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INTRODUCTION
TO
GENERATIVE AI
Exploring Cutting-Edge Technology Shaping The Future
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EVOLUTION OF ARTIFICIAL INTELLIGENCE

Artificial Intelligence enables machines to learn from data, reason,
make decisions, and solve complex problems.
AI has come a long way through different stages of development.
AI machines can display abilities such as recognizing languages and
objects.
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EVOLUTION
OF AI:
 1940S - 1960S: PAGE 04

AI emerges in the wake of cybernetics,

with the goal of imitating human cognitive
abilities.
Mathematical models of neurons and the
transition to binary logic in computers set
the foundation for AI.
The term AI is attributed to John McCarthy
at the 1956 Dartmouth conference,
considered the birth of the discipline.
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1960S - 1980S:
Early AI research focuses on expert
systems, specialized in specific domains.
Promises of AI development lead to initial
excitement, but limitations in programming
and maintenance cause a decline in
interest.
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1980S - 1990S:
AI experiences an AI winter with
reduced funding and focus due to
challenges in expert systems.
The success of Deep Blue beating
a chess champion in 1997 is a
symbolic achievement, bringing
back the interest in AI.
 2010S - 2020S: PAGE 07

A new boom in AI begins due to increased

computing power and access to massive
amounts of data.
Deep learning shows promising results in
various applications, such as voice and image
recognition.
Significant successes include Watson winning
at Jeopardy in 2011, Google's AI recognizing
cats in 2012, and AlphaGo beating the Go
world champion in 2016.
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SINCE 2020S:
Large Language Models arrive at the scene to produce systems that
can write computer code, generate images, and write poetry.
ChatGPT, a generative AI chatbot developed by OpenAI, debuts in
November 2022.
It will gain more than 100 million users by January 2023, making it
the fastest-growing consumer application to date.
Generative AI has begun to find applications in many domains
across different sectors.
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AI
BUZZWORDS
MACHINE LEARNING PAGE 10

A subset of AI that allows computers

to learn without being explicitly
programmed.
Machine learning algorithms are
trained on data, and they use that
data to make predictions or
decisions.
ARTIFICIAL NEURAL NETWORKS PAGE 11

A type of AI algorithm in which a

computer is programmed to learn in
very roughly the same way a human
brain does — through trial and error.
Each success or failure reinforces
future attempts and adaptations.
Artificial Neural Networks are often
simply called Neural Networks.
DEEP LEARNING: PAGE 12

A subset of machine learning that

uses artificial neural networks to
learn from data.
Deep learning algorithms are able to
learn complex patterns in data, and
they are often used for tasks such as
image recognition and natural
language processing
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NATURAL LANGUAGE PROCESSING

A field of study that deals with the

interaction between computers and
human (natural) languages.
NLP techniques are used to
recognize and process human
language, and they are often used
for tasks such as text classification,
machine translation, and question
answering.
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COMPUTER VISION

A field of study that deals with the

ability of computers to see and
recognize around them.
Computer vision techniques are used
to analyze images and videos, and
they are often used for tasks such as
object detection and facial
recognition.
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GENERATIVE AI

A type of AI that can create new content,

such as text, images, or music.
Generative AI algorithms are trained on
data, and they use that data to generate
new outputs that are similar to the data
they were trained on.
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LARGE LANGUAGE MODELS (LLMS)

LLMs are models that are trained using

massive amounts of text in a particular
language from all over the internet,
including e-books, news articles etc.
One of the most popular tools - ChatGPT
is actually powered by a Large
Language Model (LLM).
 STUDIO
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SHODWE

A prompt in generative AI is a set

of instructions that tells the AI
what to generate.
Prompts can be as simple as a
single word or phrase, or they can
be more complex, containing
multiple sentences or even
paragraphs.
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ACTIVITY: GUESS THE REAL VS. GENERATED

IMAGE 1 IMAGE 2
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Look closely and determine which of

the two images is generated by AI
(Select the correct image)

IMAGE 1

IMAGE 2
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ACTIVITY: GUESS THE REAL VS. GENERATED

IMAGE 1 IMAGE 2
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Look closely and determine which of

the two images is generated by AI
(Select the correct image)

IMAGE 1

IMAGE 2
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ACTIVITY: GUESS THE REAL VS. GENERATED

IMAGE 1 IMAGE 2
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Look closely and determine which of

the two images is generated by AI
(Select the correct image)

IMAGE 1

IMAGE 2
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WHAT IS
GENERATIVE AI?
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GENERATIVE AI
Generative AI is a type of artificial intelligence that can create new
content, such as text, images, or music.
Generative AI algorithms are trained on data, and they use that data to

generate outputs based on certain instructions provided by the user.

Generative AI is a rapidly growing field has the potential to be used for a
variety of applications, such as creating content, generating marketing
materials, personalizing experiences, and even writing code!
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GENERATIVE AI
VS
TRADITIONAL AI
 GENERATIVE AI PAGE 27

Some Generative AI models can create content in multiple formats like

images, text, and music based on instructions provided. These models are
known as multi-modal generative AI models.

It looks like as if it simulates human creativity, but in reality, it’s a

mathematical model that tries to predict the next word/pixel/sound in an
ordered sequence based on instructions provided and what it can recognize
from data it has been trained on.
 TRADITIONAL AI PAGE 28

Traditional AI focuses on analyzing and recognizing patterns from

existing data.

Traditional AI aims to make predictions, classifications, or optimizations

based on patterns recognized from the trained data.
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WHICH OF THE FOLLOWING STATEMENTS IS TRUE?

Generative AI can simulate human creativity, while Traditional AI

recognises patterns from existing data.

Generative AI uses rules, while Traditional AI uses data.

Generative AI requires less training, while Traditional AI requires more.

Generative AI is older than Traditional AI.

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WHICH OF THE FOLLOWING STATEMENTS IS TRUE?

Generative AI can simulate human creativity, while Traditional AI

recognises patterns from existing data.

Generative AI uses rules, while Traditional AI uses data.

Generative AI requires less training, while Traditional AI requires more.

Generative AI is older than Traditional AI.

 APPLICATIONS
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GENERATIVE AI
Generative AI has found applications in various fields, revolutionizing
industries and sparking new possibilities
 Proofreading PAGE 32

Generative AI is capable of correcting grammar and spelling errors in

written content.
 Code Generation PAGE 33

Generative AI helps developers by generating code based on instructions.

 Advertising and Marketing PAGE 34

Generative AI can create marketing campaigns.

 MEDICAL RESEARCH PAGE 35

Generative AI can aid in analyzing data for drug discovery.

 SIMULATION
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MODELING
Generative AI is capable of creating realistic models for engineering
and architecture.
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WHICH OF THE FOLLOWING CAN NOT BE GENERATED

WITH AI?
An email requesting for absence from work

Human emotions

Image captions

Fictional story
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WHICH OF THE FOLLOWING CAN NOT BE GENERATED

WITH AI?
An email requesting for absence from work

Human emotions

Image captions

Fictional story
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PROMPTING
GENERATIVE AI
 PROMPTING GENERATIVE AI PAGE 40

Prompt engineering means finding better ways to ask questions or give

instructions to AI models so they can provide more accurate and useful
responses.
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DESIGNING EFFECTIVE PROMPTS

Clear and specific instructions:
Providing clear instructions helps the AI understand our desired output.
 EXAMPLE :1
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Good Prompt:
"Make a list of reasons why brushing your teeth is a good idea. Each item in
the list should be a sentence of less than 15 words"

Bad Prompt:
"Write something about brushing your teeth"
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EXAMPLE :2
Good Prompt:
"Write a persuasive essay arguing for the importance of renewable energy
sources in mitigating climate change."

Bad Prompt:
"Write an essay"
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DESIGNING EFFECTIVE PROMPTS

Use examples of the desired output:
This can help the model to refer to the patterns and features of the desired
output
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EXAMPLE :1
Good Prompt:
"Generate a painting of a cat in Van Gogh’s style"

Bad Prompt:
"Generate a painting of a cat"
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DESIGNING EFFECTIVE PROMPTS

Experiment with different prompts:

When it comes to prompt engineering, it's important to remember that

there are no right or wrong answers.

To find the most suitable prompts for your particular use case, you may

need to iterate multiple times and experiment again till you get responses

you are satisfied with.

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What are prompts in generative AI?

The output generated by AI systems

Input given to AI on what to generate

These are the tasks we do for AI

Prompts are chapters

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What are prompts in generative AI?

The output generated by AI systems

Input given to AI on what to generate

These are the tasks we do for AI

Prompts are chapters

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Why is it important to provide clear instructions in prompts?

Clear instructions are not important because they can be boring

It helps the AI understand what we want it to generate

TheClear instructions are not important because prompts are just for
humans to readse are the tasks we do for AI

It makes the AI less creative

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Why is it important to provide clear instructions in prompts?

Clear instructions are not important because they can be boring

It helps the AI understand what we want it to generate

TheClear instructions are not important because prompts are just for
humans to readse are the tasks we do for AI

It makes the AI less creative

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Which of the following is NOT a consideration for writing

effective prompts?
Providing context

Being vague

Being specific

Being clear and easy to understand

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Which of the following is NOT a consideration for writing

effective prompts?
Providing context

Being vague

Being specific

Being clear and easy to understand

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ADVANTAGES
AND
CHALLENGES
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ADVANTAGES:
Creative assistance
Generative AI sparks new ideas and enhances human creativity.
Example: A designer can generate packaging designs from scratch or
generate variations on an
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ADVANTAGES:
Time-saving Automation
Generative AI can automate processes, saving time and increasing
efficiency.
Example: Generative AI tools can facilitate copywriting for marketing and
sales, and help brainstorm creative marketing ideas.
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ADVANTAGES:
Personalization
Generative AI can personalize experiences by tailoring content or
recommendations to individual preferences.
Example: Retailers can enhance chatbot capabilities by integrating
generative AI and existing AI tools. This enables chatbots to respond to
customer queries, track orders, offer discounts, and upsell products.
 CHALLENGES:
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False Information
Generative AI can sometimes produce inaccurate or misleading content.
 CHALLENGES: PAGE 58

Ethical Concerns
There are concerns about generative AI creating toxic or harmful content,
like deepfakes or misinformation.
 CHALLENGES:
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Bias and Fairness

Generative AI may show biases based on the data it was trained on, leading
to unfair or biased outputs.
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Generative AI offers creative inspiration, time-saving efficiency, and

exploration opportunities, while posing challenges regarding ethics, bias, and
quality control.
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Which of the following is an advantage of generative AI in

content creation?
Reduces creativity

Slows down productivity

Boosts creativity and generates new ideas

Limits exploration and human expertise

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Which of the following is an advantage of generative AI in

content creation?
Reduces creativity

Slows down productivity

Boosts creativity and generates new ideas

Limits exploration and human expertise

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What is a challenge associated with generative AI in content

generation?
Boosts creativity

Generative AI requires supercomputers to generate texts

Raises question about authenticity

Saves time
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What is a challenge associated with generative AI in content

generation?
Boosts creativity

Generative AI requires supercomputers to generate texts

Raises question about authenticity

Saves time
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POPULAR
GENERATIVE AI
TOOLS
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 AI TOOLS
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Generative AI is changing the way we

generate content by offering innovative tools
and opportunities.
These tools can help us draft an email,
generate images, edit videos, or write
computer programs!
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TEXT GENERATION
These tools can generate text based on the given prompt and can help us
translate languages, answer questions, and more.
ChatGPT
Google Bard
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Image/Video generation and editing

These tools can create realistic images, and edit images as well based on
text descriptions.
DALL-E
Midjourney
RunwayML
Synthesia
Deepbrain
 Code Generation
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These tools can generate computer programs from natural language

prompts.
GitHub Copilot
Codex
Tabnine
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WORKING
WITH
GENERATIVE AI
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TIPS TO WORK :
Generative AI has given rise to a lot of possibilities in numerous fields.
Here are a few important points to keep in mind when working with
generative AI.
 Be aware of the limitations of
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generative AI
Generative AI is still under development, and it is
not perfect.
The models can sometimes generate inaccurate
or misleading content.
It is important to be aware of these limitations
and to fact-check the information generated by
generative AI.
 Verify content generated by
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generative AI
Just because the content is generated
by AI does not mean that it is accurate
or reliable.
It is important to be critical of the
content and to evaluate it carefully
before using it.
 Use generative AI responsibly
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Generative AI can be used for both

good and bad purposes.
It is important to use generative AI
responsibly and to avoid using it for
harmful purposes.
 Label all generative AI content PAGE 76

It is important to label all generative AI

content so that users know that the
content has been generated by AI.
This will help to prevent users from
mistaking the content for human-
generated content.
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Use generative AI for creative

purposes
Generative AI is a powerful tool for
creativity.
It can be used to create new ideas, to
create art forms, and to solve problems
in new ways.
 Use generative AI for creative
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purposes
Generative AI is a powerful tool for
creativity.
It can be used to create new ideas, to
create art forms, and to solve problems
in new ways.
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KEY TAKEAWAYS
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Let’s take a quick look at what have we

learned:

Evolution of artificial intelligence

Advantages and disadvantages of generative AI
Effective design of prompts
Popular generative AI applications and tools
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THANK
YOU!
Thank you for exploring the potential of AI technology
with us! Let’s shape the future together.