Ai history in legal advice -ai history filter -Foundational Concepts of AI

Ai History development and foundation = areas of ai

 

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ai history filter

 

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 ai history filter part history

  • 1941 =the initial computer ,even to run a singer program, they need to do many connection s it is used to be a complex task to do
  • 1943 = first work recognize by warren mccullon
  •  r watter pits proposed a model of ai neurons
  • 1949 = Donald hebb = update s modify connection strength b/w neurons called Hebbian learnine
  • 1950 = Alan Turing Proposed atest. “Computing Machinery Intelligence Test tocheck machine ability by human Intelligence.
  • 1956 =Birth of AI- Darth Mouth Conference adop the word Artificial Intelligence by american Scientist. (John McCoring)
  • (till now the High level language – FORTAN, LISPEY (BOL)
  • 1966 Joseph Weizen baum first chat box- ELIZA (researchers developing algo, which can solve mathematical Problem)
  • 1972 =first inteligent humanoid robot – WABOT-1 made in Japan
  • (1974-1930) AI Winer
  • 1980 = AI come back with expert system, they programmed with decision making abilities are
  • (1987-1993) =second ai winer ( hight cost result   expert system like x com very costly )
  • 1997 = IBM deep blue best would chess champion (Gary Kasparov)
  • 2002 = AI entered in the home in form of Roomba, a vacuum cleaner.
  • 2006 = AI in business world, testing AI.,Company like FB, twitter,et
  • 2011 = IBM watson won jeopardy (a quiz show), it can Solve complex question I riddles.
  • 2012 = Google launch Android app – ‘Google Now – provide info to user as a prediction. Provide
  • 2014 = Chatbox “Eugene Goostman” won a competition in the famous turing test.
  • 2016 = Foundation AI was founded in 2016 by a team of researchers from Google, OpenAI, and other leading AI companies. The lab is funded by a consortium of technology companies, including Google, Microsoft, and Amazon.
  • AI developed high level deep learning, big data data science tren like boom, company like PB, Amazon, 18M create amazing devices Google
ai history filter
ai history filter

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artificial intelligence (AI):

 

History of AI:

1. Early Concepts (Antiquity to 20th Century):

  • The concept of artificial beings with human-like intelligence dates back to ancient civilizations, but it gained more formal attention in the 20th century.

2. Birth of Computer Science (1930s – 1940s):

  • The development of computers and digital technology provided a foundation for AI. Pioneers like Alan Turing and John von Neumann contributed to early AI theory.

3. Dartmouth Workshop (1956):

  • The Dartmouth Workshop, led by John McCarthy, coined the term “Artificial Intelligence” and laid the groundwork for AI as an interdisciplinary field.

4. Early AI Research (1950s – 1960s):

  • Researchers began developing symbolic AI systems, including rule-based expert systems.

5. First AI Winter (1970s – 1980s):

  • Due to unmet expectations and challenges, AI research faced a decline in funding and interest, leading to the first “AI winter.”

6. Expert Systems (1980s):

  • Expert systems, which used rule-based reasoning, gained popularity and were applied in various domains.

7. Neural Networks (1980s – 1990s):

  • The reemergence of neural networks, inspired by the human brain, led to advancements in machine learning and pattern recognition.

8. Second AI Winter (1990s):

  • The second AI winter occurred due to high expectations and underwhelming results, particularly in the commercial sector.

9. Rise of Machine Learning (2000s – Present):

  • Machine learning, data-driven AI, and deep learning technologies saw significant advancements, driving AI applications in areas like image recognition and natural language processing.

ai history filter foundation

Foundational Concepts of AI:

1. Symbolic AI: Early AI systems used symbolic logic and knowledge representation to solve problems by manipulating symbols.

2. Machine Learning: This approach involves training algorithms to learn from data and make predictions, leading to advancements in areas like image and speech recognition.

3. Neural Networks: Inspired by the structure of the human brain, artificial neural networks are a key component of deep learning and have led to major breakthroughs in AI.

4. Expert Systems: These rule-based systems encode human expertise and were applied in areas like medical diagnosis and decision support.

5. Natural Language Processing (NLP): NLP enables computers to understand and generate human language, leading to applications like chatbots and language translation.

6. Robotics: AI-driven robotics involves creating autonomous or semi-autonomous machines capable of interacting with the physical world.

7. Ethics and Bias: As AI systems become more pervasive, addressing ethical concerns, transparency, and bias in AI decision-making has become a critical aspect of AI development.

 

 

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