2. 1.Introduction to AI
2.Importance and Impact of AI in Various Industries:
3.Types of Artificial Intelligence
4.Examples of AI applications
5.AI in Machine Learning
6.AI in NLP
7.AI in reinforcement learning (RL)
8.AI in Neural Network
9.Smart assistants
10.Examples of popular smart assistants
11.The interaction flow between users and smart
assistants
12.Application of smart assistant
13.Benefits of Smart Assistants
14.Challenges and Limitations of Smart Assistants
15.CASE STUDY
16.Ethical Considerations
17.conclusion
content
3. Artificial Intelligence (AI) refers to the simulation
of human intelligence in machines, enabling them
to perform tasks that typically require human
intelligence. These tasks include learning,
reasoning, problem-solving, perception,
understanding natural language, and even
interacting with the environment
what is
AI?
4. Although the terms
artificial intelligence
(AI) and machine
learning are
frequently used
interchangeably,
(machine learning is
a subset of the larger
category of AI.
Artificial
intelligence
signifies
computers'
general ability to
mimic athought
while carrying out
tasks in real-
world
environments
Machine learning
implies to the
technologies and
algorithms that
allow systems to
recognize patterns,
make decisions,
and improve
themselves through
experience and
data.
how does machine Learning
Relate to Ai?
5. AI IN NLP
Artificial Intelligence (AI) in Natural Language Processing (NLP) is a field that
focuses on enabling computers to understand, interpret, and generate human
language. It involves developing algorithms and models that can analyze text
or speech data, extract meaningful information, and perform tasks such as
language translation, sentiment analysis, and text summarization. AI-
powered NLP systems have numerous applications across various industries,
including virtual assistants, healthcare, customer service, and social media
analysis. Despite advancements, challenges such as ambiguity in language
understanding and ensuring fairness and transparency in NLP models persist.
However, AI in NLP continues to evolve rapidly, driving innovations in
communication and human-computer interaction.
6. AI in reinforcement
learning
Artificial Intelligence (AI) in reinforcement learning (RL) is a branch of AI focused
on training agents to make sequential decisions in dynamic environments. Unlike
supervised learning, where models learn from labeled data, RL agents learn by
interacting with an environment and receiving feedback in the form of rewards or
penalties for their actions. Through trial and error, RL algorithms aim to discover
optimal strategies or policies to maximize cumulative rewards over time. AI in RL
has applications in various domains, including robotics, autonomous vehicles,
game playing, and resource management. Despite challenges such as exploration-
exploitation trade-offs and sample inefficiency, RL continues to advance, driven
by innovations in deep learning and algorithmic improvements.
7. AI IN NEURAL NETWORK
•AI plays a central role in neural networks, a class of machine learning
algorithms inspired by the structure and function of the human brain.
Here's how AI is utilized in neural networks:
•Learning Representations: AI algorithms, such as backpropagation,
stochastic gradient descent (SGD), and optimization techniques like Adam
and RMSprop, are used to train neural networks by adjusting the weights
and biases of connections between neurons to minimize the error between
predicted and actual outputs.
Activation Functions: AI algorithms are used to design and select activation
functions for neurons in neural networks, determining how inputs are
transformed into outputs. Common activation functions include sigmoid,
tanh, ReLU (Rectified Linear Unit), and softmax, each serving different
8. EXAMPLE
AI can be used for various
situations, but these are
some examples of AI in our
daily life.
E-commerce
Virtual Assistance
Autonomous vehicles
chatbots
Recommendation
systems
Navigation apps
Facial
recognition
Text
editors
9. SofiA THE AI ROBOT
Sophia is a realistic
humanoid robot capable of
displaying humanlike
expressions and interacting
with people. It's designed
for research, education, and
entertainment, and helps
promote public discussion
about AI ethics and the
future of robotics.
10. WHAT PROBLEMS CAN AI SOLVE?
As shown above, AI can solve a LOT of problems. Let's explore a
few on the next slide!
→ dectecting spam
→ medical records
→ idea generation,
finding data
→ self driving cars
11. USE OF AI
(Advantages of ai)
Image and facial
recognition
It can help make data
safer and more secure.
For example, face
authentication can
ensure that only the
appropriate person
has access to sensitive
information that is
intended specifically
for them
Medical diagnosis
Provides more exact
diagnoses, detects
hidden patterns in
imaging investigations,
and predicts how
patients will respond to
specific medications.
This leads to better
treatment strategies,
fewer clinical errors,
and more accurate
diagnosis.
Customer service
Customer service
teams can get feedback
from customers by
using AI. For example,
AIpowered information
can provide agents
with information on
client intent, language,
and sentiment so they
are aware of how to
approach an encounter.
Recommendation
systems
AI content
recommendations help
people stay engaged
and informed. For
example, Virtual(Siri
and Alexa.),
Personalized content
on streaming
platforms, Apps that
suggest best routes
based on traffic.
12. what are the
disadvantages of AI?
• Lack of Transparency
• Bias and Discrimination
• Privacy Concerns
• Ethical Dilemmas
• Security Risks
• Concentration of Power
• Dependence on AI
• Job Displacement
→ lying about using
AI
→ assumtion based of incorrect
information
13. Put People First
People should use their own creativity, not copy
off of AI! AI is just a tool for efficiency!
Minimize unintended
bias
Consider data and privacy
goals
Ensure AI transparency
14. REsponsible Ai USe
AI can help do repetitive work for humans, but humans should still be prioritized.
Create a culture that utilizes creativity, empathy, and dexterity from humans and AI for
increased efficiency
Businesses should adopt strong security measures, limit access to sensitive data, and
anonymize data whenever possible to secure data privacy with AI and ML technologies
There needs to be fairness in AI which entails identifying and eliminating
discrimination while also encouraging diversity and inclusion. This is can be done by
using training models with equal representation
Develop explainable AI that is visible across processes and functions to generate
trust among employees and customers. Provide examinability, comprehension,
and traceability.
15.
16. Smart assistants, also known as virtual assistants or
intelligent personal assistants, are software
applications or platforms that utilize artificial
intelligence (AI), natural language processing (NLP),
and machine learning algorithms to provide users with
personalized assistance, perform tasks, and retrieve
information in response to voice commands or typed
queries.
what is Smart
Assistant
17. Examples of popular smart assistants
Siri (Apple): Siri is Apple's virtual assistant, available on iOS devices
(iPhone, iPad, iPod Touch), macOS, watchOS, and HomePod. Users
can interact with Siri using voice commands to perform various tasks
such as sending messages, making calls, setting reminders, playing
music.
Google Assistant: Google Assistant is Google's virtual
assistant available on Android devices, iOS devices,
Google Home speakers, smart displays, and other third-
party devices. It can perform tasks similar to Siri, as well
as provide personalized recommendations, control smart
home devices, manage schedules, and answer
questions using Google's vast knowledge graph.
18. The interaction flow between
users and smart assistants
The interaction flow between users and smart assistants typically follows a sequence of steps
that involve input from the user, processing by the smart assistant, and output or action taken
by the assistant. Here's a general overview of how the interaction flow works:
• Wake Word Activation: The interaction begins when the user triggers the smart assistant
by saying a wake word or phrase. This wake word activates the assistant and signals it to
start listening for the user's command.
• Input/Input Recognition: Once the wake word is detected, the smart assistant listens to
the user's input, which can be in the form of a voice command or a typed query.
• Intent Recognition: After understanding the user's input, the smart assistant identifies the
user's intent or the action the user wants to perform
• Processing and Contextual Understanding: The smart assistant processes the user's
request, taking into account contextual information such as the user's preferences, past
interactions, location, and other relevant data
19. Application of smart
assistant
• Home Automation: Smart assistants can control smart home devices
such as thermostats, lights, locks, cameras, and appliances. Users
can use voice commands to adjust settings, turn devices on or off, or
create automation routines.
• Personal Organization: Smart assistants help users manage their
schedules, set reminders, create to-do lists, and organize
appointments. They can also provide weather forecasts, traffic
updates, and travel information.
• Entertainment: Users can use smart assistants to play music,
podcasts, audiobooks, and radio stations.
20. CASE Study
Here are a couple of case studies highlighting how organizations have leveraged smart assistants to
achieve success:
Domino's Pizza:
•Background: Domino's Pizza, a global pizza delivery company, wanted to enhance customer
experience and streamline the ordering process.
•Solution: Domino's introduced its virtual assistant, Dom, which allows customers to place orders
using natural language commands via various platforms, including the Domino's website, mobile
app, and smart speakers.
•Successes: Dom has simplified the ordering process, making it faster and more convenient for
customers. By integrating with various channels, Dom enables seamless ordering experiences
across different platforms.
•Lessons Learned: Domino's success with Dom highlights the importance of understanding
customer preferences and providing convenient, intuitive interfaces for interacting with smart
assistants. Continuous iteration and improvement based on user feedback are crucial for
optimizing smart assistant performance and enhancing customer satisfaction.
21. .
CONCLUSION
We conclude that if the
machine could successfully
pretend to be human to a
knowledgeable observer then
you certainly should consider it
intelligent. AI systems are now
in routine use in various field
such as economics, medicine,
engineering and the military, as
well as being built into many
common home computer
software applications,
traditional strategy games etc.
In conclusion, the implementation
of smart assistants presents both
opportunities and challenges
across various industries and use
cases. Smart assistants leverage
AI and natural language
processing technologies to
streamline tasks, enhance
productivity, and improve user
experiences. However, several
considerations must be addressed
to maximize the benefits of smart
assistant technology
