artificial intelligence

1. ARTIFICIAL
INTELLIGENCE
Shaping the
Present and Future

2. Artificial Intelligence (AI) refers to the development of computer
systems that can perform tasks requiring human-like
intelligence. These tasks include problem-solving, reasoning,
learning, understanding natural language, and perception.
WHAT IS AI
2

3. TYPES AND STAGES OFAI
* According to a Survey
3
NARROW
(WEAK) AI
• Specialized in a single task.
• Performs well within a predefined scope.
• Examples:
Virtual personal assistants (Siri,Alexa)
, recommendation systems.
GENERAL
(STRONG) AI
• Possesses human-like cognitive
abilities.
• Understands, learns, and performs a
wide range of tasks.
• Capable of reasoning, problem-solving,
and adapting to new situations.
• Human-level AI remains a theoretical
concept, yet to be achieved.
TYPES OF AI

4. TYPES AND STAGES OFAI
* According to a Survey
4
REACTIVE
MACHINES
Earliest stage of AI.
Follows pre-programmed rules
to make decisions.
Lacks memory and learning
capability.
Examples: Chess-playing
computers with predefined
moves.
LIMITED
MEMORY AI
Learns from historical data
to improve performance.
Utilizes past experiences
for decision-making.
Examples: Self-driving
cars learning from real-
world scenarios.
THEORY OF
MIND AI
Understands human
emotions, beliefs, and
intentions.
Recognizes and responds
to emotional states.
Still a theoretical concept
and not yet realized.
SELF-AWARE AI
Possesses consciousness
and self-awareness.
Understands its own existence
and emotions.
This level of AI is largely
speculative and futuristic.
Stages of AI
Development

5. DOMAINS OFAI
*Based on 1st year projections
5
22% 45% 38% 10% 8%
Entertainment Finance Entertainment Education Healthcare
AI Applications Across Industries

6. MACHINE LEARNING, DEEP LEARNING,
NEURAL NETWORKS, AND NLP
6
Machine Learning is a subset of AI that
focuses on developing algorithms that
enable computers to learn from and
make predictions or decisions based on
data.
Machine Learning (ML)
Deep Learning is a subfield of Machine
Learning that uses neural networks with
multiple layers to analyze complex
patterns in data.
Deep Learning (DL)
• Structure: Neural networks consist of
interconnected nodes (neurons)
organized in layers (input, hidden,
output).
• Training: Neural networks learn by
adjusting the weights of connections
based on the error between predicted
and actual output.
• Deep Neural Networks: Networks
with many hidden layers are capable of
learning hierarchical features.
Neural Networks
NLP is a branch of AI that focuses on
enabling computers to understand,
interpret, and generate human language.
Natural Language
Processing (NLP)

7. AI IN DAILY LIFE
7
• Examples: Virtual assistants like Siri, Alexa,
and Google Assistant use AI to understand
and respond to voice commands.
• Tasks: They can set reminders, answer
questions, provide weather updates, and
control smart devices.
Virtual Assistants
• Content Curation: AI algorithms
personalize social media feeds by showing
content relevant to users' interests and
behaviors.
• Recommendations: Platforms suggest
friends, groups, and pages based on users'
connections and activities.
Social Media
• Diagnosis and Treatment: AI aids doctors
by analyzing medical data for early disease
detection and suggesting treatment options.
• Wearable Devices: Smartwatches and
fitness trackers use AI to monitor health
metrics and suggest exercise routines.
Healthcare

8. AI IN DAILY LIFE
8
• Facial Recognition: AI-enabled security
systems use facial recognition to grant
access to devices and buildings.
• Fraud Detection: AI analyzes transaction
patterns to identify suspicious activities and
prevent financial fraud.
Security
• Real-Time Translation: AI translates
languages on the fly, facilitating
communication between people who speak
different languages.
• Language Learning: Language learning
apps use AI to teach pronunciation,
vocabulary, and grammar.
Language Translation
• Home Automation: AI controls smart
devices like thermostats, lights, and
appliances to optimize energy usage and
enhance convenience.
• Voice Control: AI-powered voice assistants
control smart home devices based on user
commands.
Smart Homes

9. AI IN DAILY LIFE
9
• GPS and Maps: AI-powered navigation
apps recommend optimal routes based on
real-time traffic data and user preferences.
• Predictive Alerts: AI notifies users about
traffic jams, accidents, and road closures,
allowing them to plan alternate routes.
Navigation
• Product Recommendations: Online
retailers suggest products based on user
browsing history, purchases, and similar
users' behaviors.
• Chatbots: AI-driven chatbots assist
customers in finding products, tracking
orders, and resolving issues.
E-commerce
• Content Suggestions: Streaming platforms
recommend movies, shows, and music
based on user preferences and viewing
history.
• Gaming: AI-powered opponents adapt their
strategies to challenge players, enhancing
gaming experiences.
Entertainment

10. FUTURE OFAIAND ITS IMPACT
10
AI's Evolution: Opportunities and Challenges Ahead
• Automation and Job Disruption
• Ethical Considerations
• Advancements in Medicine
• Human-Machine Collaboration
• AI in Education
• Environmental Impact
• AI-Powered Creativity
• Human Well-Being
• Closing Thoughts

11. CONCLUSION
• Rapid Evolution: Artificial Intelligence has rapidly evolved from theoretical
concepts to practical applications, transforming various aspects of our
lives.
• Diverse Applications: AI's impact spans industries such as healthcare,
finance, entertainment, and more, enhancing efficiency and decision-
making.
• Advancements: Machine Learning, Deep Learning, and Neural Networks
have unlocked the potential for AI to tackle complex tasks and learn from
data.
• Daily Integration: AI is seamlessly integrated into our daily lives through
virtual assistants, social media algorithms, navigation apps, and more.
• Challenges and Opportunities: While AI presents incredible
opportunities, ethical considerations, bias, transparency, and job disruption
must be addressed.
• Human-AI Collaboration: The future involves collaboration between
humans and AI, leveraging their respective strengths to drive innovation. 11

12. QUESTIONS AND DISCUSSION
12
Exploring AI's Impact and Future Possibilities

13. 13
Leader of the team
Sanuri Ashen Kalasi
Sheshitha Naduni
THE TEAM
Keshan

14. THANK
YOU