Advancements in technology happen every day. Whether it be a new update to a phone type, or a completely new device, something, in the technological world, is always advancing. The earliest Artificial Intelligence can be traced back to early philosophers in Greece, and their efforts to model human thinking as a system of symbols.
More recently than that, in 1950, a man by the name of Alan Turing wrote a paper suggesting how to use or test a “thinking machine”. He believed that if a machine could carry a conversation by way of a teleprinter, imitating a human with no differences anyone could see or notice, it could be described as thinking. His paper was followed in 1952 by the Hodgkin-Huxley model of the brain as neurons forming an electrical network, with individual neurons firing in on/off pulses. These events helped spark the concept of Artificial Intelligence.
Jonathan Crane is the Chief Compliance Officer of Ipsoft, an American multinational company that primarily focuses on artificial intelligence, cognitive and autonomic solutions for enterprises. IPsoft is a world leader in Enterprise AI. And it also homes Amelia, a cognitive A.I. platform.
Amelia was first released in 2014 and is continuously coming out with updated versions. She is best known for her customer support and helpdesk applications. She has changed the way businesses and customer service interact with their clients by responding as any other human would. This is what Jonathan Crane had to say about the current state of artificial intelligence;
“AI is driving a huge change in the way we can target our marketing and advertising, even for smaller companies. This means that businesses are able to target their ‘spend and increase ROI’ and allow advertising to do what it should, giving people adverts they want to see.” -Jonathan Crane
What Crane is referring to here is Amelia’s use of Big Data. Big Data is extremely large data sets that may be analyzed computationally to reveal patterns, trends, and associations, especially relating to human behavior and interactions. A.I. can be combined with Big Data to handle complex tasks, and process information much faster than any previous system.
Though, the development process of Artificial Intelligence has not been streamlined and efficient. It started as an exciting and imaginative concept in 1956, but funding was cut in the 1970s, after several reports of lacking progress. Efforts in imitating neural networks were experimented with, then dropped. The most impressive and functional units, of that time, were only able to handle simple problems and were described as toys. The researchers had been overly optimistic in establishing these goals for A.I. and made naive assumptions about the problems they would face. When the results never came up, it was no wonder the funding was cut.
The stretch of time between 1974 and 1980 has become known as ‘The First A.I. Winter’. Once the government funding was cut, interest was lost, and research was dropped. It wasn’t until the 1980s that research resumed, with the U.S. and Britain providing funding to compete with Japan’s new “fifth generation” computer project. The First A.I. Winter ended with the introduction of “Expert Systems”, which were developed and quickly adopted by competitive corporations everywhere.
An Expert System was a piece of software programmed using artificial intelligence techniques. Such systems use databases of expert knowledge to offer advice or make decisions in such areas as medical diagnosis and trading on the stock exchange. These simple programs became quite useful and started saving businesses large amounts of money.
In the early 1900s, A.I. research shifted its focus to something called an intelligent agent, which refers to an autonomous entity that acts, directing its activity towards achieving goals upon an environment using observation through sensors and consequent actuators. These intelligent agents could be used for retrieval services, online shopping, and browsing the web. These are sometimes called ‘agents’ or ‘bots’. With the use of Big Data, they evolved into personal digital assistants or virtual assistants.
The A.I. field experienced another major winter from 1987 to 1993. The second A.I. slow down coincided with XCON, which was an Expert System created by the Digital Equipment Corporation in 1980, and other Expert System computers, being seen as slow and clumsy. Desktop computers were also becoming very popular and were replacing the older, bulkier computer banks. Eventually, Expert Systems became too expensive to keep and maintain compared to desktops. They could not ‘learn”, and were difficult to update, so they became obsolete. Desktop computers did not have these problems.
At about the same time, DARPA (Defense Advanced Research Projects Agency) concluded Artificial Intelligence would not be the “next wave” of technological advances, and funds were redirected to projects that looked as if they would provide quicker results.
Currently, giant tech businesses such as Google, Facebook, IBM, and Microsoft are researching a number of artificial projects, including virtual assistants. They are all competing to create assistants such as Cortana from Microsoft, or Apple’s Siri. The goal of A.I. is no longer to create an intelligent machine capable of imitating human conversation. The use of Big Data has allowed Artificial Intelligence to take the next step. Now the goals are software capable of speaking languages, such an English, and act as your own virtual assistant. The assistants represent the future of Artificial Intelligence, and may take physical forms such as laptops, smartphones and may help in business decisions, or even integrated into customer service, and they will answer the phone.
A.I. has since evolved in many ways. In 2019, Sumitomo Artificial Life was created by James Sumitomo, and his partner Wong Huang, and they gained government funding, creating and experimenting with Artificial Intelligence and virtual assistants. With so much already known and a capable crew, in early 2025, Amelia Suzuki created their first Artificial Intelligence Assistant, the Ekko.1. Not only does Ekko use Big Data, but she can also read vital signs, and completely act on her own, no voice command, although it is sometimes needed. Amelia Suzuki worked on this project with her partner, Aki Amida, who sadly went missing near the deadline. Together, not only did they created a highly advanced Artificial Intelligence unit, they created a revolutionary piece of technology. Sumitomo Artificial Life will not stop there, though. Their research is highly valuable and under much protection. But their research could change the way the world works. Ekko.1 was a high success, but most units were recalled, for they came down with a bug in their system. Ekko incorrectly reading some code or data. A new and improved model should be out in six months' time.
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