You will agree with the fact that the present generation is witnessing a rush of technological innovations. All in an attempt to create new and profitable business models, entrepreneurs and technologists are keeping their eyes and ears open to latest technological advancements that can simplify their lives in more ways than one.
One such technological revolution comes with Artificial Intelligence (AI) tagged with specific emphasis on Machine Learning (ML). ML makes it possible for machines to improve their performance without the intervention of humans to explain how all the pre-defined tasks can be completed. This revolution which is being witnessed since the onset of 2017 has paved the way for building systems that independently learn how to perform tasks without any sort of manual interference.
What is the Big Deal with AI?
The business of AI is unique for two important reasons. Firstly, we as human beings are much more informed about things than we can actually explain in clear terms. We struggle to explain how we do certain things. Before the invention of ML, the hands of humans were tied with this inability of expressing knowledge that was assimilated by them. This made the process of automating many processes a far-off dream. Now with ML, we are on the path of progress to not only express our knowledge but also automate many tasks, effortlessly.
Secondly, you should appreciate the fact that ML systems are excellent learners. ML can be used to derive phenomenal performance in multiple spheres. ML can be employed in medicine to diagnose a disease or to detect a fraud by examining a single stroke of the signature. The present generation is thus making the most of this ML technology and is deploying it across multiple spheres which will register an exponential impact on global businesses.
What Are All the Businesses That Will Benefit from AI?
AI is looked upon as the top bet to experience a superhuman impact in general purpose technologies. Some of the general purpose technologies are the earliest innovations like the electricity and the steam engine. Once electricity came into vogue, it paved the way for a host of complementary innovations, providing ample opportunities to set up new business models.
Tag these advancements with AI and you will find that most of the worldwide companies have already incorporated AI into their businesses. However, there is so much out there when it comes to AI that its entire potential is waiting to be tapped. With AI gaining ground, you will be able to register a phenomenal growth in practically every sphere of human intervention.
You can see AI making its strong presence felt with disciplines like healthcare, finance, transportation, manufacturing and retailing; naming only a few. The good news is that ML can be employed to all these activities. Now comes the not-so good news. And that is, the challenge to manage, implement and set the right stage for ML-centric business imagination.
Global Companies Leading the AI Race
As per the latest MIT Technology Review of 2017 [1], China and the United States are the countries that are delving deep into the research of AI, followed by England and Australia. Tagged as the Big Three, Microsoft, IBM and Google are the leading companies that are making headway in matters concerning AI. While Microsoft focused on publishing AI research papers to the global technology fraternity, IBM and Google employed these learnings to gain a strong foothold in the AI space.
Examples That Establish the Strength of AI
AI, since its inception, has been making waves in the technological spheres. Improving various processes at a rapid pace, the most promising sections of AI can be categorized into 2 broad sections;
- Perception
- Cognition.
Perception – The Top Most Important Advancement of AI
Speaking of perception, you can see the evident advancement coming in the direction of speech recognition. Siri and Google Assistant are prominent examples that have made it possible for machines like smartphones to recognize human voices. Now is the age when computers take dictations from humans and come up with accurate documents that are delivered faster than your personal assistant using her desktop to type your documents.
Image recognition is another section under perception. Mobile apps and Facebook are now able to recognize the faces of your contacts in the posted photographs. All thanks to the image recognition ability of AI that these apps can prompt you to tag them with their respective names. With image recognition powered by AI gaining ground, organizations are bidding a goodbye to ID cards.
Performance Metrics of AI Speak Volumes
Research conducted by AI scientists demonstrated results in favor of speech recognition. You will be thrilled to learn that AI through its speech recognition abilities has tripled the speed of processing contrasted by the average time taken to type on a smartphone. It is not only about enhancing the speed of processing, you will also be concerned about experiencing error-free results. AI paved the way for a phenomenal drop in error rate from 8.5% to 4.9% in 2016.
Cognition – The Second Major AI Improvement
Cognition is the ability to understand with a sense of reasoning. AI’s second important advancement is linked to the ability to logically understand a particular scenario. Helping you come up with problem-solving alternatives, it is through AI that the DeepMind team at Google was able to cool its data centers by more than 15%, despite being optimized by human data center specialists and administrators. Another notable contribution of AI in the area of cognition is linked to detecting malware that causes money laundering on online payment gateways.
The list of cognitive functions of AI does not end here. AI through ML is finding its place in many companies which are prompted to invest in certain shares listed on Wall Street. Investors are able to make rightful credit decisions and earning monies by trading in the stock market by employing the concepts of AI.
The Magic of Machine Learning Technology
You should keep in mind that ML offers a completely different approach to creating software applications. Machines are not programmed to come up with a pre-defined result. On the contrary, examples and instances are the tools that help machines learn. This is a significant development that is going against the practices of the past.
If you look at all the technological innovations that emerged since the last 50 years, you would appreciate the fact that software developers used to develop a code by applying their subject learnings. They would then embed the code into a machine for the code to generate a result that is desired by the clients of the software company. That means coding is a practice that allows the transference of the knowledge of the developer into a form that a machine can understand and eventually execute it. This process of coding is flawed since you as developers will not be in a position to completely explain your code. This weakness boils down to the fact that we as humans cannot explain all that we know and do.
All the above drawbacks of coding can be effectively resolved through ML when the present generation will wake up to the second phase of the machine age. This will be an age that will be dominated by machines built by humans. But the striking part would be that these machines will learn from examples and follow a pattern of feedback so that they will not require the intervention of human experts in solving their problems.
The Long List of ML Flavors
It is an interesting piece of trivia to note that ML and AI come in different flavors. However, AI is registering success with one major category, and that is: Supervised Learning Systems. So true to its name, these systems comprise of machines that work around a set of examples of a solution to a problem. Involving a mapping procedure, these machines map a set of X inputs to a set of Y outputs.
Imagine the set of X to be the pictures of various flowers and the Y set has the labels of flowers like rose, jasmine, marigold and chrysanthemum. Machines that employ ML will be able to match the images of flowers with their corresponding names. If the machines are trained to look at all such examples that are labeled with the right answer, there is a great chance for them to predict answers with a commendable rate of accuracy; thrilling human experts.
Conclusion
With so much going in favor of AI and ML, the AI-based systems will move ahead with superior performance levels when compared to those systems that are linked to human intervention. And once this scenario emerges, AI will spread its wings into all the spheres of human life at a rapid pace.
