The first chatbot emerged in the 1960s and by the late 2000s they were being commercialized. However it’s only recently with the rise of ChatGPT that chatbots have gained widespread popularity. Chatbot Vs ChatGPt which is best? Despite this success ChatGPT isn’t the right tool for every business application. If you’re looking to integrate a conversational AI into your business and want to understand the key differences between general chatbots and ChatGPT here’s what you need to know:
What is a chatbot?
A chatbot is a software designed to simulate conversations with users, offering quick responses without human involvement. They’re versatile and used across various industries. There are three main types:
Rule-based chatbots:
These follow set rules and can’t learn or generate original responses. They rely entirely on predefined templates.
AI chatbots:
They use machine learning to select the best response from a limited set of predefined templates. They’re often specialized in specific areas but struggle with queries outside their domain.
Generative chatbots:
These, like ChatGPT can generate responses from a vast range of data, making them more versatile but less specialized in specific topics.
How does a chatbot work?
Receiving Input: The chatbot first gets a message or command from the user, either through text or voice.
Processing Input:
- Tokenization: The chatbot breaks down the input into smaller units, like words. For example, “How are you?” becomes “How,” “are,” “you,” and “?”.
- Intent Understanding: Using natural language processing (NLP) and natural language understanding (NLU), the chatbot figures out what the user wants. Is it a question, a request, or an emotional statement?
- Entity Recognition: The chatbot identifies important pieces of information in the input, such as names, locations, or dates. For instance, in the sentence “Book a ticket to Paris,” “Paris” is recognized as the destination.
Determining the Response:
- Rule-based Chatbots: These bots follow a set of predefined rules and search their knowledge base for the best-matching answer to the user’s input.
- Intelligent Chatbots: These use AI, like machine learning, to analyze the user’s input and infer their intent, even if there isn’t an exact match in the knowledge base.
Returning the Response: Once the chatbot has processed the input and determined the most appropriate response, it sends this answer back to the user.
What's ChatGPT?
ChatGPT is a chatbot that uses AI to generate responses based on the information it’s been trained on. Instead of just picking from pre-set answers, it can create unique, human-like replies for each conversation. It learns from vast amounts of data to provide intelligent, context-aware responses.
How does ChatGPT work?
ChatGPT is a powerful AI model based on the GPT (Generative Pre-trained Transformer) architecture, specifically its third version. It’s trained on an enormous amount of text—hundreds of billions of words—to learn how language works.
Here’s a simple breakdown of how ChatGPT functions:
It generates text: ChatGPT can create sentences and paragraphs that flow logically and make sense in response to your input.
Training: It’s initially pre-trained on a huge variety of texts, which helps it learn the basics of language. Afterward, it’s fine-tuned for specific tasks to improve its responses.
Uses the Transformer architecture: This is the technical framework behind ChatGPT. For example, if you ask, “What are some traditional dishes in Italy?” ChatGPT goes through these steps:
- Tokenization: It breaks down your input into smaller pieces (tokens), such as words or parts of words.
- Embedding and encoding: Each word is converted into a numerical value, and its position in the sentence is recorded so ChatGPT understands the order of words.
- Assigns weights to words: It prioritizes certain words in the sentence. For example, in “Give me a recommendation,” the word “recommendation” is more important than “give.”
- Context understanding: ChatGPT uses multiple layers of Transformer blocks to grasp the meaning. It recognizes patterns like “traditional dishes in Italy” and understands you want food suggestions.
- Response generation: It then crafts a response, using both the context from your question and what it’s learned from its training. For example, it knows that dishes like pizza and pasta are associated with Italy.
In essence, ChatGPT breaks down your input, figures out what you’re asking, and provides a coherent answer based on patterns it has learned from vast amounts of text.
What are the differences between chatbot vs ChatGPT?
1. Architecture and Design
- Rule-based chatbots: These are built on a simple design. They rely on a database of predefined answers and use keywords to match user inputs with a fixed response. It’s a bit like a “choose your own adventure” where everything is scripted in advance.
- AI chatbots: These are powered by machine learning models and generate responses based on the data they’re trained on. However, their answers are restricted to their training data, which means they might be good in specific areas but limited in flexibility.
- ChatGPT: This is a much more advanced system, based on the Transformer architecture. Instead of sticking to templates or predefined answers, it generates entirely new responses by identifying patterns from massive datasets, making it capable of more dynamic and varied conversations.
2. Flexibility
- Rule-based chatbots: Extremely limited. They can only provide answers to questions they’ve been pre-programmed to handle. If you ask something outside of their scope, you’ll get no useful response.
- AI chatbots: These are more flexible than rule-based ones. They can generate slightly varied responses but are still limited by the specific data they’ve been trained on.
- ChatGPT: Incredibly flexible. It can generate responses to a huge range of topics because it doesn’t rely on fixed answers or templates. It adapts based on context and user input, making it far more capable in varied conversations.
3. Training
- Rule-based chatbots: No real “training” here—just predefined rules and answers. Think of it as a fixed script that the chatbot sticks to.
- AI chatbots: These are trained on specific datasets relevant to their purpose, like answering questions in a particular field. They might need fine-tuning to perform better in that domain, but they struggle with queries outside their expertise.
- ChatGPT: This model has been trained on vast, diverse datasets. It doesn’t just learn specific topics—it generalizes across many subjects, which allows it to have a broad understanding and answer questions on a wide variety of topics.
4. Conversational Depth
- Rule-based chatbots: Shallow conversations. They can only deliver canned responses or guide users through a few predefined options. If the conversation needs to go deeper, they may connect you to a human agent or fail entirely.
- AI chatbots: These provide more depth, but only within the limits of the data they’ve been trained on. For example, if trained on dog-related topics, they can answer well about dogs but might be clueless about other animals.
- ChatGPT: Offers much more conversational depth. It can take complex or open-ended questions, connect multiple ideas, and generate coherent, meaningful responses, often bridging topics together in ways traditional AI chatbots can’t.
Personalization in Chatbots, Explained:
Rule-based chatbots: These are like decision trees—they can only follow preset paths based on your inputs. Personalization is limited because they stick to a fixed script. You might get different options depending on your choices, but it’s still pretty basic.
AI chatbots: These are a bit smarter. They can give you personalized suggestions, but only in the specific area they’re trained in. For example, a music chatbot might suggest songs or genres based on your taste, but its personalization is limited to music.
ChatGPT: This takes personalization to the next level. If you tell it you like noir films, it can make connections beyond just movies—like recommending noir-inspired music. It’s more flexible and creative, able to link ideas across different topics based on what you’ve told it.
How to pick between an AI chatbot and a generative chatbot?
To decide between an AI chatbot and a generative chatbot, you should choose a generative AI chatbot if:
- You need your chatbot to give customized, unique responses that adapt to each specific question or input, rather than repeating standard answers.
- Your use case would benefit from creative, human-like conversations that feel more natural and engaging, rather than rigid, pre-programmed responses.
- You have the technical ability and resources to support and manage the complex infrastructure needed to run a powerful generative AI system.
- You are prepared to deal with the higher costs that come with using advanced AI models, especially when it comes to maintaining and scaling them.
- You’re ready to collect user feedback and continuously tweak and improve the chatbot’s performance based on that input, ensuring it keeps learning and getting better over time.
How to create your own GPT chatbot?
To create your own GPT chatbot without spending a lot upfront, you can use the ChatGPT API and build it on your computer. Here’s how you can do it:
Install Python: First, you’ll need Python on your computer, which is a programming language. Download and install it for either Windows, macOS, or Linux.
Check Python Version: After installation, open your terminal (Command Prompt on Windows or Terminal on macOS/Linux) and run
python --version(orpython3 --versionfor macOS/Linux) to make sure Python is correctly installed.Upgrade Pip: Pip is a package manager for Python, which you’ll need to install extra tools. Run this command to upgrade it:
- For Windows:
python -m pip install -U pip - For macOS/Linux:
python3 -m pip install -U pip
- For Windows:
Install OpenAI Library: This library allows your chatbot to connect to OpenAI’s servers. In the terminal, type:
- Windows:
pip install openai - macOS/Linux:
pip3 install openai
- Windows:
Install Gradio: Gradio is a tool to create a simple web interface for your chatbot. Install it by typing:
- Windows:
pip install gradio - macOS/Linux:
pip3 install gradio
- Windows:
Download Sublime Text: This is a text editor where you’ll write your chatbot’s code. Install it from the Sublime Text website.
Get Your OpenAI API Key: Go to OpenAI’s website, create an account, and get your API key. This key allows your chatbot to use OpenAI’s GPT model. Save this key as you’ll need it for the next step.
Write the Code: Open Sublime Text and paste the following code. Replace
"Your API key"with the actual key you got from OpenAI:
9.Save the Code: Save the file with a .py extension (for example, chatbot.py) on your desktop.
10. Run the Code: Go to the file location, right-click (on Windows) and select “Copy as Path,” or just copy the file path (on macOS/Linux). In your terminal, type python (Windows) or python3 (macOS/Linux), then paste the file path and hit Enter.
11. Access the Chatbot: After running the code, the terminal will display a local URL (a link). Copy and paste that link into your browser to start chatting with your new GPT-powered bot!