“AI and ML Revolution: How MNCs Enhance Their Products to Lead in the Modern Era”

In today’s digitally-driven world, Artificial Intelligence (AI) and Machine Learning (ML) have become game-changers for multinational corporations (MNCs). These technologies have not only transformed the way these companies operate but have also elevated their products to the pinnacle of innovation. In this article, we’ll explore the manifold benefits that MNCs are reaping from AI/ML, showcasing how they’ve leveraged these advancements to become industry leaders.

Let us first understand what is Artificial Intelligence(AI), Machine Learning(ML) and deep learning.

What is Artificial Intelligence?

Artificial intelligence (AI) is a wide-ranging branch of computer science concerned with building smart machines capable of performing tasks that typically require human intelligence. AI is an interdisciplinary science with multiple approaches, but advancements in machine learning and deep learning are creating a paradigm shift in virtually every sector of the tech industry.

How does AI work?

Less than a decade after breaking the Nazi encryption machine Enigma and helping the Allied Forces win World War II, mathematician Alan Turing changed history a second time with a simple question: “Can machines think?”

Turing’s paper “Computing Machinery and Intelligence”(1950), and it’s subsequent Turing Test, established the fundamental goal and vision of artificial intelligence.

At its core, AI is the branch of computer science that aims to answer Turing’s question in the affirmative.

In their groundbreaking textbook Artificial Intelligence: A Modern Approach, authors Stuart Russell and Peter Norvig approach the question

AI is “the study of agents that receive percepts from the environment and perform actions.” (Russel and Norvig viii)

Norvig and Russell go on to explore four different approaches that have historically defined the field of AI:

1. Thinking humanly
2. Thinking rationally
3. Acting humanly
4. Acting rationally

The first two ideas concern thought processes and reasoning, while others deal with the behavior.

While these definitions may seem abstract to the average person, they help focus the field as an area of computer science and provide a blueprint for infusing machines and programs with machine learning and other subsets of artificial intelligence.

Types of AI

AI generally falls under two broad categories:

• Narrow AI: Sometimes referred to as “Weak AI,” this kind of artificial intelligence operates within a limited context and is a simulation of human intelligence.

A few examples of Narrow AI include:

1. Google search
2. Image recognition software
3. Siri, Alexa, and other personal assistants
4. Self-driving cars
5. IBM’s Watson

• Artificial General Intelligence (AGI): AGI, sometimes referred to as “Strong AI,” is the kind of artificial intelligence we see in the movies, like the robots from Westworld. AGI is a machine with general intelligence and, much like a human being, it can apply that intelligence to solve any problem.

How is AI used in everyday life?

Below are some AI applications that you may not realize are AI-powered:

• Online shopping and advertising

Artificial intelligence is widely used to provide personalized recommendations to people, based for example on their previous searches and purchases or other online behavior. AI is hugely important in commerce: optimizing products, planning inventory, logistics, etc.

• Web search

Search engines learn from the vast input of data, provided by their users to provide relevant search results.

• Digital personal assistants

Smartphones use AI to provide services that are as relevant and personalized as possible. Virtual assistants answering questions, providing recommendations, and helping organize daily routines have become ubiquitous.

• Artificial intelligence against Covid-19

In the case of Covid-19, AI has been used in thermal imaging in airports and elsewhere. In medicine, it can help recognize infection from computerized tomography lung scans. It has also been used to provide data to track the spread of the disease.

What is Machine Learning?

ML is a subset of AI that uses statistical learning algorithms to build smart systems. The ML systems can automatically learn and improve without explicitly being programmed. The recommendation systems on music and video streaming services are examples of ML. Machine learning algorithms are classified into three categories: supervised, unsupervised, and reinforcement learning.

What is Deep Learning?

This subset of AI is a technique that is inspired by the way the human brain filters information. It is associated with learning from examples. DL systems help a computer model to filter the input data through layers to predict and classify information. Deep Learning processes information in the same manner as the human brain. It is used in technologies such as driver-less cars. DL network architectures are classified into Convolutional Neural Networks, Recurrent Neural Networks, and Recursive Neural Networks.

Thus, we understand that AI is an umbrella discipline that covers everything related to making machines smarter. Machine Learning (ML) is commonly used along with AI but it is a subset of AI. ML refers to an AI system that can self-learn based on the algorithm. Deep Learning (DL) is machine learning (ML) applied to large data sets.

How Companies Use Artificial Intelligence In Practice

Machine Learning has proved to be a game-changer for many industries. ML techniques have plunged into almost all major industry verticals. No wonder, Machine Learning with its incredible potential has completely revolutionized the business space.

The machine learning market is expected to grow from USD 1.03 Billion in 2016 to USD 8.81 Billion by 2022, at a Compound Annual Growth Rate (CAGR) of 44.1% during the forecast period, says a report.

Following is the list of some companies that have the power and resources to shape our connected future and are investing heavily in AI.

1. Amazon

Trade giant Amazon has invested in both the consumer-oriented side of AI and in applications for companies and their processes. 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. 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.

2. 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 its 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.

3. 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 another man vs. machine competition, 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.

4. 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.

5. Baidu

The Chinese equivalent of Google, Baidu, uses a tool called Deep Voice that uses artificial intelligence and deep learning that only needs 3.7 seconds of audio to clone a voice. It is a deep neural network that can generate entirely synthetic human voices that are very difficult to distinguish from genuine human speech. The network can “learn” the unique subtleties in the cadence, accent, pronunciation, and pitch to create eerily accurate recreations of speakers’ voices. 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. Yelp

Yelp Is Using Artificial Intelligence to Help You Find Dinner. For an entire generation of diners, taking photos of their food has become second-nature — and thanks to them, Yelp has a gigantic database of photos. While previously the company has relied on users to caption their own photos with “search-friendly metadata,” it’s now armed with software intelligence that can identify information about a restaurant based on photos alone.

7. Starbucks

With more than 90 million transactions a week in 25000 stores globally, Starbucks uses Machine Learning and big data analytics to help direct marketing, business decisions, and sales. By launching its mobile application and reward program they collected and analyzed their customer’s buying habits. The users themselves have created the data by defining where what, and when they buy coffee.

Starbucks gathers this information about their customer’s buying habits. So that even when the customer visits an offline store their system is able to identify their preferences through their smartphone. In addition to this, the app can also suggest new treats that might go with the drinks they ordered.

All this is powered by Starbucks ’ Digital Flywheel Program. It is a cloud-based Artificial Intelligence engine that recommends food and drinks options to customers who are not aware but want to try something new.

The technology is so sophisticated that the recommendations will change according to the weather on that particular day, or if it is a holiday or a weekday, or at what location you are.

Another way Starbucks is utilizing AI is through its Mastrena espresso machines, which the retailer is currently adding across its U.S. fleet with expectations to finish in the next 12 months, as well as internationally.

The machines have Internet of Things sensors built into them, meaning Starbucks gleans telemetry data from them that goes into its support center. “We can see every shot of espresso that’s being pulled and we can see centrally if there is a machine that’s out there that needs tuning or maintenance,” explained Johnson. With Starbucks’ Deep Brew capabilities and predictive analytics, Johnson said the company is “going to be able to determine if a machine needs preventative maintenance on it before it breaks.”

Artificial Intelligence and Machine Learning have become the centerpiece of strategic decision making for organizations. They are disrupting way industries and roles function from sales and marketing to finance and HR, companies are betting on AI and ML to give them a competitive edge. Thousands of vacancies are open as organizations scour the world for AI and ML talents.

Emphasizing enhancement of AI provided to their products and make them the top-notch companies of this generation. The last decade has brought about a huge revolution in the form of Artificial Intelligence (AI) and Machine Learning (ML) cutting across industries. These changes brought an evolution in the overall operating scenario of companies by providing them insights to improve their product and service offerings. It wouldn’t be wrong to say that AI made lives easier through chatbots, algorithms, recommendation engines, hardware infrastructure, language processing and much more.

The AI industry witnessed tremendous growth in 2019. According to the Deloitte report from late last year, 9 out of 10 companies investing in artificial intelligence. Whereas 70% of such companies also accepted to have seen minimal or no impact from their investments in AI. Over the last decade, while organizations actively associated with AI companies, implementation of models has remained a challenge. 2020 will see a visible shift towards intelligent automation changing the face of all major sectors right from the Indian Government to Startups and Small Medium Entrepreneurs.

Artificial intelligence and its applications have made a significant impact on nearly every industry. Defined as a technique enabling machines to mimic human behaviour, brands are using AI to automate processes at an increasing rate. We see this at many points of brand interaction site suggestions on our search engine, lane assistance in passenger vehicles, and app troubleshooting, to name a few.

AI isn’t a new phenomenon. It has been around for almost 50 years, learning constantly, almost on a daily basis. As we evolve and become more efficient, and artificial intelligence learns to better emulate human intelligence, businesses benefit from the increased process and operational efficiencies. As just one example, analysis by PWC predicts that AI could contribute up to $15.7 trillion to the global economy as soon as 2030. Of this, $6.6 trillion will likely come from increased productivity. $9.1 trillion, from consumption side effects.

Machine Learning :

Imagine that you were in charge of building a machine learning prediction system to try and identify images between dogs and cats. As we explained above, the first step would be to gather a large number of labelled images with “dog” for dogs and “cat” for cats. Second, we would train computer to look for patterns on the images to identify dogs and cats, respectively.

Trained machine learning system capable of identifying cats or dogs. Once the machine learning model has been trained, we can throw at it (input) different images to see if it can correctly identify dogs and cats. As seen in the image, a trained machine learning model can (most of the time) correctly identify such queries. for example, the image search and translation tools use sophisticated machine learning. This allows the computer to see, listen and speak in much the same way as humans do. Much wow!

Gmail, Google Search and Google Maps already have machine learning embedded in services. Google is the master of all. It takes advantage of machine learning algorithms and provides customers with a valuable and personalized experience.

Uses and Applications of Artificial Intelligence and ML in Business :

Artificial intelligence has dramatically change business landscape. What started as rule based automation is now capable of mimicking human interaction. It is not just the human-like capabilities that make artificial intelligence unique. An advanced AI algorithm offers far better speed and reliability at a much lower cost as compared to its human counterparts.

Artificial intelligence today is not just a theory. In fact, has many practical applications. Today’s business across the globe are leveraging artificial intelligence to optimize their process and reap higher revenues and profits. We reached out to some industry experts to share their outlook on the applications of artificial intelligence. Here are some insights we received:

1] 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 labelling 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.

2] AI to Improve Workplace Communication :

Current business communication is overloaded with content, channels, tools, and so-called solutions, depriving individuals (and companies) of 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.

3] 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 take away their jobs. From an analytical standpoint, AI can be incorporated into interfaces to change how they receive and understand data.

Chabot’s , in particularly are always on and 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

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] 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 behaviour in such business applications as ERP or Financial systems.

A system of behaviour 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.

6] 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 centres. Autonomous trucks and robotic picking systems allow supply chains to make fulfilment 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.

7] Sports betting Industry :

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 a 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.

How Companies Use Artificial Intelligence In Practice :

All the world’s tech giants from Alibaba to Amazon are in a race to become the world’s leaders in artificial intelligence (AI). These companies are AI trailblazers and embrace AI to provide next-level products and services. Here are best examples of how these companies are using artificial intelligence in practice.

Best Examples Of How Companies Uses Artificial Intelligence In Practice :

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 signalled its commitment to deep learning when it acquired DeepMind. Not only did the system learn how to play 49 different Atari games, but the AlphaGo program was also 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.

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 different languages) that its users publish every second. With use of DeepFace, the social media giant can automatically identify you in a photo that is shared on its 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 another 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.

Conclusion :

By giving such AI and ML practical applications as well as their uses. And also different Examples of highly varied MNC’s , I wanted to showcase the benefits of ML & AI.

There Are Many things about Artificial Intelligence and Machine Learning that i will be discussing in my upcoming article’s .

THANKYOU !