What is AI?

Artificial Intelligence(AI) is everywhere around us, say voice recognition software in your mobile phone or navigations in car. Even Google uses Artificial Intelligence for its search engine. Netflix, amazon prime movie suggestions are based on Artificial Intelligence. Interacting with Siri, Alexa, Google assistant is also a form of Artificial Intelligence.

Artificial Intelligence is a broad area of Computer Science, it makes machines seem like they have human Intelligence. Artificial Intelligence is not just about Programming a computer to obey rules to drive a car. But an Artificial Intelligence should function in a much more effective manner and be independent like a human to a certain extent to make decisions.

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Artificial Intelligence has followed a classic boom and burst cycle in the timeline. There are two types of Artificial Intelligence –

  • Weak AI
  • Strong AI
Weak AI Strong AI
Narrow application, scope is very limited Widely applied, scope is vast
Good at specific tasks Incredible human- level intelligence
Uses supervised and unsupervised learning. Uses clustering and association to process data.
Eg. Siri, Alexa Ex. Robotics, Automation.

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Reasons why AI became Important?

The major reasons why AI became important are the data generation in enormous amount everyday, improvements in processing speed and interpretation speed of computer systems.

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Growth of AI :

Ever wondered how AI is so popular and the growth is exponentially increasing. The major reason for these include-

  • Decreasing cost of computational powers
  • Availability of Data
  • Better Algorithms

Artificial neural network is an attempt to model the network of cells of human brain on a computer. It is like an interconnected web artificial neurons. If you have any query related to Artificial neural network, kindly refer our AI and Deep Learning Community.

History of AI

Let’s the History of Artificial Intelligence in deep:-

Year Milestone
1950 Alan Turing introduced the “Turing Test” for machine intelligence.
1951 The first neural network, SNARC, is created.
1956 John McCarthy organized the Dartmouth Conference, marking the birth of AI as a field.
1957 Frank Rosenblatt invented the Perceptron, a type of neural network.
1959 Allen Newell and Herbert Simon developed the Logic Theorist, the first AI program.
1964 ELIZA, a natural language processing program, is created by Joseph Weizenbaum.
1966 Shakey the Robot, the first mobile robot, is developed at Stanford Research Institute.
1969 The first AI laboratory was established at Stanford University.
1973 The MYCIN system, an expert system for diagnosing bacterial infections, is developed.
1980s Expert systems have gained popularity in various industries.
1985 Terry Winograd developed SHRDLU, a natural language understanding program.
1997 Deep Blue, a chess-playing computer, defeats World Champion Garry Kasparov.
2002 Roomba, an autonomous vacuum cleaner, is introduced.
2011 IBM’s Watson wins Jeopardy! against human champions.
2012 AlexNet, a deep convolutional neural network, wins the ImageNet competition.
2014 Google acquires DeepMind, a leading AI research company.
2016 AlphaGo, developed by DeepMind, defeats world champion Lee Sedol in Go.
2018 OpenAI releases GPT-2, a large-scale language model.
2020 GPT-3, with 175 billion parameters, is released by OpenAI.
Present AI continues to advance in various fields including healthcare, finance, and robotics.

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Goals of AI

These are the Goals of AI:

  1. Automation and Complex Problem Solving: AI strives to create systems that can automate tasks and tackle intricate problems, mimicking human intelligence.
  2. Comprehension and Processing of Natural Language: The objective is to enable machines to grasp, interpret, and generate human language in a contextually appropriate manner.
  3. Adaptation and Learning from Data: AI seeks to build systems that can learn from experiences and data, adjusting their responses and behavior accordingly.
  4. Interpretation of Visual Data and Pattern Recognition: AI aims to empower machines to make sense of visual information, similar to how humans process images and videos.
  5. Independent Decision-Making with Data-Driven Insights: The goal is to develop systems capable of making informed decisions autonomously, often relying on data, algorithms, and predefined criteria.
  6. Facilitating Seamless Interaction Between Humans and Machines: AI endeavors to create interfaces and systems that enhance communication and collaboration between humans and machines.
  7. Ethical and Responsible AI: There is an increasing focus on ensuring that AI systems operate ethically, transparently, and without bias, while respecting privacy and societal values.
  8. Robotics and Interaction with the Physical World: AI in robotics aims to create machines capable of interacting with the physical environment, performing tasks, and navigating autonomously.
  9. Achieving Artificial General Intelligence (AGI): The ultimate aspiration is to attain a level of machine intelligence comparable to human beings, capable of learning and performing a wide range of intellectual tasks.
  10. Continuous Innovation and Advancement in AI Research: The field is dedicated to pushing the boundaries, seeking new algorithms, and adopting advanced methodologies to expand the capabilities and applications of AI.

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Career Transition

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Application Areas of AI:

Following are the applications of AI used in various field

  • Banking to organize operations, invest in stocks, and manage properties.
  • Augmented reality, Robotics
  • Image, Speech recognition
  • Fraud detection
  • Emotional recognition
  • Security/Authentication

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