The emerging technologies we are surrounded by today viz. Internet of things (IoT), Data Science, Big Data, Cloud Computing, Artificial Intelligence (AI), and Blockchain are creating major shifts in the world we currently operate in.
They have already changed the way we live, work and amuse ourselves. And it is not hard to predict that further advancement in these technologies will result in us developing hyper automation and hyper connectivity, catapulting us entirely into the Fourth Industrial Revolution or Industry 4.0, leaving this world behind.
Majorly, the advancement in Artificial Intelligence lies at the heart of the enhanced performance of all the other technologies and the evolution of Industry 4.0. This would mean facilitating human-to-machine interactions, changing the logic of business models, and transforming the lifestyle and living standards of the human culture.
The commercial adoption of AI has brought about a change that is making the world smarter and more innovative. Be it route and traffic mapping by Google maps, price estimation of rides by Uber and Lyft, friends’ tag suggestions at Facebook, spam filters in our email, recommendation for online shopping and cancer detection are only a few examples of AI technological innovations simplifying our day-to-day lives.
AI is moving at an incredible pace and with every sector that it is entering, it is forcing companies to get into the race to make their company an AI company. With this, business, strategists, pioneers, entrepreneurs and investigators are compelled to use AI to design new strategies and create new sources of business value.
Quoting Andrew Ng, co-founder Google Brain; former vice president & chief scientist of Baidu; co-chairman and co-founder of Coursera and an adjunct professor at Stanford University said in 2017 at Stanford MSx (Master of Science in Management for Experienced Leaders) Program (Lynch 2017)-
“Just as electricity transformed almost everything 100 years ago, today I actually have a hard time thinking of an industry that I don’t think AI will transform in the next several years.”
Let’s pay attention to something so closely related to AI like electrons are related to atoms:
Alan Turing (1912–1954) understood the concept of computers as none other. As early as the 1940s he was able to establish that there would be endless debate about the difference between artificial intelligence and original intelligence in the future when computers would become smarter.
According to him, asking whether a machine could think was the wrong question. The right question is: “Can machines do what we — as thinking and rationalizing entities can do?” And if the answer is yes, isn’t the distinction between artificial and original intelligence essentially meaningless? Doesn’t it become a moot point?
In order to drive the point home, he devised a version of what we today call the ‘Turing Test.’ In this test a jury asks questions of a computer. The role of the computer is to make a significant proportion of the jury believe, through its answers to the questions, that it is actually a human.
Throwing some more light on the Turing’s logic, what effectively is the actual difference between an AI being able to counterfeit a Rembrandt painting and it being a painter? Or being able to compose a “new” Vivaldi symphony and it being a composer?
Imagine if an AI can pretend at this level all the time, under any given circumstances, no matter how deeply it is probed, then maybe it actually is an artist, or a composer, or whatever else it has been taught to be.
What would Alan Turing say in this case?
- It will be astounding to know that AI autopilots in commercial airlines dates as far back as 1914, definitely pertaining to how loosely one defines the term autopilot. According to an article from The New York Times, the average flight of a Boeing plane involves only seven minutes of human-steered flight and that typically involves takeoff and landing.
- Jeff Schneider is the engineering lead for Uber ATC. In an NPR interview he had described how the company uses Machine Learning in order to predict rider demand to ensure that “surge pricing” or the short periods of sharp price increases to decrease rider demand and increase driver supply, will soon no longer be necessary. Danny Lange, Uber’s head of Machine Learning had confirmed Uber’s use of machine learning for ETAs for rides, estimated meal delivery times on UberEATS, computing optimal pickup locations, as well as for fraud detection.
- A company called Blue River Technology has developed a robot called See & Spray that uses computer vision technologies like object detection to monitor and precisely spray herbicide on cotton plants. This type of precision spraying can help prevent herbicide resistance.
- A Berlin-based agricultural tech start-up called PEAT, has developed an AI application called Plantix that identifies potential defects and nutrient deficiencies in soil through images.
- In this technique, the image recognition app can identify possible defects through images captured by the user’s smartphone camera. Users are then provided with soil restoration techniques, tips and other possible solutions.
This is not the end, in fact this is not even the beginning. These applications are just like scratching the surface, apart from them, there are many others like AI-powered robots capable of thinking and solving problems in a limited capacity, increasingly adopted AI-powered marketing tools that can help marketers generate in-depth customer insights reports, book more impactful business meetings, and create pertinent content, among others. And all these are being done with minimal human intervention.
Artificial Intelligence is deeply impacting human lives through a diverse range of applications. The choices we make are getting influenced by it to a good extent. Companies have started including Artificial Intelligence consulting in their budget in order to not miss out on this massive opportunity.