These AI Class 9 Notes Chapter 1 Introduction to AI Class 9 Notes simplify complex AI concepts for easy understanding.
Class 9 Introduction to AI Notes
Intelligence Class 9 Notes
Intelligence in human beings is the ability to learn from experiences, solve problems, think abstractly, and understand complex concepts. It involves gathering information from the surrounding world, analyzing it, and using that knowledge to make decisions and adapt to new situations.
Intelligence involves being creative, learning from experiences, reasoning through problems, and being able to communicate effectively with others.
“The aggregate or global capacity of the individual to act purposefully, to think rationally and to deal effectively with his environment.” . Psychologist David Wechsler
Artificial Intelligence Class 9 Notes
“Artificial intelligence (AI) is about creating intelligent machines that can learn and perform tasks typically requiring human intelligence. It’s not necessarily about replicating human thought, but rather about enabling machines to solve problems, adapt to new situations, and make data-driven decisions. Artificial intelligence (AI) is capable of many different tasks, including speech recognition, game play, and problem solving, frequently without direct human supervision.”
For example, when you talk to Siri, Alexa, or Google Assistant, they use AI to grasp your voice commands and offer answers or do tasks. Services like Netflix and YouTube rely on AI to recommend movies or videos you might enjoy, taking into account your previous choices.
History of AI Class 9 Notes
Artificial Intelligence is not a new word and not a new technology for researchers. This technology is much older than you would imagine. Following are some milestones in the history of AI which defines the journey from the AI generation to till date development.
- 1943 American researchers Warren McCulloch and Walter Pitts present their model of artificial neurons, considered the first artificial intelligence.
- 1950 British mathematician Alan Turingproposes a test for machine intelligence. If a machine can fool humans into thinking it is human, then it has intelligence.
- 1956 American computer scientist John McCarthy coins the term “artificial intelligence” to describe “the science and engineering of making machines intelligent”.
- 1961 General Motors installs the first industrial robot, Unimate, to replace humans in assembly tasks.
- 1964 Joseph Wizenbaum develops the first natural language processing computer program, ELIZA, which simulates human conversation.
- 1966 Shakey, the first general purpose mobile robot capable of reasoning about its own actions, is launched. It is considered the forerunner of autonomous cars.
- 1997 IBM’s Deep Blué super computer beats world chess champion Garry Kasparov in one game.
- 2002 Roomba, the first mass produced robotic hoover sold by iRobot, is launched, capable of roaming and cleaning in the home.
- 2011 IBM’s Watson system, capable of answering questions asked in natural language, wins first prize in the popular US TV quiz show Jeopardy!
- 2014 The Eugene computer program passes the Turing Test by convincing a third of the judges participating in the experiment that if was a human being.
- 2016 DeepMind’s AlphaGo programme, based on a deep neural network, beats Lee Sodol, the world Go champion in five games.
- 2022 OpenAI launches ChatGPT, an artificial intelligence chatbot application trained to hold conversations and answer questions, to the public.
Types of Artificial Intelligence Class 9 Notes
Artificial Intelligence can be categorized in different ways. The two important bases on which AI can be categorized are:
In this chapter, we will discuss about Narrow AI and Strong or General AI.
Based on Capabilities
Artificial intelligence that works with limited functionality and needs some prior information to be fed in order to accomplish a task is called narrow AI. One the order hand, any device or machine that is equipped with human-like intelligence is said to be showing strong AI.
1 . Narrow or Weak AI
Artificial Narrow Intelligence (ANI) refers to AI systems that are designed and trained for a specific task or a narrow range of tasks. These systems excel at performing well-defined tasks within a limited domain but lack the ability to generalize their knowledge or skills beyond that domain.
Example Voice assistants like Siri or Alexa are examples of ANI. They can perform tasks like setting reminders, answering questions, or playing music within their specific domains but cannot perform tasks outside their programmed capabilities.
2. Strong or General AI
(AGI – Artificial General Intelligence)
Artificial General Intelligence (AGI) refers to AI systems that possess the ability to understand, learn, and apply knowledge across a wide range of tasks and domains, similar to human intelligence. AGI would have the capacity for flexible adaptation and problem-solving in various contexts.
Example As of now, AGI only exists in theory and research, with no practical implementations. An AGI system would be able to excel in tasks ranging from language understanding and problem-solving to creativity and emotional intelligence, exhibiting human-like cognitive abilities across diverse domains.
Note There is another form of AI called Artificial Superintelligence which is the highest form of AI using which machines will surpass human intelligence owing to their speed, capability to process astronomical amount of data and self-evolving smarter algorithms. What kind of world would that be with Super AI machines around is hard to predict.
Advantages of Artificial Intelligence Class 9 Notes
Artificial Intelligence (AI) offers numerous advantages across various industries and sectors. Some key advantages include:
1. Automation AI can automate repetitive tasks, saving time and effort. For example, in factories, AI-powered robots can assemble products quickly and accurately, reducing human labour.
2. Efficiency AI algorithms can process vast amounts of data much faster than humans. This ability enhances efficiency in tasks like data analysis, where AI can quickly identify patterns or anomalies that might be challenging for humans to spot.
3. Decision Making AI can assist in decision-making processes,by providing insights based on data analysis. For example, in healthcare, AI systems can analyze medical records to suggest potential treatments or diagnosis, aiding doctors in making informed decisions.
4. Personalization AI enables personalized experiences by analyzing user preferences and behaviour. For example, streaming platforms use AI to recommend movies or music based on what users have previously watched or listened to.
5. 24/7 Availability AI systems can work round the clock without fatigue. For example, chatbots provide customer service at any time, addressing queries and issues even outside of regular business hours.
Disadvantages of Artificial Intelligence Class 9 Notes
While Artificial Intelligence (AI) offers numerous benefits, there are several disadvantages and challenges associated with its development and deployment. Some of these disadvantages include:
- Job Loss AI can do some tasks that people used to do. For example, in factories, robots powered by AI might replace some workers who used to assemble things.
- Unfair Decisions Sometimes, AI systems can make decisions that are not fair because they learn from old data that might have biases. Like when a computer program used for hiring prefers one group of people over others without a good reason.
- Privacy Problems AI needs a lot of information to work well, but sometimes, it collects too much personal data. Imagine if a shopping app collected more info about you than you wanted and shared it without your permission.
- Ethical Questions AI might face situations where making the right choice is not easy. For example, imagine a self-driving car that has to decide between hitting one person or another in an accident.
- Hard to Understand Some AI systems work like a mystery. They give answers, but it’s tough for people to know how they reached those conclusions.
Domains of AI Class 9 Notes
The major Domains of Artificial Intelligence are
Data (Data Science)
Data is a collection of raw facts which can be processed to make information out of it. Data includes structured data (organized in databases) and unstructured data (like text, images, videos).
Data Science refers to the scientific study of data. It applying scientific methods, statistical techniques, computational tools, and domain expertise to explore, analyze, and extract insights from data.
Data science is related to
- Data Mining refers to the process of discovering patterns, trends, and insights from large datasets.
- Machine Learning (ML) is a discipline of artificial intelligence (AI) that provides machines with the ability to automatically learn from data and past experiences while identifying patterns to make predictions with minimal human intervention.
- Big Data refers to the massive volume of information that is too large and complex for traditional data processing techniques to handle efficiently. Big data is generated from various sources such as social media, sensors, mobile devices, and more.
Computer Vision (CV)
Computer vision is an artificial intelligence domain instructing computers to comprehend and interpret visual data. It involves tasks such as image recognition, object detection, video analysis, and image generation. CV helps AI systems to “see” and comprehends visual data, enabling applications in fields like autonomous vehicles, healthcare diagnostics, and augmented reality.
Natural Language Processing (NLP)
Natural Language Processing (NLP) is a domain of artificial intelligence that deals with the interaction between computers and humans in natural language. It involves the use of computational techniques to process and analyze natural language data, such as text and speech, with the goal of understanding the meaning behind the language.
It has two-sub categories:
Natural Language Understanding (NLU) which involves the ability of computers to comprehend and interpret human language input. NLU also enables computers to communicate back to humans in their own languages (e.g., Siri and Google Assistant understand our speech).
Natural Language Generation (NLG) simply means producing text from computer data. It acts as a translator and converts the computerized data into natural language. In this, a conclusion or text is generated based on collected data and input provided by the user. NLG is used in applications like chatbots, summarization tools, report generation, and content creation.
Applications of Artificial Intelligence Class 9 Notes
1. Healthcare
AI algorithms can analyze medical images like X-rays and MRIs to detect abnormalities faster and more accurately than humans. Chatbots can provide round-the-clock assistance, answering patient queries and offering personalized health advice, thereby enhancing access to healthcare services.
2. Automobiles
Artificial intelligence enhancing safety and efficiency in automobiles industries. AI interprets data in self-driving automobiles, such as Tesla’s Autopilot, to ensure safe navigation. AI-powered systems also optimize fuel use and predict maintenance requirements, hence enhancing overall performance.
3. Education
Personalizing learning experiences is a key way artificial intelligence is transforming education. AI-powered tutoring systems like Khan Academy can adjust to students’ learning styles and speed, improving comprehension. Language learning programs like Duolingo use AI to provide personalized exercises and targeted feedback, helping users identify and address weaknesses more effectively.
4. Digital Voice Assistants
AI is the brains behind smart assistants like Siri, Alexa, and Google Assistant. These virtual assistants understand our voice commands, allowing us to set reminders, play music, control smart home devices, and even get answers to our questions.
5. Facial Recognition
One of the most notable applications of AI in daily life is facial recognition. It replaces pin codes and fingerprints on cellphones to enable quick unlocking. Various algorithms that can identify a person’s face with remarkable precision, social networking sites like Facebook use facial recognition to automatically recommend tagging friends in photos you submit. Airports are also using this technology to speed up boarding by using facial recognition to confirm identity, which makes travel easier.
6. Humanoid Robots
Humanoid robots are finding uses in a surprising number of fields, from dangerous industrial tasks to providing companionship for people. Here are a few areas where you might encounter them:
Manufacturing Humanoid robots can be used on assembly lines to perform delicate tasks or handle heavy materials. For instance, they can weld car parts or carefully assemble electronics with greater precision and tireless endurance than humans.
Space Exploration Since they can mimic human movements, humanoid robots are being developed to assist astronauts in space. NASA’s Robonaut 2 was one of the first humanoid robots to be sent to the International Space Station. These robots can help with routine tasks or even perform dangerous repairs outside the spacecraft.
Healthcare Humanoid robots are being studied for use in physical therapy and rehabilitation. They can be used to guide patients through exercises or provide companionship and emotional support. For example, a robot named Pepper has been used to help reduce social isolation among elderly patients.
Research Humanoid robots are valuable tools for researchers in a variety of fields. Studying how to build robots that move and interact like humans can lead to a better understanding of human biology and movement. This knowledge can then be used to create new prosthetics or improve surgical techniques.
Sophia is a humanoid robot developed by Hanson Robotics that is known for its realistic appearance and ability to simulate human conversation. She is the world’s first robot citizen. While Sophia isn’t currently being used in a commercial setting, it’s a good example of the potential for humanoid robots to interact with people in a natural way. In the future, robots like Sophia could be used for education, entertainment, or even as companions for people who live alone.
Future Goals of Artificial Intelligence Class 9 Notes
The future of AI holds immense potential to reshape various aspects of human life and society. Here are some key points:
1. Automation AI will continue to automate routine tasks across industries, improving efficiency and productivity. This will lead to significant changes in the workforce, with a shift towards more skilled and creative roles.
2. Personalization AI algorithms will enable highly personalized experiences in areas such as marketing, healthcare, education, and entertainment. Products and services will be tailored to individual preferences and needs, enhancing user satisfaction.
3. Healthcare AI-powered tools will revolutionize healthcare by enabling early disease detection, personalized treatment plans, and improved patient outcomes. AI algorithms will analyze vast amounts of medical data to identify patterns and insights that can inform diagnosis and treatment decisions.
4. Autonomous Systems AI will drive the development of autonomous vehicles, drones, and robots that can perform tasks independently. These systems will revolutionize transportation, logistics, and manufacturing, leading to safer and more efficient operations.
5. Ethical and Social Implications As AI becomes more pervasive, ethical considerations surrounding data privacy, bias, transparency, and accountability will become increasingly important. Society will need to address these challenges to ensure that AI technologies benefit everyone equitably.
6. Collaboration Humans and AI will collaborate more closely in various domains, augmenting each other’s capabilities. This human-AI partnership will lead to innovative solutions to complex problems and drive progress in science, engineering, and creative endeavors.
Glossary
- Artificial Intelligence (AI) It is the field of computer science concerned with creating intelligent machines that can perform tasks typically reguiring human intelligence.
- Artificial Narrow Intelligence (ANI) It refers to AI systems that are designed and trained for a specific task or a narrow range of tasks.
- Artificial General Intelligence (AGI) It refers to AI systems that possess the ability to understand, learn, and apply knowledge across a wide range of tasks and domains, similar to human intelligence.
- Data Science It refers to the scientific study of data. Computer Vision It is an artificial intelligence domain instructing computers to comprehend and interpret visual data.
- Natural Language Processing (NLP) It is a domain of artificial intelligence that deals with the interaction between computers and humans in natural language.
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