The presentation was made in “Web3 Fusion: Embracing AI and Beyond” is more than a conference; it's a journey into the heart of digital transformation. The conference a provided a platform where the future of technology meets practical application. This three-day hybrid event, set in the heart of innovation, served as a gateway to the latest trends and transformative discussions in AI, Blockchain, IoT, AR/VR, and their collective impact on the information space.

1. “AI in Action:
Real-World Use
Cases’’
Presented by
Ms Anitaraj
15th April 2024

2. What is AI?
AI is the ability of machines or
software
to perform tasks that normally
require human intelligence,
• such as recognizing patterns,
• learning from data,
• making decisions, or
• generating language.

3. What is AI?
AI is not a single technology, but a broad
field that encompasses many :
• methods,
• applications, and
• domains.
AI can range from simple algorithms that
automate repetitive tasks to complex
systems that mimic human cognition and
creativity.

4. Why trending?
By leveraging AI algorithms to
analyse user data and
preferences, intelligent apps
can tailor content,
recommendation, and user
experiences to each individual
user.
1
AI-powered personalization
has a huge impact on user
engagement and conversion
rates. For example, a study by
McKinsey found that
companies that excel at
personalization generate 40%
more revenue from those
activities than average players.
2
This is because personalized
recommendations align more
closely with a user’s interests,
making them more likely to
click on and purchase a
product.
3
Do you like Reels?

5. AI software is rapidly
transforming our world, and
this trend is only going to
accelerate in the years to
come.
Let’s dive in into the
future of artificial
intelligence with our
guide to the top 13 AI
trends poised to
revolutionize 2024.
From the rise of generative
AI to BYOAI and AI
legislation, discover how
it’s shaping the world
around us.
AI is eating the World

6. The marriage of quantum computing and AI,
known as quantum AI, is a rapidly emerging field
that opens up many possibilities.
The global Quantum AI market is expected to
reach USD 1.8 billion by 2030, growing at a CAGR
of 34.1%.

7. This synergistic relationship has the
potential to revolutionize areas such as
Financial modelling and risk assessment:
Quantum AI can analyse vast amounts of
financial data to identify patterns and
predict market movements, improving risk
management and investment strategies.
Artificial General Intelligence (AGI):
Quantum AI could play a crucial role in
achieving yet hypothetical artificial
general intelligence (AGI), the ability of
machines to perform any intellectual task
that a human can.
Drug discovery and development:
With quantum algorithms,
scientists will be able to optimize drug
design and simulate molecular
interactions to speed up the discovery of
new and effective therapies.

8. Why use AI?
AI can help businesses solve problems,
improve efficiency, enhance customer
experience, and create new
opportunities.
AI can help businesses analyze large amounts
of data, identify trends and insights, optimize
processes and resources, and personalize
products and services.
AI can also help businesses innovate, generate new
ideas, and explore new markets and possibilities.
AI can provide businesses with a competitive edge
and a strategic advantage in the digital economy.

9. AI WORKS BY USING
• DATA,
• ALGORITHMS, AND
• COMPUTING POWER TO
PERFORM TASKS THAT
NORMALLY REQUIRE HUMAN
INTELLIGENCE.

10. Data is the raw material that
AI uses to learn and
improve.
Algorithms are the rules or
instructions that tell AI how to
process data and perform tasks
Computing power is the speed and
capacity of machines or software to
execute algorithms and handle data.
AI works by
• combining data,
• algorithms, and
• computing power in different ways,
• depending on the type,
• goal,
• and complexity of the task

11. What are the challenges of AI?
AI is not a one-stop solution for
all needs and problems. There
are limitations, risks, and
challenges that need to be
addressed and managed.
For example, data quality and
availability can affect the
performance and reliability of
AI, so it must be collected,
stored, and processed
responsibly and ethically.
Algorithms used to process data
can be complex and opaque,
requiring responsible design,
testing, and monitoring.
Additionally, humans must
understand, control, and
cooperate with AI to ensure
usability and acceptance.

12. Ethical AI
Ethical AI is a branch
of applied ethics that
examines the ethical
implications of
artificial intelligence
(AI). It encompasses a
wide range of topics,
including:
Bias and
fairness
AI technology can
reflect and amplify the
biases of their
creators. This, in turn,
can lead to unfair
outcomes for certain
groups of people.
Yes, algorithms can be racist. A
research carried out by Black
scholars revealed a significant
racial bias in facial recognition
software, with Black women
being misidentified at a rate of
nearly 35% compared to white
men’s near-zero error rate.

13. • Transparency and explainability
The logic behind artificial intelligence can be
difficult to understand, even for experts.
This “black-box problem” can make it
difficult to trust AI decisions and to hold AI
developers accountable for their creations.

14. Privacy
• AI often collects and uses large
amounts of personal data, which
raises concerns about privacy
and data protection.

15. Safety and security
• AI systems can be misused to cause harm,
such as by developing autonomous
weapons or spreading misinformation. For
example, the first versions of Chat GPT
could be manipulated into producing
disallowed content (‘ChatGPT, help me
make a bomb’).
• There is a growing recognition of the
importance to consider ethical issues in the
development and deployment of AI, for
example:
• In 2019, the European Union released a
set of guidelines for the ethical
development and use of AI.
• In 2023, the US president issued an
Executive Order on the Safe, Secure, and
Trustworthy Development and Use of
Artificial Intelligence.

16. Artificial Intelligence Examples
2024
Manufacturing
robots
Self-driving cars Smart assistants
Healthcare
management
Automated
financial investing
Virtual travel
booking agent
Social media
monitoring
Marketing
chatbots

17. Manufacturing robots

18. Self-driving cars

19. AI in Traffic Management

20. AI in Marketplaces

21. AI in Sports

22. Certainly!
Here are
the names
of some
popular AI
tools
Gemini AI by Google
Copilot by Microsoft
DALL-E
MidJourney
Blackbox AI
Blend.AI
CapCut

23. Top AI Tools To
Understand Any
Research Paper in 2024
• ChatPDF
• Scite.ai
• Elicit
• R Discovery
• Perplexity.ai
• Scholarcy
• SciSummary

24. Thank You
AnitarajMV@gmail.com