Information About ARTIFICIAL INTELLIGENCE(AI)

INFORMATION ABOUT AI (ARTIFICIAL INTELLIGENCE).
WHAT IS AI?
TYPES OF AI?
EXAMPLES OF AI?
ADVANTAGES AND DISADVANTAGES OF AI?
KEY COMPONENTS OF AI?

1. ARTIFICIAL
INTELLIGENCE (AI)

2. WHAT IS AI
Artificial intelligence is the simulation of human
intelligence processes by machines, especially
computer systems. Specific applications of AI
include expert systems, natural language
processing, speech recognition and machine
vision.

3. TYPES OF AI
1.Reactive machines
2. Limited memory machines
3. Theory of mind machines
4. Self-aware machines

4. TYPES OF AI
ARTIFICAL Narrow Intelligence (ANI)
ARTIFICAL General Intelligence (AGI)
ARTIFICAL Super Intelligence (ASI)

5. EXAMPLES OF AI
1. Maps and Navigation
2. Facial Detection and Recognition
3. Text Editors or Autocorrect
4. Search and RecommendationAlgorithms
5. Chatbots
6. Digital Assistants
7. Social Media
8. E-Payments

6. ADVANTAGES AND DISADVANTAGES
OF AI
Personalized learning: AI can analyze individual
student data, enabling the provision of personalized
learning experiences that cater to each student's
needs and preferred learning styles. As a result,
students can progress at their own pace and receive
the necessary assistance for their academic success.
Improved engagement and motivation: AI can create
more interactive and engaging learning experiences
that can help students stay focused on their learning.
Enhanced assessment and feedback: AI can provide
more accurate and timely assessment and feedback
to help students track their progress and identify areas
where they need additional support.
Increased access to education: AI can help to increase
access to education by providing more personalized
and affordable learning opportunities.
Improved teacher training: AI can help to improve
teacher training by providing teachers with data and
insights that can help them better understand their
students and their needs.
Job Displacement: AI automation may lead to job
losses in certain industries, affecting the job market
and workforce.
Ethical Concerns: AI raises ethical issues, including
data privacy, algorithm bias, and potential misuse of
AI technologies.
Lack of Creativity and Empathy: AI lacks human
qualities like creativity and empathy, limiting its ability
to understand emotions or produce original ideas.
Cost and Complexity: Developing and implementing AI
systems can be expensive, and require specialized
knowledge and resources.
Reliability and Trust: AI systems may not always be
fully reliable, leading to distrust in their decision-
making capabilities.
Dependency on Technology: Over-reliance on AI can
make humans dependent on technology and reduce
critical thinking skills.

7. TYPES OF AI

8. Key Components of AI
1.Machine learning:Machine learning is an AI application that automatically learns and
improves from previous sets of experiences without the requirement for explicit
programming.
2.Deep learning:Deep learning is a subset of ML that learns by processing data with the
help of artificial neural networks.
3.Neural network:Neural networks are computer systems that are loosely modelled on
neural connections in the human brain and enable deep learning.
4.Cognitive computing:Cognitive computing aims to recreate the human thought process
in a computer model. It seeks to imitate and improve the interaction between humans
and machines by understanding human language and the meaning of images.
5.Natural language processing (NLP):NLP is a tool that allows computers to
comprehend, recognize, interpret, and produce human language and speech.
6.Computer vision:Computer vision employs deep learning and pattern identification to
interpret image content (graphs, tables, PDF pictures, and videos).