In recent days, Machine Learning (ML) has become a buzz word in the financial industry. As mentioned in the previous post, banks in the US have spent around US$17 billion in big data and business analytics solutions where ML is one of the key technologies being used. Artificial Intelligence (AI) is also a related technology that’s gaining traction in the market. But, people often think that both are the same or can be used interchangeably.
“The science and engineering of making intelligent machines,” defines John McCarthy, who coined the term Artificial Intelligence (AI). In simple words, AI is the capability of a machine to imitate intelligent human behavior. AI is a broader concept of advanced computer intelligence on par with the smartest human minds ever.
The Google’s self-driving car, IBM Watson that won the Jeopardy and IBM Deep Blue chess machine which defeated the world champion Garry Kasparov are a few known examples of an AI system. Some of the AI systems are rule-based while the others are learning based. An ideal AI system must pass the Turing Test. The Turing test is a test, developed by Alan Turing in 1950, of a machine’s ability to exhibit intelligent behavior equivalent to, or indistinguishable from, that of a human. An ideal AI system must possess the following in order to pass the Turing test.
- Natural Language Processing to enable it to communicate successfully in English (or some other human language).
- Knowledge representation to store information provided before or during the interrogation.
- Automated reasoning to use the stored information to answer questions and to draw new conclusions.
- Machine learning to adapt to new circumstances and to detect and extrapolate patterns.
A recent research found that the smartest AI System available today is only as intelligent as a four-year-old kid. So, there is a lot to look forward to in this space.
“It is a type of AI that provides computers with the ability to learn without being explicitly programmed,” defines Arthur Lee Samuel who coined the term Machine Learning (MI). It’s a core subset of AI that enables a system to learn and recognize patterns to make predictions. ML algorithms are designed not only to make predictions on the existing data, but also to continuously learn to optimize the output.
ML techniques are widely used in Image recognition engines, Natural Language Processing (NLP), Fraud detection, Translation and Financial market analysis. Deep Learning is an advanced ML technique that’s gaining traction. It uses Neural Networks (NN) that simulate data storage, processing and decision making similar to that of humans.
The implementation of the above technologies has transformed many businesses, particularly in the financial sector. Being a thought leader in the financial technology space, Market Simplified has applied these technologies to its Intelligent Virtual Assistant solutions.
About Market Simplified: Market Simplified is a thought leader in revolutionizing and digitizing products for financial institutions by continuously innovating and simplifying finance. We empower our customers with cutting edge digital experience that is highly personalized and enhanced for the end users with our ‘Experience Engineering’ platform driven by Analytics, AI, Machine Learning and Blockchain technologies. Our clientele includes industry leaders like OptionsXpress (Charles Schwab), Currenex (State Street), MB Trading, Maybank Kim Eng, Kotak Mahindra Bank, National Stock Exchange of India and many others across the globe.
About The Author: Gokoulane Ravi is a foodie, technology enthusiast, and a developer turned marketer with more than 5 years of experience in the space of mobility. When he is not working, he likes to read, write, run and cycle.