More articles in ChatGPT

There was a time when books were the only source of information, and then Google came into the picture. However, with advancements in artificial intelligence (AI), ChatGPT has become the go-to search space for most people.

But why ChatGPT?

ChatGPT has done wonders for writers, coders, and professionals from all aspects. Simply put, it cut short any long-forming process. It helps writers create articles, short content, and creative ideas as it speeds up the writing process. All in all, coders get a lot of use out of ChatGPT when it comes to generating code and offering suggestions or explaining how potential issues can be debugged. Alongside these, ChatGPT abets other industries by automating repetitive jobs, helping with research, and providing custom insights so that professionals can dedicate more time to making strategic and creative decisions.

Do you know…

According to a study by Amazon Web Services, 57% of content on the Internet today is generated using AI. According to a Forbes report, this number will likely reach 90% by 2025.

Now, you might know the definition of ChatGPT and why it is used, despite Let’s revisit the memory lane…

What is ChatGPT?

ChatGPT is an AI-powered conversational agent developed by OpenAI. It is based on Generative AI, a type of artificial intelligence designed to create new content by learning from large datasets of existing content. 

ChatGPT is your go-to person with solutions to all your problems, but by Generating TEXT.

ChatGPT is a Large Language Model (LLM) that uses a variant of the Transformer architecture to understand and generate human-like text based on the input it receives.

ChatGPT, when asked to make a quote about itself: 

“ChatGPT is a powerful language model that has the potential to revolutionize the way we interact with and utilize artificial intelligence in our daily lives. Its ability to generate human-like text allows it to assist with a wide range of tasks that involve language processing, making it a valuable tool for businesses, researchers, and individuals alike.”

Definition and Functionality

Fundamentally, ChatGPT is a text-processing tool that can take in textual inputs and generate coherent responses. Its versatility allows it to be used in many ways, such as answering questions, providing recommendations, summarizing texts, and simply generating content for many domains.

One of OpenAI’s descriptions of ChatGPT reads:

“ChatGPT is an AI model trained to follow instructions and provide detailed, coherent responses to user prompts. It leverages a large dataset of diverse text to simulate conversation.”

It is based on a Generative Pretrained Transformer, a type of deep learning introduced in 2018. Every follow-up model—GPT -2, GPT-3, GPT-4, GPT-4o and soon-to-come GPT 5—has become bigger and better. These models are pre-trained on massive datasets from the internet and then fine-tuned for specific applications, allowing them to engage in interactive, context-sensitive dialogues.

Overview of Generative AI and ChatGPT

Source: OpenAI – It depicts how ChatGPT was trained

By generative AI, you can understand a system that produces new content with prompts (text, image, music, etc.). Generative models are a subset of AI models where the network goes beyond its normal classification or regression function to generate new data from what it has learned. Here’s an example: With ChatGPT, one of the state-of-the-art Natural Language Processing (NLP) tools, you can engage in incredibly natural and human-like conversations—sometimes even better than interacting with a real person.

As explained by OpenAI:

“Generative AI models like GPT are designed to predict the next word in a sequence, and by doing this repeatedly, they can generate coherent and contextually relevant text.”

These generative models have multiple applications in industries, from customer service automation to content creation and education. For instance, ChatGPT can assist with:

1. Customer Support: Acting as a virtual assistant, ChatGPT can handle inquiries, complaints, and service issues.
2. Writing and Editing: Generative AI can draft articles, create reports, and refine written material.
3. Coding Assistance: With an understanding of programming languages, ChatGPT can generate code snippets, help debug errors, or explain complex programming concepts.
4. Education: It helps explain complex concepts or summarize topics across academic fields.

For more about ChatGPT, refer to this article: How to Use Chat GPT? A Simple Guide for Beginners

The success of ChatGPT in various applications is due to its training process, which involves pre-training on extensive text data and fine-tuning on specific instructions to enhance response accuracy and coherence.

Reading List 

6 Easy Ways to Access ChatGPT-4 for Free 

From Zero to Millionaire: Generate Passive Income using ChatGPT

Evaluating GPT-4o mini: How OpenAI’s Latest Model Stacks Up?

All About ChatGPT-4 Vision’s Image and Video Capabilities

How to Make Custom ChatGPT?

Why Does ChatGPT Use Only Decoder Architecture?

The Evolution of ChatGPT (From GPT-1 to GPT-4o and more)

The evolution of ChatGPT has been marked by significant advancements in its underlying technology, capabilities, and applications.

With this evolution of GPTs, Sam Altman says – I don’t quite agree with it, but “a calculator for words” is an interesting framing for ChatGPT,

2015: The Birth of OpenAI
OpenAI was founded by Sam Altman, Elon Musk, and others to ensure that artificial intelligence (AI) benefits everyone.

2018: The Introduction of GPT-1
OpenAI introduced GPT-1, its first language model, in a research paper titled “Improving Language Understanding by Generative Pre-Training.”

2019: GPT-2 Arrives
GPT-2 was launched with 1.5 billion parameters, showcasing better text generation. OpenAI initially held back the full release, fearing misuse.

2020: The Power of GPT-3
OpenAI released GPT-3, which features a whopping 175 billion parameters and marks a huge leap in text generation capabilities.

2022: ChatGPT Takes Off
ChatGPT, based on the GPT-3.5 model, was launched and quickly gained massive popularity, reaching over a million users in just five days.

2023-2024: GPT-4 Breakthroughs
GPT-4 was released, allowing the processing of both text and images, pushing the boundaries of what AI can do. OpenAI also introduced GPTs, allowing users to create customized ChatGPT models for specific tasks. Later, GPT-4o was announced, adding audio processing to the mix and setting new records for performance.

Future: GPT-5 on the Horizon
The future is bright! GPT-5 is expected to bring even more groundbreaking capabilities that will astonish us all.

Reading List 

Multimodal Chatbot with Text and Audio Using GPT 4o

The Pre-AGI Era War: Google Astra vs GPT-4o

The Omniscient GPT-4o + ChatGPT is HERE!

Build ATS Friendly Resume Using Overleaf and ChatGPT for Big 4s

Build a Model to Predict Stock Prices using ChatGPT

How to Build a ML Model in 1 Minute using ChatGPT

How to Create Mind Maps and Flowcharts Using ChatGPT

Applications of ChatGPT

“ChatGPT is a fascinating technology that has the potential to transform the way we communicate with machines.” ~Andrew Ng, Founder of DeepLearning.ai

Applications of ChatGPT in everyday tasks / How ChatGPT enhances productivity in various fields:

• Writing Assistance: ChatGPT is often used to write articles, research papers, and more due to its capabilities of:
  • Brainstorming ideas and generating content for articles, stories, scripts, etc.
  • Drafting and refining text to improve writing quality and clarity
  • Providing feedback and suggestions for revisions
• Education and Tutoring: If you are an educator inclined towards making student life easier, ChatGPT can assist you in developing ideas, lessons, and:
• • Explaining complex topics and providing detailed answers to questions
  • Assisting students with homework, assignments, and exam preparation
  • Offering personalized learning experiences and study tips
• Coding and Software Development: If you are a non-tech professional and want to improve your coding skills, ChatGPT is the best option for you as it eases:
• • Generating code snippets and templates based on natural language descriptions
  • Providing syntax suggestions and optimizing code for efficiency and performance
  • Debugging code by identifying and fixing bugs
• Business and Marketing: Quick and good work is necessary for every employee to stay on top. ChatGPT can be your assistant in creating good marketing campaigns and:
• • Automating email generation for customer service and lead nurturing
  • Ideating and brainstorming for marketing campaigns and content
  • Providing customer support and answering FAQs
• Creative Applications: Creativity opens the door to endless possibilities, allowing individuals to explore new ideas, innovate, and approach problems from fresh perspectives. ChatGPT helps create quirky, witty, and out-of-the-box text; you just need to give a detailed prompt and use the content. It helps in:
• • Writing poetry, stories, scripts, and other creative content
  • Generating ideas for interactive fiction and games
  • Roleplaying as different characters in hypothetical scenarios
• Language Translation: If you want to understand a topic in your native language, ChatGPT can be your go-to tool in:
• • Translating text between multiple languages accurately and efficiently
  • Providing context-specific translations to convey the original meaning
  • Enabling communication between people who speak different languages

ChatGPT’s natural language understanding and generation capabilities make it a versatile tool across many domains. While it can assist with various tasks, it’s essential to use it judiciously and not rely on it entirely, especially for high-stakes applications. Responsible use of AI is critical to realizing its full potential.

Reading List 

How to Improve Dataset Selection with ChatGPT?

15 Ways to Use ChatGPT for SQL

GPT2-chatbot: Is it Better than GPT4 and Claude Opus?

10+ Easy ChatGPT Prompts for Working Professionals in 2024

OpenAI Announces GPT-4 Turbo: Everything you Need to Know

Open AI’s ChatGPT Announced a New Feature: Image Editing

30+ ChatGPT Prompts You Can Use Get the Dream Job in 2024

Top 7 Free ChatGPT Prompt Engineering Courses and Resources

9 ChatGPT Affiliate Marketing Tips to Try

GPT 3.5 vs GPT 4 vs GPT 4 Turbo

The differences between GPT-3.5, GPT-4, and GPT-4 Turbo primarily revolve around their architecture, capabilities, and performance. Here’s a breakdown of each model:

Key differences

• Memory: GPT-4 can remember and process up to 64,000 words, while GPT-3.5 handles up to 8,000 words.
• Input Types: GPT-4 can process text and images, but GPT-3.5 can only process text.
• Availability: GPT-4 and GPT-4 Turbo are available through subscriptions, while GPT-3.5 is free.
• Customization: GPT-4 and GPT-4 Turbo allow fine-tuning for specific tasks, but GPT-3.5 doesn’t.
• Capabilities: GPT-4 has better language understanding, multimodal abilities (text + images), and reliability than GPT-3.5.
• Data-to-Text vs. Text-to-Text: GPT-4 models can generate responses from structured data (data-to-text), while GPT-3.5 only works with text-based inputs and outputs (text-to-text).

GPT-4 and GPT-4 Turbo represent significant advancements over GPT-3.5 in terms of memory capacity, input modalities, safety, customization, and overall performance. However, GPT-3.5 remains a powerful and widely accessible language model.

Model Architecture and Size

• GPT-3.5: This model has around 175 billion parameters. The platform is tailored to everyday workloads and offers the perfect combination of performance and cost efficiency, which applies to many use cases.
• GPT-4: This significantly larger model, estimated at around 1 trillion parameters, has a more advanced architecture that helps it better understand context and response. GPT-4 provides better long-range dependency handling than GPT-3.5, as it can handle up to 64,000 tokens, compared to GPT-3.5’s 8,000 tokens.
• GPT-4 Turbo: This variant is optimized for efficiency, reducing inference time and costs. It is based on a larger context window of 128,000 tokens (allowing full packets as more status inputs) and has been designed to be cheaper than the GPT-4 model.

Capabilities of the Models

• Text and Image Processing: Unlike GPT-3.5, which only handles text, GPT-4 can process both text and images. This makes it more useful for tasks involving understanding visual content and text.
• Response Accuracy and Safety: GPT-4 has better contextual understanding, leading to more accurate responses. It is also 82% less likely than GPT-3.5 to generate inappropriate or disallowed content.
• Plugins and Real-Time Data: GPT-4 can use plugins to access real-time information, a feature not available in GPT-3.5, making its responses more up-to-date and relevant.

User Experience and Cost Effectiveness

• Speed and Cost: While GPT-3. 5 is naturally faster and more cost-effective, GPT-4 delivers a user experience with higher contextual capabilities than ever before. Regarding efficiency and cost, the GPT-4 Turbo is an informed choice, being more advanced than the GPT-3. 5.
• Use Cases: GPT-3. 5 is still used for general computing because it spins more cheaply and quickly. GPT-4 or GPT-4 Turbo, on the other hand, can help both write and understand at a deeper level for more complex tasks such as creative writing, detailed analysis, and interactive applications.

GPT-4 Vs. GPT-4o

Here is the comparison of GPT-4 vs GPT-4o on different metrics:

Feature	GPT-4	GPT-4o
Main Advantage	Versatile and capable across various tasks and languages	Optimized for specific tasks, faster and more efficient
Architecture	Transformer-based, large-scale deep neural network	Optimized Transformer-based, tuned for efficiency
Parameter Size	175 billion parameters	12 billion parameters (15x smaller than GPT-4)
Data Size	Vast dataset (~570 GB) from diverse sources and languages	Curated, smaller dataset (~45 GB) from high-quality sources
Training Method	Self-supervised learning	Semi-supervised learning (mix of self-supervised and supervised)
Optimization	Standard large-scale training	Includes distillation, pruning, and quantization for efficiency
Speed	Standard speed	2x faster than GPT-4
Cost	Higher computational costs	50% cheaper compared to GPT-4
Rate Limits	Standard rate limits	5x higher rate limits compared to GPT-4 Turbo
Performance	Excels at general language tasks, diverse domains	Specialized for domain-specific tasks, accurate and efficient
Use Cases	General text generation, question-answering, summarization	Specific domain applications, reasoning, inference, and analysis
Limitations	Scalability, cost, high energy usage	Task specificity, reduced generalization, data dependencies
Environmental Impact	High carbon footprint due to large resource usage	Lower carbon footprint due to optimization and smaller size
Adaptability	High adaptability to new tasks	Limited flexibility outside optimized domains
Deployment	For diverse, large-scale applications	Optimized for efficiency, speed, and specific applications

• GPT-4 is more extensive and general, excelling across diverse tasks and languages, but it comes with higher computational costs and environmental concerns.
• GPT-4o is a smaller, optimized version of GPT-4, offering faster performance, cost efficiency, and task-specific accuracy, though it may need to be more adaptable outside its specialized domains.

Reading List 

How to Launch Your Online Business Using ChatGPT

10 Best ChatGPT Plugins For Enhancing Productivity

6 Ways on How to Use ChatGPT for Blogging in 2024

How Cooking made easy using ChefGPT?

ChatGPT Can Now Remember Your Style and Preferences

How to use ChatGPT for Excel ?

Common Methods to Jailbreak ChatGPT and Other LLMs

Ultimate List of Generative AI Resources

Top 52+ ChatGPT & Bard Prompts for Affiliate Marketing Success

120 ChatGPT Prompts to Simplify Your Workflow

What is the GPT Store? How to Access It?

ChatGPT for Developers

Getting Started with the ChatGPT API

A step-by-step guide to integrating ChatGPT into applications:

1. Obtain API Key: Sign up at OpenAI and get your API key.
2. Install OpenAI SDK: Use pip or npm to install the OpenAI Python/JavaScript SDK.

!pip install openai

1. Make API Requests: Set up a basic HTTP request to the ChatGPT API using your key.

!pip install openai
from getpass import getpass
OPENAI_KEY = getpass('Enter Open AI API Key: ')
import openai
from IPython.display import HTML, Markdown, display
openai.api_key = openai_key
def get_completion(prompt, model="gpt-3.5-turbo"):
    messages = [{"role": "user", "content": prompt}]
    response = openai.chat.completions.create(
        model=model,
        messages=messages,
        temperature=0.0, # degree of randomness of the model's output
    )
 return response.choices[0].message.content
response = get_completion(prompt='Explain RAG in 2 bullet points', 
                          model='gpt-4o-mini')
display(Markdown(response))

1. Handle Responses: Process the model’s output for use in your application.

Also read: Here’s How You Can Use GPT 4o API for Vision, Text, Image & More.

Customizing the ChatGPT Experience

Adjust model parameters to fine-tune responses:

• Temperature: Controls randomness. Lower values make output more deterministic, while higher values increase creativity.
• Max Tokens: Limits the length of generated responses. This is useful for controlling verbosity.

Automating Tasks with ChatGPT

Using ChatGPT to streamline workflows and automate mundane tasks:

1. Task Automation: Integrate the API with workflows (e.g., customer support, content generation).
2. Chatbots: Develop conversational agents for common queries.
3. Code Assistance: Automate code generation or debugging by asking ChatGPT to generate specific code snippets.

Also read: 120 ChatGPT Prompts to Simplify Your Workflow

ChatGPT vs. other Models

Here, we compare ChatGPT, a widely-used conversational AI, with other prominent models such as BERT, LLaMA, Claude, PaLM 2, MidJourney, and Gemini. Through a detailed examination of their architecture, use cases, and unique features, this comparison highlights the strengths and applications of each model in different AI-driven scenarios.

Comparison	ChatGPT	BERT
Purpose	Designed for generating natural text.	Excels at understanding tasks (e.g., text classification, question answering).
Architecture	Fine-tuned for conversations.	Focuses on understanding context bidirectionally (from both sides of a sentence).
Output	Generates full responses.	Used for tasks requiring fixed-length outputs.

Also read: Perplexity AI vs Chatgpt: Which is a Better Option?

Comparison	ChatGPT	LLaMA
Size and Optimization	Larger models like GPT-3.5 or GPT-4; require more computing power.	Smaller, optimized for specific tasks, more accessible for developers with limited resources.
Use Cases	Suitable for general conversations and creative tasks.	Suited for research and domain-specific tasks.

Also read: Meta Llama 3.1: Latest Open-Source AI Model Takes on GPT-4o mini

Comparison	ChatGPT	Claude (Anthropic)
Ethical Considerations	Focuses on safety but is generalized.	Emphasizes ethical AI use and safety more strictly.
User Control	Allows basic customizations (e.g., temperature adjustments).	Offers more control over AI behavior.

Also read: Claude vs. ChatGPT: Which AI Chatbot is Best for Everyday Tasks?

Comparison	ChatGPT	PaLM 2
Language Support	Supports multiple languages, general-purpose.	Excels in multilingual tasks, especially cross-lingual translations.
Integration	Accessible via OpenAI’s API and across various platforms.	Integrated with Google Cloud services.

Also read: Gemini vs ChatGPT: Which is Better for Coding?

Comparison	ChatGPT	Gemini (Google)
Accuracy	Relies on pre-trained models; may not always be up-to-date.	Emphasizes factual accuracy and real-time search capabilities.
Applications	Versatile for casual conversations and professional tasks.	Tailored for accurate information retrieval.

Also read: Top 30+ ChatGPT Alternatives You Can Try In 2024 (Free and Paid)

Managing Hallucinations in ChatGPT

• Why It Happens: ChatGPT is probabilistic and sometimes creates fake or false information. Even when the model has been trained on a large dataset, it does not have any prior information about facts; in actuality, all this training did was teach the sequence of words that is most likely given its input, which can also be misleading and generate what are called hallucinations from confidence.
• How to Mitigate: Hallucinations Mitigation strategies include:
  • Fine-tuning models on more specific, accurate datasets.
  • Adding user prompts that explicitly ask for clarification or fact-based responses.
  • Implementing retrieval-augmented generation (RAG) to cross-reference real-time information from external databases.

Also read: Top 7 Strategies to Mitigate Hallucinations in LLMs

Fact-Checking with ChatGPT

• Ensuring Accuracy: Developers and users can ensure accuracy by:
  • Cross-Referencing: Pairing ChatGPT with external fact-checking APIs or real-time search engines to verify claims.
  • Prompt Engineering: Ask the model to provide sources or evidence for claims, which can help identify where the model might be uncertain or less reliable.
  • Human-in-the-Loop: Always having a human verify critical or sensitive information generated by the model.

Bias in ChatGPT Responses

• Why It Occurs: ChatGPT can exhibit bias because it is trained on datasets sourced from the internet, which inherently contains biases related to culture, society, gender, and other factors.
• Addressing Bias: Bias can be addressed by:
  • Bias Detection Tools: Implementing tools that flag potential biases in responses.
  • Continuous Fine-Tuning: Training models on more balanced and representative data.
  • User Feedback Loops: Gather feedback from diverse user bases to understand where biases are most prevalent and correct them over time through retraining or updates.

Future of ChatGPT

The future of ChatGPT and GPT models is poised for significant advancements, with key developments expected in areas like multi-modal capabilities, seamless integration with other AI tools, and expanded real-world applications. Here’s a breakdown of what lies ahead:

• Upcoming Developments and Potential Applications:

• More Powerful Models: Future versions like GPT-5 will be larger, smarter, and less prone to errors, making them suitable for critical fields like law, medicine, and research.
• Specialized Applications: Expect industry-specific versions of GPT, tailored for finance, healthcare, education, and customer support, boosting productivity across sectors.
• Customization and Personalization: Users may get tools to fine-tune models to meet personal or business needs, making AI even more flexible and precise.

• Integrating ChatGPT with Other AI Tools:

• Vision Models: Combining ChatGPT with image tools (like DALL-E) could create AI that understands and generates both text and images, revolutionizing media, advertising, and education.
• Voice Assistants: Merging ChatGPT with voice tech could lead to more natural virtual assistants, enhancing smart home devices, customer service, and accessibility.
• Robotics: Integrating GPT with robots could improve human-robot interaction in areas like healthcare (robotic companions), hospitality, and industrial automation.

• Expanding ChatGPT’s Abilities: Beyond Text:

• Multi-modal Models: Future GPT models will go beyond text and images, incorporating inputs like voice and video for more comprehensive AI solutions.
• AI-generated Videos: ChatGPT could assist in creating and editing videos and streamlining work for content creators, marketers, and educators.
• Real-time, Multi-sensory Assistants: Virtual assistants that process text, voice, and video at once could offer richer experiences for education, remote work, and gaming.

These advancements will drive more sophisticated AI applications, pushing boundaries in creativity, problem-solving, and practical use cases across industries.

Learning Resources

Tutorials and Guides for Mastering ChatGPT

• “Mastering ChatGPT: The Ultimate Beginner’s Guide to ChatGPT!” Udemy course – How to master using ChatGPT for various tasks such as writing letters, acing job interviews, creating writing prompts, and more.
• ChatGPT Prompt Engineering for Developers: learn how to use a large language model (LLM) to build new and powerful applications quickly.
• ChatGPT Advanced Data Analysis: Automate tasks in your work and life with ChatGPT Code Interpreter and more.
• ChatGPT Playground for Beginners: Intro to NLP AI: create an AI-powered Health Assistant using the ChatGPT Playground Graphical User Interface, simulating a conversation between a family doctor and a patient. 

Online Communities and Forums for ChatGPT Users

• OpenAI Forum – Official forum for discussions, support, and updates related to ChatGPT and other OpenAI products.

Research Papers and Other Resources

Research Papers and Latest Findings related to ChatGPT

• “Language Models are Few-Shot Learners” by OpenAI – Seminal paper that introduced GPT-3 and the few-shot learning approach.
• “Scaling Laws for Neural Language Models” by OpenAI – Explores the relationship between model size, compute, and performance in language models.
• SearchGPT Prototype – A new way to search
• Fine-tuning now available for GPT-4o: Fine-tune custom versions of GPT-4o to increase performance and accuracy for your applications.
• Introducing GPT-4o and more tools to ChatGPT free users.
• Improvements to data analysis in ChatGPT: Interact with tables and charts and add files directly from Google Drive and Microsoft OneDrive.
• How the voices for ChatGPT were chosen?
• New compliance and administrative tools for ChatGPT Enterprise.

These resources cover many learning materials, from practical tutorials to in-depth research, to help you become proficient in using ChatGPT and stay updated on the latest advancements in large language models and AI. Moreover, you can find more papers here – Link.

Frequently Asked Questions

What kind of tasks can ChatGPT handle well?
Ans. It excels at text generation, summarization, code assistance, and answering complex queries.

Can I train ChatGPT on my data?
Ans. You cannot directly train it, but you can use fine-tuning or Retrieval-Augmented Generation (RAG) methods.

Is ChatGPT safe to use for sensitive data?
Ans. It’s not recommended for handling sensitive or confidential data due to privacy concerns.

Can ChatGPT make a PowerPoint presentation?
Ans. Yes, it can generate text-based slides or provide outlines and content for presentations.

Can ChatGPT make mistakes?
Ans. Yes, it can occasionally produce incorrect or biased information.

ChatGPT and AI course?
Ans. ChatGPT can assist in learning AI topics, including providing explanations and code examples.

Can ChatGPT generate images?
Ans. Not natively, but models like DALL-E can generate images when integrated with ChatGPT.

How does ChatGPT work?
Ans. It uses deep learning, particularly transformer models, to process input, generate responses, and maintain context.

How does ChatGPT work in Excel?
Ans. It can help write and explain formulas, clean data, and automate tasks using Excel functions or macros.

How does ChatGPT work, the model behind the bot?
Ans. It’s based on the GPT architecture, using transformers and extensive pretraining on large text corpora.

How does ChatGPT work technically for beginners?
Ans. ChatGPT predicts the next word in a sequence by analyzing patterns in vast amounts of text data.

Can ChatGPT make a PowerPoint presentation?
Ans. Yes, it can outline and suggest presentation content, but manual design work is needed.

Can ChatGPT make a website?
Ans. It can generate code for simple websites and guide structure and features.

Can ChatGPT make animated videos?
Ans. It can’t create videos directly but can help write scripts or provide suggestions for animations.

Can ChatGPT make a balance sheet?
Ans. Yes, it can assist in creating balance sheets by generating the necessary formulas and layouts.

Which ChatGPT app is best?
Ans. The official ChatGPT app by OpenAI provides the most comprehensive and up-to-date features.

Which ChatGPT app is best for Android?
Ans. The official OpenAI ChatGPT app for Android is the most reliable option.

Which ChatGPT can create images?
Ans. When integrated with DALL-E, ChatGPT can generate images based on text prompts.

Can ChatGPT make images?
Ans. It can assist with image generation tools like DALL-E, but not directly.