Today’s tech world is moving crazy for artificial intelligence and is restless to gather AI modalities in some way or another.
AI is emerging as an empire in the prevailing technology but the birth and growth of AI was not a royal journey.
This article covers the roller coaster expedition of artificial intelligence that progressed through a series of hills and valleys of success.
Table of Contents
AI in thoughts…
The idea to build human intelligence or in other words, to mold intelligent machines is several decades old.
This historic venture is evoked by the proposal of the mathematical model for artificial neurons. A highly simplified model of a neuron was presented in the Bulletin of Mathematical Biophysics as a combined effort of a neuroscientist named Warren S. McCulloch and a logician named Walter Pitts in the year 1943.
The manuscript entitled “A logical calculus of the ideas immanent in nervous activity” illustrated the biological model of neurons as a weighted sum of input which is later named the perceptron.
The idea behind artificial intelligence is to mimic the functionality of the brain, wherein the brain is made of neurons.
Thus the idea to develop artificial neurons was a significant step in the journey of AI.
The iconic invention of the perceptron is trailed by the theory of Hebbian Learning which is formulated by Donald Hebb in 1949. The theory relates the physiological and neurological foundations of neurons.
The Turing turn…
The thought process was further taken over by a renowned British mathematician and computer scientist, Alan Turing.
The question was raised about the possibilities of the machines to make decisions and solve problems like the humans do the same from the available information.
His remarkable thought presented in his famous article, “Computing Machinery and Intelligence” in the year 1950, influenced the world to take serious moves on the development of AI.
But some significant consequences stopped him from making further developments on his thoughts.
- The major crisis was that the computers couldn’t store data. Since memory is the key feature to acquire intelligence, this caused a major plight for the development of machine intelligence.
- Another important challenge was the extremely expensive computing facilities which resulted in nearly impossible access for it.
AI into the picture…
The concept of “intelligence in machines” was converted to the revolutionary term “Artificial Intelligence” in the year of 1956 during an academic conference on the campus of Dartmouth College in the project entitled Dartmouth Summer Research Project on Artificial Intelligence (DSRPAI) hosted by John McCarthy and Marvin Minsky.
This program which named Logic Theorist by its creators Allen Newell, Cliff Shaw, and Herbert Simon, is designed to achieve the problem-solving skills of humans.
This happened to be a spark on the enthusiastic minds to canary over the flame of AI into action.
These substantial contributions by McCarthy, Alan Turing, Allen Newell, Herbert A. Simon, and Marvin Minsky made them be honored as the founding fathers of Artificial Intelligence.
The powerful come-back…
The period 1957 to 1974 was a golden age for AI in which various productive experiments were handled with AI and experienced grand success.
This gained significant attention among the arising technologies and was taken over by several groups for further implementations.
When the artificial neurons were arranged to form a network by Frank Rosenblatt which was later named the artificial neural network in 1957, the roots of artificial intelligence have immersed deeper into the minds of future aspirants and expected a massive development.
The major advancements in the utilization of AI were,
- An attempt by MIT in 1965, which is known as DENDRAL, is an intelligent system related to molecular chemistry.
- The first chatbot named ELIZA was launched in 1966 by Joseph Weizenbaum, a German American computer scientist.
- This was followed by the demonstration by Newell and Simon on the achievement of human problem-solving skills by mathematical approaches.
- 1970 witnessed the design of a humanoid robot which is given the name as WABOT – 1. This first anthropomorphic robot is designed in the School of Science & Engineering of Waseda University.
Another expert system with the title MYCIN which was specialized in blood disease diagnosis and prescribing drugs was launched in 1972.
The system could effectively identify infection-causing bacterias and prescribe antibiotics of sufficient dosage.
The haze of the first AI Winter….
The progress rapid evolution of AI underwent a severe decline in its progress during the years 1974 to 1980 which is known as the first AI winter.
The major reason was the lack of sufficient computational power for the growing demand for complicated computations to execute AI programs.
Numerous critics arose against the growth of AI which in turn significantly reduced the government funding and a severe drop in the field of AI was noticed.
The British government later took over the funding responsibility and also provided the facilities required for the research in AI which was actually aimed to beat the Japanese technology. The boost of funds was effectively utilized to enhance the computation facilitates using algorithmic tool kit which happened to be a reignition for AI research.
On the other side, the Japanese government released huge financial support for AI research works in accordance with the Fifth Generation Computer Project (FGCP) which was their unique step towards the growth of expert systems with AI.
Second AI Winter…
The availability of sufficient funds for the research was a major advantage but the challenges persisted for numerous other reasons.
The collapse of the market and the resultant reluctance in government funding lead to another AI winter during the period of 1987 – 1993.
The method of machine reasoning was visible as a “black box” since it was not clearly demonstrated how the reasoning was performed.
Several critics arise due to this lack of justification. Thus the further development and continuity of research became extremely complicated due to the deflated interests.
AI regains strength with Deep Blue…
The series of expert systems finally re-established the strength of AI with the success of the Deep Blue algorithm developed by IBM. The algorithm, which was based on the brute force theory, was designed to evaluate and weigh all the moves in a chess game.
The success of Deep Blue created history by defeating Garry Kasparov. The intelligence of the Russian grandmaster was overcome at the championship of May 1997.
Although it was past 30 years, this was also the victory of Herbert Simon’s 1957 outlook on the reasoning capabilities achieved by the machines.
This remarkable breakthrough generated a strong belief in the progress of artificial intelligence and thus emanated numerous research works and its necessary funding.
Well established and the journey continues….
The 20th century began with the magnificent influence of artificial intelligence. The demand for AI was expected to increase since it started to prove its power in various sectors.
- The first AI-supported home appliance was launched in the year 2002 which was an intelligent vacuum cleaner with the name Roomba.
- With a vision of the power of AI, social media platforms started to embed AI functionalities. AI conquered the business world by 2006 when it was being utilized by renowned companies like Twitter, Netflix, Facebook, etc for to achieve highly efficient recommendations for the customers.
- IBM again created history when IBM’s Watson won Jeopardy, the famous quiz show in 2011 that included the solutions for tricky questions and riddles.
The list goes endless because AI is one of the most utilized technologies of the current world. The transformation from reluctance to extreme demand was due to several essential reasons.
- The availability of a huge amount of data: The extremely improvised storage facilities resulted in the availability and access of massive data volumes. The data is generated every second in different formats. Since it can be collected and stored effectively, it becomes the crucial support for AI systems.
- The availability of highly powered processors for computing: The extensive and complicated set of computations is the major challenge to run an AI program. The launch of high computing powers like GPU and HPC made a clear path to explore the AI world.
The facilities are still developing that makes computations easier and the process simpler. The world has now witnessed the progression of AI from zero states. AI is well established with its powerful results and its journey continues.
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