What can be the motivation for granting intelligence to machines? Of course, lazy life and moreefficiency in day-to-day tasks. Regardless of ethical obligations from fellow beings, we aresuccessfully outsourcing the tasks we are not interested in, to AI. And success is not one-sided.The outcome is also remarkable. AI is changing life on earth completely and propelling thesame towards a more efficient future. But what we see today is a result of years of research,investigations, and failed experiments.
At the 1956 Dartmouth conference, John McCarthy coined the term artificial intelligence and changed the way we looked at machine intelligence. Intelligent machines back in those days were room sized and extremely slow by all means. Making a code was an arduous and time-consuming process and running the same was even more lengthy. And thus, the most intelligent machines were also pretty limited in all aspects.
The story of Alan Turing
Alan Turing was a pioneer in the field of hypothetical computation and is known for his invention of the hypothetical computer. The Turing machine. The computer in this case is an infinite string of 0s and 1s with program instructions for each value. And an editing component that detects 0s and 1s and follows the embedded program instructions. This string of tape is as long as it needs to be, thus hypothetically a string of infinite length. And the perception and editing components can keep on working until the result is obtained. This hypothetical machine is the foundation of modern computation. And computers or intelligent machines seem to follow the Turing model. And due to the infinite capabilities of this hypothetical computer, it is considered the pinnacle of computation. Something still out of reach of modern machines.
But how do communicate with these machines? How to build a program book that is actually comprehensible? In order to understand the same, we must pay a deeper look at the LISP language family.
The story of List processor (LISP)
In the 1950s leading scientists all across the world came together and developed the first ever machine language. Simply known as information processing language or IPL. the language was developed for a room-sized computer called Johniac. And with the implementation of the same list-based processing emerged as a concept. And after that one invention after the other shook the world and revolutionized the way we approached machines. LISP or list processor was one such language, developed by the father of AI john McCarthy himself. That too, for artificial intelligence research. The revolutionary language was first introduced in the article titled, “Recursive functions of symbolic expressions and their computation by machines pt-1”. Published by Mccarthy and his team after a few years of hardships in MIT. and with that publication, artificial intelligence got its much-needed foundation and started emerging as an independent discipline. Now it was possible to communicate with machines and train them conveniently.
AI in our times
The story of Alan Turing or john Mccarthy is undoubtedly inspiring. But what humanity is achieving today with AI is also a worthy tribute to their effort.
- In the healthcare sector, AI is being used for the analysis of gargantuan amounts of medico historical data, for the development of personalized medicine.
- Well-trained AI entities are being placed at the helm of remote diagnostic systems and helping patients at risk of rapid onset diseases. And allowing them to live a carefree life.
- Computer vision and deep learning tools are being used for histo-metabolic diagnosis.
- AI entities armed with cutting-edge sensors and monitoring systems are being deployed for swift prosecution of rogue vehicles and drivers.
- By automated analysis of natural calamity data, an Ai can generate an alarm before the onset of a calamity. Saving valuable lives and property in the process.
- Mundane but important back-office tasks are being increasingly outsourced with the help of automation. The result is more efficiency and less human error with a promise of more value to human labor.
- Huge amounts of data and AI-enabled engagement tools are in heavy use in marketing.
- In the case of business discretization and forecasting, automated data analytics is the only paradigm for safer predictions.
- Mundane troubleshooting and customer support in our times do not require a lot of human involvement. Automated tools are being deployed in the field with a high degree of success and the dependency is expected to go up with time.