyber criminals who have been winning the cyber war for so long.”
• Travel. “The immediate impact of driverless cars is in sight. Within five years they will be a more than common presence on roads across the globe. … Equally, machine learning has a role to play in international travel. With the repetition of tasks you find in corporate travel machine learning embedded in online services could enable anticipating preferences, automatically booking recurring trips, or categorizing your travel expenses.”
• Manufacturing. “The manufacturing industry is being revolutionized by the internet of things devices, which generate huge amounts of data to help improve efficiency and drive innovation. However, without machine learning this data is underutilized. The technology will be able to detect anomalies to prevent machine failures and also help drive robot proof of concepts to drive optimization.”
• Finance. “Financial institutions will increasingly lean on machine learning to devise new business opportunities, deliver customer services and even detect banking fraud as it is taking place.”
• Retail. “Similar to the impact on global brands like Amazon, Netflix and Facebook, machine learning has the ability to truly transform the retail industry with one word: personalization. … It allows retailers to identify why individual shoppers shop when they do, and buy what they do in incredible detail. It will help change the idea of customer service.”
• Entertainment, Hospitality, and Fashion. “[ML] can help optimize the entertainment experience for viewers at home. … With the emergence of cloud computing, hotels can have access to revenue management systems, which when leveraged with machine learning can automatically collect large and complex data sets. … Fashion … success … relies on staying at the forefront of change. The industry on the cusp of a machine learning revolution where the technology will help deliver accurate predictions about style and tastes, while being able to identify items that appeal to individual consumers.”

As you can see, the possibilities are nearly endless. Rosenthal writes, “Through the accessibility of cloud computing, the ubiquitous availability of parallel processing power, near free data storage and an exponential increase in data input from consumers, we have reached a perfect storm that is enabling artificial intelligence to truly have its day in the sun.”

Machine Learning and the Cloud

Rosenthal asserts, “We are at the dawn of an era in which machine learning will be a horizontal layer across all businesses, and managers should begin exploring and investing in these technologies now. Consumers will expect intelligence from their services, and brands that build core competencies in data science and machine learning stand to create defensible competitive advantages over time.” The cloud is going to play an important role in the business environment and ML will help ensure it lives up to its potential. Marty Puranik, founder and CEO of Atlantic.Net, writes, “By merging with machine learning, cloud computing is in the midst of a pivot towards becoming more interconnected and intelligent.”[5] He goes on to discuss technology areas in which machine learning is impacting the cloud. They are:

• Cognitive computing. “Cognitive computing is rapidly evolving the landscape of how we communicate and do business online. Using data mining, natural language processing and pattern recognition, the models developed aim to simulate human thinking. The promise is for intelligent computing that’s seamlessly integrated. … In the coming years, we should expect more programs powered by AI engines that employ visual recognition, face detection, emotion detection, video analytics, etc. to showcase self-learning systems.”
• Chatbots and personal assistants. “Personal assistants and chatbots belong to a breed of technology designed to simulate a conversation or interaction with human users. By learning from past choices and conversational patterns, machine learning engines can make these bots more powerful in their ability to offer a personal interactive experience. And the demand for it is growing.”
• Internet of Things. “Acting as the unifier for the now two decade old trend, data-driven cloud platforms have created a seamless virtual environment in which all the components of IoT can come together and advance to the next level. But it is machine learning that will be responsible for making IoT intelligent.”
• Business intelligence. “Before the cloud, most enterprise systems manually and locally collected data related to the habits of their users. Cloud computing enabled business to connect all this data together and find underlying patterns. With the introduction of machine learning, automation entered the picture. Such systems, which no longer require manual input, are extremely efficient.”
• Security and data hosting. “Cybersecurity has been using machine learning to become smarter. Complex algorithms analyze data flows sent from and to servers every millisecond looking for anomalous patterns to pinpoint intruders. Their goal: Eliminate false alerts and prevent attacks before they happen. Machine learning will also increasingly affect data hosting. With machine learning powered load balancing, data centers will be able to support better and faster data flow.”

Janakiram MSV (@janakiramm), an analyst at Janakiram & Associates, observes, “The cloud as we know it is going through a massive transformation. … The cloud in its latest avatar is emerging as a data-centric, intelligent platform ready to deal with the next generation of applications and workloads. … The adoption of this brand-new cloud will not only result in better revenues for the providers but also helps them deliver better capabilities that are driven by data.”[6]

Summary

Swaminathan concludes, “Today, more and more companies are using Machine Learning to improve their business decisions, increase productivity, deliver faster, respond sooner to the customer and do many more things. This is irrespective of the size of the company, Small, Medium or Super Large! With the exponential growth of technology, we not only need better tools to understand the data we currently have, but we also need to prepare ourselves for the data we will have in the near future.” Maybe it’s time for your business to explore the possibilities of cognitive computing and the cloud.

Footnotes
[1] Nick Ismail, “What is machine learning?” Information Age, 12 June 2017.
[2] Bernard Marr, “What Is Machine Learning – A Complete Beginner’s Guide In 2017,” Forbes, 4 May 2017.
[3] T. N. Swaminathan, “Demystifying Machine Learning,” BW Disrupt, 15 May 2017.
[4] Vivian Rosenthal, “How Machine Learning Will Reinvent Business,” Forbes, 30 May 2017.
[5] Marty Puranik, “5 ways machine learning is impacting cloud computing,” Information Management, 5 June 2017.
[6] Janakiram MSV, “Welcome To The Era Of Intelligent Cloud Powered By Machine Learning,” Forbes, 28 March 2017.