How artificial intelligence is transforming the world

What is artificial intelligence?

Artificial intelligence (AI) is the basis for mimicking human intelligence processes through the creation and application of algorithms built into a dynamic computing environment. Stated simply, AI is trying to make computers think and act like humans.

Achieving this end requires three key components:

• Computational systems
• Data and data management
• Advanced AI algorithms (code)

The more humanlike the desired outcome, the more data and processing power required.

How did artificial intelligence originate?

At least since the first century BCE, humans have been intrigued by the possibility of creating machines that mimic the human brain. In modern times, the term artificial intelligence was coined in 1955 by John McCarthy. In 1956, McCarthy and others organized a conference titled the “Dartmouth Summer Research Project on Artificial Intelligence.” This beginning led to the creation of machine learning, deep learning, predictive analytics, and now to prescriptive analytics. It also gave rise to a whole new field of study, data science.

Why is artificial intelligence important?

Today, the amount of data that is generated, by both humans and machines, far outpaces humans’ ability to absorb, interpret, and make complex decisions based on that data. Artificial intelligence forms the basis for all computer learning and is the future of all complex decision making. As an example, most humans can figure out how to not lose at tic-tac-toe (noughts and crosses), even though there are 255,168 unique moves, of which 46,080 end in a draw. Far fewer folks would be considered grand champions of checkers, with more than 500 x 1018, or 500 quintillion, different potential moves. Computers are extremely efficient at calculating these combinations and permutations to arrive at the best decision. AI (and its logical evolution of machine learning) and deep learning are the foundational future of business decision making.

Machine Learning

What Is Machine Learning?

A subset of artificial intelligence (AI), machine learning (ML) is the area of computational science that focuses on analyzing and interpreting patterns and structures in data to enable learning, reasoning, and decision making outside of human interaction. Simply put, machine learning allows the user to feed a computer algorithm an immense amount of data and have the computer analyze and make data-driven recommendations and decisions based on only the input data. If any corrections are identified, the algorithm can incorporate that information to improve its future decision making.

Topics

• How Does Machine Learning Work?
• Why Is Machine Learning Important?
• Machine Learning Use Cases

How Does Machine Learning Work?

Machine learning is made up of three parts:

• The computational algorithm at the core of making determinations.
• Variables and features that make up the decision.
• Base knowledge for which the answer is known that enables (trains) the system to learn.

Initially, the model is fed parameter data for which the answer is known. The algorithm is then run, and adjustments are made until the algorithm’s output (learning) agrees with the known answer. At this point, increasing amounts of data are input to help the system learn and process higher computational decisions.

Why Is Machine Learning Important?

Data is the lifeblood of all business. Data-driven decisions increasingly make the difference between keeping up with competition or falling further behind. Machine learning can be the key to unlocking the value of corporate and customer data and enacting decisions that keep a company ahead of the competition.

Machine Learning Use Cases

Machine learning has applications in all types of industries, including manufacturing, retail, healthcare and life sciences, travel and hospitality, financial services, and energy, feedstock, and utilities. Use cases include:

• Manufacturing. Predictive maintenance and condition monitoring
• Retail. Upselling and cross-channel marketing
• Healthcare and life sciences. Disease identification and risk satisfaction
• Travel and hospitality. Dynamic pricing
• Financial services. Risk analytics and regulation
• Energy. Energy demand and supply optimization

Artificial Intelligence and Machine Learning in Business

1. Chatbots:

Artificial intelligence continues to be a hot topic in the technology space as well as increasing its inception into other realms such as healthcare, business, and gaming. AI-powered chatbots in enterprises will also see an influx of people get more comfortable with how AI can actually benefit businesses versus, say, take away their jobs. From an analytical standpoint, AI can be incorporated into interfaces to change how they receive and understand data.

Chatbots, in particular, are always on, delivering smart and flexible analytics through conversations on mobile devices using standard messaging tools and voice-activated interfaces.This dramatically reduces the time to collect data for all business users, thereby accelerating the pace of business and streamlines the way analysts use their time, preparing companies for the growing data needs of the near future.

2. Artificial Intelligence in eCommerce:

Artificial Intelligence technology provides a competitive edge to e-commerce businesses and is becoming readily available to companies of any size or budget. Leveraging machine learning, AI software automatically tags, organizes and visually searches content by labeling features of the image or video.

AI is enabling shoppers to discover associated products whether it is size, color, shape, or even brand. The visual capabilities AI is improving every year. By first obtaining visual cues from the uploaded imagery, the software can successfully assist the customer in finding the product they desire. Many e-commerce retailers are already becoming more sophisticated with their AI capabilities, and I only expect this to grow in the future.

3. AI to Improve Workplace Communication:

Current business communication is overloaded with content, channels, tools, and so-called solutions, depriving individuals (and companies) from hitting targets while also harming work-life balance. Artificial Intelligence will help businesses improve communication internally and externally by enabling individual personalization for each professional, allowing for enhanced focus and increased productivity.

With such AI personalization, each individual will be empowered thanks to an intelligent virtual assistant, helping take care of mundane or repeatable tasks, save time by understanding your needs and goals, as well as recommend next-best-action to take…as to utilize time much more efficiently, without requiring any extra effort. In the short to long run, business processes will improve, innovation will grow as employees will clear their tasks, and stress may decrease.

4. Human Resource Management:

AI and Machine learning are going to drastically and irrevocably change how HR and recruitment work in every company and this is going to be awesome. In fact, HR is likely to be one of the first areas of business that will benefit from AI for two simple reasons. Firstly there are tons of top quality data in HR, and secondly, HR is one part of any company that is both essential and yet feels the pressure of time.

If aspects of the recruiting and HR job can be automated, the HR workers can have the freedom to directly work with people in the business or potential hires, spending the quality human time necessary for a great HR department. It might seem paradoxical but the more Artificial Intelligence a company deploys in HR, the more ‘Human’ a company it can be.

Artificial Intelligence will essentially take out all of the “worst” elements of every HR professionals job (mundane screening, time-consuming paperwork, and annoying data entry) as well as deliver powerful tools and insights are a bonus to make their work better. HR’s automatic generation of top quality data and the incredible benefits of AI make it one of the first places to experience the 4th industrial revolution.

5. AI in Healthcare:

In the year ahead, and particularly in the next five to ten years, artificial intelligence is going to have a big impact on the healthcare industry and the ways in which healthcare related companies utilize AI. Here is a short note from Dr. Jeff Dunn, CEO of Redivus Health. Redivus Health is a transformative mobile app used by healthcare providers to prevent medical errors by offering both clinical decision support during critical medical events as well as documenting those events electronically in real time.

AI presents opportunities for our application to take the data we have gathered from patients and be able to clinically innovate to improve patient outcomes to an even greater extent. AI improves reliability, predictability, and consistency with quality and patient safety. For us, AI, as applied to software, is used as a decision augmentation tool, but it should not have free reign without human interaction and guidance. While it can’t replace doctors and nurses, it can make them more effective, efficient and happier on the job as it takes the cognitive burden off our providers — which increases confidence as well as reduces stress and anxiety.

6. Intelligent Cybersecurity:

In regard to cybersecurity, Artificial Intelligence is making great strides. Although AI is considered to be in its infancy in cybersecurity and cannot always effectively address all issues, it works successfully in data protection. AI allows companies to detect vulnerabilities or anomalous user behavior in such business applications as ERP or Financial systems.

A system of behavior anomalies analysis in computer systems resembles the world’s most protected airport: when you are on the way to it, the security system has enough time to analyze your identity; you are examined by cameras and in case of any signs of danger, you are intercepted. Deep learning is empowered to see if a user has any suspicious activity. So, even if attackers have penetrated into a victim’s system, they start taking actions that differ from the usual ones and as a result, they do not leave unnoticed and their damage is prevented.

7. Artificial Intelligence in Logistics and Supply Chain:

When combined with customer data and analytics, physical artificial intelligence removes friction from the customer experience. Artificial intelligence empowers businesses to act on consumer data to drive improvements throughout many areas of supply chain operations. Mobile technology and the “Uberization” of things have made consumers hungry for AI.

Consumers demand shorter delivery waits from retailers and retailers will expect the same from manufacturers and distribution centers. Autonomous trucks and robotic picking systems allow supply chains to make fulfillment seven days a week. Within the next five years, the shipping term “business days” will become obsolete as consumers expect delivery on nights and weekends

8. Sports betting Industry:

In its article Sports trading and AI: Taking the human out of sports betting, Gambling Insider argues that, “Just as more scientific analysis of sport is changing how coaches, trainers, and clubs play their respective games, greater analysis of sporting events is helping odds making database operators evaluate the potential permutations of each sporting event, increasing the accuracy of that respective odd and thereby making the subsequent odds determination easier.”

Human traders cannot compete with artificial intelligence when it comes to analyzing huge volume of data. With AI we can perform analysis of the vast volume of sporting analysis data available to maximize our accuracy when it comes to predicting future outcomes. This proves especially fruitful in today’s expansive betting market, where a large number of games and bet types are offered to an increasingly insatiable betting public.

9. Streamlined Manufacturing with AI:

For most customers when it comes to AI or Machine Learning, the magic happens when vast amounts of data can be streamed at milliseconds from the machine and process data of various databases. This provides actionable insights that can help these customers reduce non-productive downtime, predict failures or build a “golden batch” that can be benchmarked across all production lines.

An example is a global adhesive manufacturing customer that is pulling data from their lab systems where the raw material is brought in and tested for quality. Data is also being pulled from what is called their “cooking process” where, based on dynamic conditions, AI and Machine Learning make real time recommendations about which materials to inject at what time to ensure continuity of the process. This helps the manufacturer keep a continual “golden batch” manufacturing of their products, improving yield and customer satisfaction.

10. Casino/Hotels/Integrated Resorts:

AI can help hotels/casinos discover customer segments that they may not realize were there. Which customers want to be near the pool, which ones need three morning papers before they can tackle the day. Armed with this kind of information, hotels can understand what matters the most to its guests at the individual level, enabling them to anticipate their guest’s needs before even the guests are aware of them.

Even more, hotels can understand key characteristics of their most profitable customers and recognize the next important ones when he or she happens to login onto the hotel’s online reservation system. The use of deep neural networks and image classifiers can analyze and parse images, which can enable hotel marketers to monitor the images that provide the highest booking conversion rate through each channel. AI can also be used to compute dynamic clusters of guests to create fluid segmentation in real-time.

11. Retail:

Shopping online creates rich data footprints regarding the individual preferences, spending habits and preferred channels of individual consumers. Feeding these digital breadcrumbs into an AI-engine helps bring curated shopping journeys to mass audiences. Automated bots can create lifelike, seamless customer service experiences, addressing the consumer on their purchase history and known preferences.

On the marketing side, AI may deliver that extra dash of relevancy programmatic advertising has been waiting for all these years. On the consumer side, AI helps create individualized display ads that website visitors want to see, while on the accounting side, “the bots handle invoicing and payment for these transactions, giving marketers more time to focus on the big picture. With AI, predictive customer service and marketing could be just around the corner.

As you can see that the use of artificial intelligence is prevalent in every aspect of the business. Today every company is in some way an IT company. Hence as a business leader, you need to move with the market and take steps to leverage this technology to its best possible extent.

Uses and Applications of Artificial Intelligence and ML in Business

1. Alibaba

Chinese company Alibaba is the world’s largest e-commerce platform that sells more than Amazon and eBay combined. Artificial intelligence (AI) is integral in Alibaba’s daily operations and is used to predict what customers might want to buy. With natural language processing, the company automatically generates product descriptions for the site. Another way Alibaba uses artificial intelligence is in its City Brain project to create smart cities. The project uses AI algorithms to help reduce traffic jams by monitoring every vehicle in the city. Additionally, Alibaba, through its cloud computing division called Alibaba Cloud, is helping farmers monitor crops to improve yield and cuts costs with artificial intelligence.

2. Alphabet — Google

Alphabet is Google’s parent company. Waymo, the company’s self-driving technology division, began as a project at Google. Today, Waymo wants to bring self-driving technology to the world to not only to move people around, but to reduce the number of crashes. Its autonomous vehicles are currently shuttling riders around California in self-driving taxis. Right now, the company can’t charge a fare and a human driver still sits behind the wheel during the pilot program. Google signaled its commitment to deep learning when it acquired DeepMind. Not only did the system learn how to play 49 different Atari games, the AlphaGo program was the first to beat a professional player at the game of Go. Another AI innovation from Google is Google Duplex. Using natural language processing, an AI voice interface can make phone calls and schedule appointments on your behalf. Learn even more about how Google is incorporating artificial intelligence and machine learning into operations.

3. Amazon

Not only is Amazon in the artificial intelligence game with its digital voice assistant, Alexa, but artificial intelligence is also part of many aspects of its business. Another innovative way Amazon uses artificial intelligence is to ship things to you before you even think about buying it. They collect a lot of data about each person’s buying habits and have such confidence in how the data they collect helps them recommend items to its customers and now predict what they need even before they need it by using predictive analytics. In a time when many brick-and-mortar stores are struggling to figure out how to stay relevant, America’s largest e-tailer offers a new convenience store concept called Amazon Go. Unlike other stores, there is no checkout required. The stores have artificial intelligence technology that tracks what items you pick up and then automatically charges you for those items through the Amazon Go app on your phone. Since there is no checkout, you bring your own bags to fill up with items, and there are cameras watching your every move to identify every item you put in your bag to ultimately charge you for it.

4. Apple

Apple, one of the world’s largest technology companies, selling consumer electronics such as iPhones and Apple Watches, as well as computer software and online services. Apple uses artificial intelligence and machine learning in products like the iPhone, where it enables the FaceID feature, or in products like the AirPods, Apple Watch, or HomePod smart speakers, where it enables the smart assistant Siri. Apple is also growing its service offering and is using AI to recommend songs on Apple Music, help you find your photo in the iCloud, or navigate to your next meeting using Maps.

5. Baidu

The Chinese equivalent of Google, Baidu, uses artificial intelligence in many ways. They have a tool called Deep Voice that uses artificial intelligence and deep learning that only needs 3.7 seconds of audio to clone a voice. They use this same technology to create a tool that reads books to you in the author’s voice — all automated with no recording studio necessary.

6. Facebook

One of the primary ways Facebook uses artificial intelligence and deep learning is to add structure to its unstructured data. They use DeepText, a text understanding engine, to automatically understand and interpret the content and emotional sentiment of the thousands of posts (in multiple languages) that its users publish every second. With DeepFace, the social media giant can automatically identify you in a photo that is shared on their platform. In fact, this technology is so good, it’s better at facial recognition than humans. The company also uses artificial intelligence to automatically catch and remove images that are posted on its site as revenge porn.

7. IBM

IBM has been at the forefront of artificial intelligence for years. It’s been more than 20 years since IBM’s Deep Blue computer became the first to conquer a human world chess champion. The company followed up that feat with other man vs. machine competitions, including its Watson computer winning the game show Jeopardy. The latest artificial intelligence accomplishment for IBM is Project Debater. This AI is a cognitive computing engine that competed against two professional debaters and formulated human-like arguments.

8. JD.com

JD.com is the Chinese version of Amazon. Its founder Richard Liu expects and is driving toward having his company be 100% automated in the future. Right now, its warehouse is already fully automated, and they have been making drone deliveries of packages for the last four years. JD.com is driving business with artificial intelligence revolution, big data, and robotics while building the retail infrastructure for the 4th industrial revolution.

9. Microsoft

Artificial intelligence is a term that appears on Microsoft’s vision statement, which illustrates the company’s focus on having smart machines central to everything they do. They are incorporating intelligent capabilities to all its products and services, including Cortana, Skype, Bing, and Office 365, and are one of the world’s biggest AI as a Service (AIaaS) vendors.

10. Tencent

Chinese social media company Tencent has incorporated artificial intelligence into its operations in its quest to become “the most respected internet enterprise,” Tencent relies on artificial intelligence. It has 1 billion users on its app WeChat, but has extended its reach to gaming, digital assistants, mobile payments, cloud storage, live streaming, sports, education, movies, and even self-driving cars. One of the company’s slogans is “AI in all.” Tencent acquires huge amounts of information and insights about its customers that it processes and leverages to the company’s advantage.