Being-Creative-with-AI/C2/Introduction to Generative AI/English - Revision history

Madhulika at 09:14, 22 May 2026

2026-05-22T09:14:40Z

Madhurig: Madhurig moved page Being-Creative-with-AI/C2/Generative-AI/English to Being-Creative-with-AI/C2/Introduction to Generative AI/English

2026-05-22T04:48:57Z

Madhurig moved page Being-Creative-with-AI/C2/Generative-AI/English to Being-Creative-with-AI/C2/Introduction to Generative AI/English

Bellatony911 at 06:35, 21 May 2026

2026-05-21T06:35:42Z

Bellatony911 at 06:03, 21 May 2026

2026-05-21T06:03:46Z

Misbah at 03:28, 21 May 2026

2026-05-21T03:28:42Z

Misbah at 03:28, 21 May 2026

2026-05-21T03:28:21Z

Misbah at 03:27, 21 May 2026

2026-05-21T03:27:44Z

Misbah at 03:15, 21 May 2026

2026-05-21T03:15:55Z

Misbah at 03:13, 21 May 2026

2026-05-21T03:13:36Z

Misbah at 03:12, 21 May 2026

2026-05-21T03:12:55Z

← Older revision		Revision as of 09:14, 22 May 2026
Line 305:		Line 305:

	Thank you for watching!		Thank you for watching!
−
−	\|-
−
−	~~\|\| Disclaimer slide~~
−
−	\|

@@ Line 59: / Line 59: @@
 http://EduPyramids.org
-| For the Pre-requisites of this tutorial, visit the website shown on your screen.
+| For the '''Pre-requisites''' of this '''tutorial''', visit the '''website''' shown on your screen.
 |-
@@ Line 122: / Line 122: @@
 | We use '''Predictive AI''' in many everyday '''apps'''.
-Some of them are '''weather apps''', '''movie apps''', '''map apps''', and '''photo''' apps.
+Some of them are '''weather apps''', '''movie apps''', '''map apps''', and '''photo apps'''.
 |-

@@ Line 22: / Line 22: @@
 Bulleted list
-| In this tutorial, you will learn about '''Generative AI''' and '''Predictive AI'''.
+| In this tutorial, you will learn about -
-Differences between '''Predictive AI''' and '''Generative AI'''.
+*'''Generative AI''' and '''Predictive AI'''
-Some important '''Generative AI''' terms.
+*Differences between '''Predictive AI''' and '''Generative AI'''
 |-

@@ Line 174: / Line 174: @@
 | This lets them generate well-structured, meaningful, human-like text.
- '''GenAI''' grew rapidly after '''Transformer architecture''' made a breakthrough in 2017.
+'''GenAI''' grew rapidly after '''Transformer architecture''' made a breakthrough in 2017.
 |-

@@ Line 148: / Line 148: @@
 || Text highlight: "Predictive → classify / Generative → create"
-| So remember this difference. '''Predictive AI''' classifies and predicts '''data''', whereas '''GenAI''' creates examples.
+| So remember this difference.
 |-

← Older revision	Revision as of 04:48, 22 May 2026
(No difference)

@@ Line 90: / Line 90: @@
 || Split screen: Spam filter vs AI painting
-| Most '''AI''' we use daily is '''Predictive AI'''. '''Predictive AI''' classifies '''data''' and makes predictions.
+| Most '''AI''' we use daily is '''Predictive AI'''.
 |-
@@ Line 98: / Line 100: @@
 | '''Predictive AI''' helps in understanding two things.
-It can give answers to "What is this?" and "What may happen next?"
+First, it can identify "What is this?".
-'''Predictive AI''' recognizes things and makes smart guesses about the future.
+So, '''Predictive AI''' recognizes things and makes smart guesses about the future.
 |-
@@ Line 152: / Line 156: @@
 | '''GenAI''' uses a '''model''' called '''Transformer'''.
-'''Transformers''' process language in parallel, rather than word by word. This makes them faster, smarter, and more efficient.
+'''Transformers''' process language in parallel, rather than word by word.
 |-
@@ Line 164: / Line 170: @@
 || Side-by-side: before vs after Transformer
-| This lets them generate well-structured, meaningful, human-like text. '''GenAI''' grew rapidly after '''Transformer architecture''' made a breakthrough in 2017.
+| This lets them generate well-structured, meaningful, human-like text.
 |-
@@ Line 180: / Line 188: @@
 Think of the '''model''' as the "brain" of the '''AI''' system.
-A '''model''' can be small and task-specific. It can also be large and for general purposes.
+A '''model''' can be small and task-specific.
 For example, '''ChatGPT''' is a '''model''' trained on large amounts of text.
@@ Line 188: / Line 198: @@
 || Training animation
-| Next term is '''Training'''. It means teaching the '''model''' to use a large amount of data.
+| Next term is '''Training'''.
 The '''model''' is given numerous examples, including entire books and sample texts.
@@ Line 198: / Line 210: @@
 || Prompt box + user typing
-| Next term is '''Prompt'''. A '''prompt''' is the instruction you give to an '''AI model'''.
+| Next term is '''Prompt'''.
 It tells the '''model''' what task it has to perform.
@@ Line 216: / Line 230: @@
 | Next term is '''Tokens'''. '''AI models''' break the input into small pieces called '''tokens'''.
-A '''token''' is a unit of '''data'''. It can be in any form, such as text, image, or audio.
+A '''token''' is a unit of '''data'''.
 The '''model''' reads, understands, and generates information '''token''' by '''token'''.
-Think of '''tokens''' like puzzle pieces. '''AI''' first breaks the information into small pieces.
+Think of '''tokens''' like puzzle pieces.
-Next it understands each piece. Then it puts the pieces together to form a meaningful response.
+Then it understands each piece and then puts the pieces together to form a meaningful response.
 |-
@@ Line 228: / Line 246: @@
 || LLM logo examples (GPT, Gemini, LLaMA)
-| Next term is '''LLM'''. It stands for '''Large Language Model'''.
+| Next term is '''LLM'''.
 '''LLM''' is a powerful '''model''' trained on billions of text '''tokens'''.
@@ Line 238: / Line 258: @@
 || Model responding to prompt
-| Next term is '''Inference'''. '''Inference''' is when the '''model''' takes a '''prompt''' and generates an '''output'''.
+| Next term is '''Inference'''.
 It's the stage where the '''model''' produces a response after it has been trained.
-So, when you give a '''prompt''', the '''model''' generates an '''output'''.
+So, when you give a '''prompt''', the '''model''' generates text as an '''output'''.
 |-
@@ Line 249: / Line 271: @@
 Bulleted list
-| Let's summarize what we learnt:
+| Let's quickly summarize what we learnt:
 '''Predictive AI''' is used to '''classify or predict'''.
@@ Line 268: / Line 290: @@
 Also, reflect on any risks or biases that may exist in your examples.
-| Here is an assignment.
+| As an assignment do the following.
@@ Line 276: / Line 298: @@
 ||Acknowledgement slides
-|Thank you for watching!
+| This brings us to the end of the tutorial.
 |-

@@ Line 268: / Line 268: @@
 Also, reflect on any risks or biases that may exist in your examples.
 | Here is an assignment.
 |-
@@ Line 277: / Line 292: @@
 '''EduPyramids Educational Services Private Limited''', '''SINE, IIT Bombay'''.
+|

@@ Line 4: / Line 4: @@
 |-
-|| Visual Cue
+|| '''Visual Cue'''
-| Narration
+| '''Narration'''
 |-
-|| Title Slide: "Introduction to Generative AI"
+|| Title Slide: '''Introduction to Generative AI'''
 | Welcome to this Spoken Tutorial on '''Introduction to Generative AI'''.
@@ Line 208: / Line 208: @@
 || Text cum Visual tokens like puzzle pieces:
-AI breaks your text into small pieces (tokens), understands each piece, and then puts the pieces together to form a meaningful response.
+AI breaks your text into small pieces (tokens),
 | Next term is '''Tokens'''. '''AI models''' break the input into small pieces called '''tokens'''.
@@ Line 272: / Line 276: @@
 This '''Spoken Tutorial''' is brought to you by
- '''EduPyramids Educational Services Private Limited''', '''SINE, IIT Bombay'''.
+'''EduPyramids Educational Services Private Limited''', '''SINE, IIT Bombay'''.
 Thank you for watching!