AI is a term that is thrown about frequently these days and tends to conjure images of talking robots and eerily intelligent machines. But what is AI exactly and how can it benefit us?
The term ‘Artificial Intelligence’ was coined by John McCarthy in 1956. McCarthy defined AI as ‘the science and engineering of making intelligent machines.’ In other words, AI refers to machines that mimic human intelligence, and are programmed with capabilities to recognise speech, problem-solve, learn and plan.
Machine learning (ML) is an application of artificial intelligence (AI). Artificial Intelligence covers a broader concept of machines being able to perform various ‘intelligent’ tasks. Machine Learning however, is an application of AI that gives machines access to data, allowing them to focus on a more specific task – learning for themselves to perform other functions.
Arthur Samuel introduced the term “Machine Learning” in 1952. He designed a programme that recorded all the positions that had been played in a checkers game up to a point. The programme then proceeded to predict the chances of each side winning, before the end of the game.
Today, ML has evolved. It provides web and mobile applications with the ability to learn automatically and improve from experience, without the need for specific programming. ML processes huge volumes of data and recognises data trends, in order to make decisions and execute necessary actions.
AI is a term that is thrown about frequently these days and tends to conjure images of talking robots and eerily intelligent machines. But what is AI exactly and how can it benefit us?
The term ‘Artificial Intelligence’ was coined by John McCarthy in 1956. McCarthy defined AI as ‘the science and engineering of making intelligent machines.’ In other words, AI refers to machines that mimic human intelligence, and are programmed with capabilities to recognise speech, problem-solve, learn and plan.
Machine learning (ML) is an application of artificial intelligence (AI). Artificial Intelligence covers a broader concept of machines being able to perform various ‘intelligent’ tasks. Machine Learning however, is an application of AI that gives machines access to data, allowing them to focus on a more specific task – learning for themselves to perform other functions.
Arthur Samuel introduced the term “Machine Learning” in 1952. He designed a programme that recorded all the positions that had been played in a checkers game up to a point. The programme then proceeded to predict the chances of each side winning, before the end of the game.
Today, ML has evolved. It provides web and mobile applications with the ability to learn automatically and improve from experience, without the need for specific programming. ML processes huge volumes of data and recognises data trends, in order to make decisions and execute necessary actions.
Artificial Intelligence and its extension – Machine Learning, is being increasingly adopted across various sectors such as:
Artificial Intelligence and its extension – Machine Learning, is being increasingly adopted across various sectors such as:
• Processes and analyses vast amounts of data
ML enables quick and efficient processing of large amounts of data that is beyond any human capability. This in turn improves productivity
• Improves productivity
Labour productivity is anticipated to rise by 40% in 2035, due to the incorporation of machine learning in technology
• Better matching of needs vs products
Using ML and big data, recommendation systems process information on customer preferences and buyer behaviour, to make suggestions of products or services consumers are more likely to purchase
• Improves customer satisfaction
Big data, AI and ML technologies have contributed to the rise of chatbots. These automated programmes simulate human conversation. They provide responses to queries in bulk, with access to customer service support on demand
• Increases sales
Studies reveal, 1 in 2 customers are more likely to make a purchase when machine learning is present. This is due to the better matching capabilities to a customer’s preferred products and services, and the enhanced customer experience overall
• Processes and analyses vast amounts of data
ML enables quick and efficient processing of large amounts of data that is beyond any human capability. This in turn improves productivity
• Improves productivity
Labour productivity is anticipated to rise by 40% in 2035, due to the incorporation of machine learning in technology
• Better matching of needs vs products
Using ML and big data, recommendation systems process information on customer preferences and buyer behaviour, to make suggestions of products or services consumers are more likely to purchase
• Improves customer satisfaction
Big data, AI and ML technologies have contributed to the rise of chatbots. These automated programmes simulate human conversation. They provide responses to queries in bulk, with access to customer service support on demand
• Increases sales
Studies reveal, 1 in 2 customers are more likely to make a purchase when machine learning is present. This is due to the better matching capabilities to a customer’s preferred products and services, and the enhanced customer experience overall
At Caspian Digital Solutions, we harness Artificial Intelligence and Machine Learning capabilities across various fields. With its ability to learn, reason, and self-correct, we have empowered our clients in different fields through our cutting-edge custom-made solutions.
At Caspian Digital Solutions, we harness Artificial Intelligence and Machine Learning capabilities across various fields. With its ability to learn, reason, and self-correct, we have empowered our clients in different fields through our cutting-edge custom-made solutions.
