Generative AI and ChatGPT- Narrates about AI, Generative AI, ChatGPT and how include chatGPT in python programs

1. Kumaresan. K,
Assistant Professor & HOD,
Department of Computer Science,
Sri. C.Achuthamenon Government College,
Thrissur
Generative AI & ChatGPT

2.  Artificial Intelligence
 Artificial Intelligence (AI) is a branch of computer science that
focuses on creating systems capable of performing tasks that
typically require human intelligence.
 These include learning, reasoning, problem-solving, understanding
natural language, speech recognition, visual perception, etc.
 AI systems are designed to mimic human cognitive functions, but
they often operate at speeds and capacities far beyond what
humans.
 Elements of AI

3. Input
Sample
s
Learnin
g
Method
Syste
m
Training
Testing

4.  A branch of artificial intelligence, concerned with the
design and development of algorithms that allow
computers to evolve behaviors based on empirical data.
 Field of study that gives computers the ability to learn
without being explicitly programmed.”
Arthur Samuel

5. Transformation

7.  Deep Learning is a subset of artificial intelligence (AI) and
machine learning (ML) that focuses on training artificial
neural networks to learn and make decisions from data.
 It is a technique inspired by the structure and functioning of
the human brain
 Neural Networks: At the core of deep learning are artificial
neural networks, which are composed of interconnected
nodes (or "neurons") organized in layers.
 These networks are capable of learning complex patterns in
data.

11.  Supervised learning
 Prediction
 Classification (discrete labels), Regression (real values)
 Unsupervised learning
 Clustering
 Probability distribution estimation
 Finding association (in features)
 Dimension reduction
 Semi-supervised learning
 Reinforcement learning
 Decision making (robot, chess machine)

13.  Generative AI enables users to quickly generate new content
based on a variety of inputs.
 Inputs and outputs to these models can include text, images,
sounds, animation, 3D models, or other types of data.
 These models learn to understand and replicate patterns in
the data they are learned/trained on/.
 They can learn to generate data points by capturing the
underlying statistical properties of a dataset. It include
images, text, audio, or even more complex types of data.

15.  Contains Two important models - Generator and
Discriminator
 Generator: This is a neural network that takes random noise
as input and transforms it into data that resembles the target
data.
 For example, in image generation, the generator might
produce an image.
 Discriminator: This is another neural network that tries to
distinguish between real data from the training set and fake
data produced by the generator.

16. Text Generation:
Content Generation: Generative models like GPT (Generative Pre-trained
Transformer) can generate human-like text for a variety of purposes, including
articles, stories, poetry, and more.
Language Translation: Models like Transformer-based models have been used for
machine translation tasks, making it possible to automatically translate text between
different languages.
Image Generation and Manipulation:
Image Synthesis: Generative Adversarial Networks (GANs) can generate high-
quality images, artwork, and even realistic faces.
Style Transfer: GANs and other generative models can transfer the style of one
image to another, creating visually striking results.
Super-Resolution: Generative models can enhance the resolution of images,
making them sharper and clearer.
Audio and Music Generation/Music Composition: AI models can generate music in
various styles composing original pieces of music.

17. Voice Synthesis: Text-to-speech (TTS) models can convert text into natural-
sounding speech.
Video Generation:
Video Synthesis: GANs and other models can generate realistic video sequences,
including deepfake videos and video game graphics.
Data Augmentation:
Generative models can create synthetic data to augment training datasets,
improving the performance of machine learning models.
Drug Discovery:
Generative AI is used in drug discovery to generate molecular structures and
predict potential drug candidates.
Anomaly Detection:
Natural Language Processing (NLP):

18. ChatGPT: An AI language model developed by OpenAI that can
answer questions and generate human-like responses from text
prompts.
DALL-E 2: Another AI model by OpenAI that can create images
Google Bard: Google’s generative AI chatbot and rival to
ChatGPT. Itcan answer questions and generate text from prompts.
Midjourney: AI model interprets text prompts to produce images
and artwork,
GitHub Copilot: An AI-powered coding tool that suggests code
completions within the Visual Studio, Neovim and JetBrains
development environments.

20.  Text-to-text Generative AI - is an AI that Generates text
based on text input. Example : ChatGPT.
 Text generation uses machine learning, existing data and
previous user input in generating responses.
 Text Generative AI can be used to:
Understanding Text
Create content
Debug code
Education
Research
Translation
Virtual Assistant

21.  ChatGPT is a state-of-the-art language model developed by OpenAI. It's based
on the GPT (Generative Pre-trained Transformer) architecture
 OpenAI, a leading artificial intelligence research organization.
 ChatGPT has been trained on a vast amount of internet text and is capable of
generating human-like text based on the prompts it receives.
 ChatGPT is designed to perform a variety of tasks, including answering
questions, generating written content, providing explanations, assisting with
programming, creating conversational agents etc
 Available versions in chatgpt1,2,3,3.5 and 4 (latest in 2023-paid)
 Text Generative AI can be used to:
Understanding Text
Create content
Debug code
Education
Research
Translation
Virtual Assistant

23.  ChatGPT-4 is an AI chatbot developed by OpenAI and launched in April
2023.
 It is designed to engage in conversations, answer questions, and help
with various tasks.
 ChatGPT-4 is only available for users with OpenAI who have a
ChatGPT Plus subscription.
 Capabilities :
Chat-GPT 4 is better at providing accurate information.
It can manage more information at once and produce better
results.
You can provide the information in text or images.
Chat-GPT 4 is good at doing difficult tasks.
It can help you with big and complex problem statements
effectively.

25.  Create API KeyGenerate a unique access code to enable
communication and authentication with the API.
Install OpenAI libraryDownload and set up the necessary software
package for OpenAI integration.
Install other necessary librariesThis step involves installing additional
essential libraries required for the intended purpose or functionality.
Set your API KeyEnter your unique API Key to authenticate and access
the API’s functionalities and resources.
Define a function that can be used to get a response from
ChatGPT:Create a function to retrieve a response from ChatGPT, enabling
seamless interaction with the model.
Query the APIRetrieve data from the API by sending a request and
receiving a response.

27.  Avoid complex inputs
 Don’t rely on the text generated by ChatGPT
 Take a look at repeated outputs
 Outlines and title generation are better
 Capabilities :