Any thing in the world have it’s own present, past and future. I discuss here the detailed history of AI in this post. And also a brief knowledge of recent decade.
Artificial intelligence timeline
Ancient hisory of AI to Pre-Modern (Pre 1900)
- 700 BC – Greek myth of Talos, a four-hundred foot tall, bronze automaton.
- 100 BC Hero of Alexandria invents ealier mechanical devices.
1206 Al-Jazari (Islamic) invents the programmable automata.
1642 Blaise Pascal inventions mechanical calculator
1830s The Analytical Engine is designed by Charles Babage, and the scheming of Ada Lovelace theorizes about thinking machines.
Precursors of Computation (1900s -1940s)
1936 – Alan Turing publishes On Computable Numbers, the roots of computer science.
1943 – McCulloch and Pitts- develop a note-worthy mathematical model of any-neural networks.
1949 Donald Hebb offers Hebbian learning: Neurons that fire together wire together.
Birth AI (1950s)
1950 Alan Turing suggests the Turing Test
1951 Minsky constructs the SNARC (first machine artificial neural network).
1955 -Newell and Simon develop Logic Theorist (earliest AI program).
1956 -Dartmouth Conference John McCarthy invents the title Artificial Intelligence.
1958 Frank Rosenblatt invents the Perceptron (early neural net).
Growth and First Boom (1960s -1970s)
1966 Joseph Weizenbaum invents ELIZA, an early chatbot.
1969 -Marvin Minsky and Seymour Papert publish Perceptrons, which is critical of neural nets (stalling research).
1972 – Shakey the Robot: first mobile robot with reason.
The 1970s – The era of Expert Systems (e.g. MYCIN in medicine).
The first AI Winter (1974-1980)
Funding declines because there are no practical finding.
Research on AI decelerates tremendously
Revival & AI Robotics years (1980s)
1980 – boom in business of Expert Systems.
1986 Elaboration of the backpropagation algorithm revives the subject of neural networks (Rumelhart, Hinton, Williams).
Efforts to develop expert systems were marked by a second AI Winter (1987-1993): Expert systems were proving expensive and pedestrian.
The 1990s through the 2000s can be considered the modern era of AI foundations.
1997- Garry Kasparov was defeated in chess by IBM computer Deep Blue.
2002- Vacuum robot (Consumers AI) (Roomba).
2006 -Geoffrey Hinton coins the term Deep Learning and revives the neural networks.
The 2010s Breakthroughs (2010s)
2011 – Jeopardy! Watson Champion
2012 – AlexNet accepts the ImageNet contest and transforms computer vision through the usage deep learning.
2014 Chatbot Eugene Goostman is said to pass the Turing Test.
2016 DeepMind achieves an AlphaGo win against Go world champion Lee Sedol.
2018 – Google introduces BERT and improves the field of NLP.
Exosplosion (2020s)
2020 – with GPT-3, OpenAI impresses with text output that seems just human.
2022 ChatGPT was released, becoming an instant hit with millions of users.
2022 The generative AI art comes with DALL-E 2, Stable Diffusion, MidJourney.
2023 Trending Plans New release GPT-4 by OpenAI with superior reasoning.
2024-2025 – AI is extended into coding (Copilot), medicine, self-driving cars and personal assistants.
Research is being carried on toward Artificial General Intelligence (AGI).
Major areas of interest: ethics and regulation, alignment to human values, responsible AI.
Benefit to the World AI
Efficiency & Automation
Automates redundant and time-consuming processes and saves time and human error.
In sectors such as manufacturing, healthcare and finance, AI increases productivity.
Healthcare Advancements
AI can be used in the prognosis of the disease and as a personalized medication as well as in drug discovery.
Robots help in very precise surgical procedures as a result of AI.
Education & Accessibility
Personalized learning is achieved when students use AI tutors and learning apps.
Assists the disabled (e.g., speech to text text the deaf, AI vision aids to the blind).
Safety and Q. Health Risk Reduction
Machines equipped with AI can be used on risky tasks (e.g., bomb detection, work with space, mining).
Makes the use of roads safer by applying autonomous driving and road management systems.
Business & Economy
Fills decisions with the data driven knowledge.
Offers virtual assistant and chatbots to customers.
Creates the new market and opportunity both in AI-driven industries.
Environmental Benefits
It will also conserve energy, forecast natural catastrophes and support climate studies.
Enables precision farming.
Drawbacks of AI
Job Displacement
In transport, retail and manufacturing, automation can take away millions of people at work.
Employees cannot always cope without retraining.
Bias & Discrimination
Because of the biases that are inherent in training data, IA can be discriminatory in decision making (e.g. hiring, policing and lending).
Privacy Concerns
Personal privacy can be divided as a violation through AI-driven surveillance, facial recognition, and collection of personal data.
Dependencies and I weakness of human abilities
Oversame investment in AI can decrease the level of human creativity, critical thinking, and problem-solving abilities.
Security Threats
Its misuse is possible to attack the cyber world, create fake news, and fake people.
It is ethically and safety dangerous that autonomous weapons can be unsafe.
Ethical/ Moral Dilemmas
There are questions concerning accountability, Q Who will be held responsible in the event that an AI system is harmful?
Ethical challenges with AI creating life-changing bills (e.g. in medical care, the courts, the armed forces).
Expensive and QVIGDIvent
Creating sophisticated AI is costly, which prefers the rich countries and corporations.
May increase the gap between the rich and the poor nations.
Conclusion-
While there are dangers such as inequality, unemployment and ethical concerns in this emerging technology, there is also a lot of potential to redefine industries, to make the world a better place and to help us solve world problems. The key is stable development and regulation, as well as human control with the idea to derive maximum of its benefits and to diminish its harms.
The history of Artificial Intelligence is a walk through fantasy to practice. The concept of mechanical people and a utopian dream of logic started as mythologies; today it has become one of the most most life changing technology to date. Expounding upon the early principles of Turing, the explosion of perceptrons and all the way to current AI winter and optimism the world of AI has become a part of our current world.
Today, machines can calculate and reason but they also create, converse, and collaborate due to the advancements in deep learning, natural language processing, and generative AI. However, with these amazing feats there are critical issues of morality, equity and accountability.
The history of AI is not over yet, however. How the human race leads its development of this technology will determine whether it will become a tool of empowerment or a difficult and uncontrollable aspect with which to deal. It is not only the story about the machine being able to learn; it is the story about us and our learning how to live with the intelligence we have created.
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