Benefits Which MNCs Are Getting From AI/ML
Artificial intelligence and machine learning are among the most significant technological developments in recent history. Artificial intelligence is moving forward, and whether we like it or not, machine learning will play an essential role in our technological future. The largest and best companies in the world already know this, and they are investing heavily in AI.
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.
What is Artificial Intelligence(AI)?
AI is a technique that enables machines to mimic human behaviour. Artificial Intelligence is the theory and development of computer systems able to perform tasks normally requiring human intelligence, such as visual perception, speech recognition, decision-making, and translation between languages.
Artificial Intelligence is accomplished by studying how human brain thinks, learns, decide, and work while trying to solve a problem, and then using the outcomes of this study as a basis of developing intelligent software and systems.
What is Machine Learning(ML)?
Machine learning is a subset of Artificial Intelligence (AI) which provides machines the ability to learn automatically by feeding it tons of data & allowing it to improve through experience. Thus, Machine Learning is a practice of getting Machines to solve problems by gaining the ability to think.
Some use case of Artificial Intelligence and ML in Industries
Artificial intelligence in healthcare
AI in healthcare overarching term used to describe the use of machine-learning algorithms and software, or artificial intelligence (AI), to mimic human cognition in the analysis, presentation, and comprehension of complex medical and health care data. Specifically, AI is the ability of computer algorithms to approximate conclusions based solely on input data.
Product Recommendations
Unsupervised learning helps in developing product-based recommendation systems. Most of the e-commerce websites today are making use of machine learning for making product recommendations. Here, the ML algorithms use customer’s purchase history and match it with the large product inventory to identify hidden patterns and group similar products together. These products are then suggested to customers, thereby motivating product purchase.
Artificial intelligence in human resource management
Artificial Intelligence (AI) integration into human resources (HR) practices will make organizations better because these applications can analyze, predict and diagnose to help HR teams make better decisions, according to research from the International Research Journal of Engineering and Technology
Detecting Spam
Machine learning in detecting spam has been in use for quite some time. Previously, email service providers made use of pre-existing, rule-based techniques to filter out spam. However, spam filters are now creating new rules by using neural networks to detect spam and phishing messages.
Image Recognition
Also, known as computer vision, image recognition has the capability to produce numeric and symbolic information from images and other high-dimensional data. It involves data mining, ML, pattern recognition, and database knowledge discovery. ML in image recognition is an important aspect and is used by companies in different industries including healthcare, automobiles, etc.
Microsoft
AI is a term that appears on Microsoft’s vision statement, which illustrates the company’s focus on having smart machine central to everything they do. They are one of the world’s biggest AI as a Service (AIaaS) vendors.
As one of the leading software companies, Microsoft has been building its AI capabilities on different fronts to drive their business. With a variety of AI-based products and services like Cortona, CNTK, cognitive services, and industry-specific AI apps, Microsoft offers developers many interesting and challenging projects in AI.
Microsoft’s Plans for AI
The adoption of AI in business and society is being spurred on by tech giants with resources to design, build and roll out services affordable and simple enough for everyday use. Microsoft is one of those at the forefront. This year, the words “artificial intelligence” appeared in a vision statement for the first time, reaffirming that smart, learning machines are considered central to everything they do.
While it may only just be beginning to shout about it, Microsoft has been building intelligent functionality into many of its products and services for some time. If you regularly use Skype, Office 365, Cortana or Bing, you have probably come across them.
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Machine learning — which is what most people mean at the moment, when they use the term AI — helps to match searches with useful results, and gives the Cortana virtual assistant the ability to improve and become more helpful over time. Through Skype, it enables chatbots to run on its communications platform, where they can be used for customer services or accessing services such as weather or travel information.
Within its Office enterprise productivity suite, as well as assistance from Cortana, Microsoft has been rolling out AI-assisted features designed to offer help with everyday tasks, such as live translation of recorded speech.
These are great examples of how specialized AI — designed to carry out one single task and become increasingly good at it — has already become embedded in our lives. Microsoft however has made it clear that their ambition goes further. It is working towards the goal of generalized AI — intelligent machines which can turn their talents to any task.
Harry Shum, executive vice president of its AI and Research group, has said “Computers today can perform specific tasks very well, but when it comes to general tasks, AI cannot compete with a human child.”
The Research and AI group was founded in 2016 as Microsoft’s fourth engineering division, alongside the Office, Windows and Cloud teams. In under one year it has grown to 8,000 employees. It is safe to say that after losing out on the last seismic change in the technological landscape — the jump to mobile — it does not want to be slow off the starting block again.
The tech giant also has an interest in development of autonomous vehicle technology. This year it announced that it is partnering with the leading Chinese search engine Baidu to develop a platform for self-driving cars. These vehicles will rely heavily on artificial intelligence to interpret data from onboard sensors and react appropriately to driving hazards.
Most recently, Microsoft announced new technology designed to accelerate machine learning algorithms to real time. Known as Project Brainwave, it uses programmable processors known as FPGAs to run the sophisticated and compute-hungry algorithms. Essentially this is software which can be programmed directly onto a programmable chip, enabling commodity hardware to function as specialized deep neural network processing units.Microsoft is positioned to capitalize on this due to the investment it has made in installing FPGAs in its data centers worldwide over recent years.
Microsoft is also developing industry specific AI applications. The company has just announced a new healthcare division based on artificial intelligence with the aim of developing predictive analytic tools that can alert people about medical problems, help diagnose diseases, and recommend the right treatments and interventions.
Put together, these projects represent the culmination of an aim first stated by the company’s most famous figurehead, founder Bill Gates, back in 1991, when he said that he believed computers would one day see, hear and learn just as humans do.
Today, the level of available computing power has reached a threshold where intelligent, self-teaching machines are starting to become a viable reality. If we imagine the task of creating AI as if we were Dr Frankenstein in his laboratory, then our creation may not yet be on its feet and walking about, but it has opened its eyes, and we can see that the lights are on.
