ChatGPT-3.5 and ChatGPT-4 are both natural language processing (NLP) models developed by OpenAI, but there are some key differences between the two that software developers should be aware of. Let's demonstrate how these differences affect the data processing and output generated by these models on specific examples.
GPT-4 vs GPT-3.5-turbo: the key differences
While GPT-3.5 is a text-to-text model, GPT-4 is more of a data-to-text model. This means that GPT-4 can process more than just text inputs which makes it more suitable for complex tasks. Here are the key differences between the two models:
Model Advancement: GPT-4 is significantly more advanced than GPT-3.5, with a 10 times improvement. This allows it to better understand context and distinguish nuances, leading to more accurate and coherent responses.
Token Limit Increase: GPT-4 has a maximum token limit of 32,000, a substantial increase from GPT-3.5's 4,000 tokens.
Handling of Longer Conversations: GPT-4 can manage longer prompts and conversations than GPT-3.5, making it more suitable for complex dialog systems.
Model Size Comparison: GPT-4, rumored to have 1 trillion parameters, is significantly larger than GPT-3.5, which has 175 billion parameters. This allows GPT-4 to generate more accurate responses.
Contextual Understanding Capability: GPT-4 can answer complex questions by synthesizing information from multiple sources, whereas GPT-3.5 may struggle to connect the dots.
Linguistic Capabilities: GPT-4 can generate more sophisticated and nuanced language than GPT-3.5, making it a more powerful tool for text generation.
Accuracy of Responses: GPT-4 is 82% less likely to respond to requests for disallowed content and 40% more likely to produce factual responses than GPT-3.5, according to internal evaluations.
Multimodal Input Handling: GPT-4 can handle both text and images, while GPT-3.5 is a text-to-text model, making GPT-4 more versatile in tasks requiring comprehension of longer documents or mixed text and image data.
Cost Comparison: GPT-4 is available through the OpenAI website as part of its ChatGPT Plus subscription, which costs $20 a month, while GPT-3.5 is free to use.
GPT-4 vs GPT-3.5-turbo: A Comparison of outputs
To compare the capabilities of the GPT-4 and GPT-3.5-turbo models, we'll examine their outputs when generating Class Diagrams and Entity Relationship Diagrams using notation of Gleek, the diagramming tool for developers.
Example 1: Generating Class Diagrams
When asked to show a sample online ecommerce website admin panel process, GPT-4 generates a detailed diagram that includes four classes which are then related via inheritance and implementation relationships. The diagram generated by GPT-4 gives a concrete and detailed visual representation of the online eCommerce website admin panel process.
Request: Show me a sample online e-commerce website admin panel process
Response GPT-4:
Classes (abstract/service/interface/none)
ClassAdminPanel:abstract
+Username
+Password
+Login()
ClassProduct
+ProductID
+ProductName
+Price
+AddProduct()
+UpdateProduct()
+DeleteProduct()
ClassOrder:service
+OrderID
+CustomerID
+OrderStatus
+ProcessOrder()
ClassCustomer
+CustomerID
+CustomerName
+AddCustomer()
+UpdateCustomer()
+DeleteCustomer()
Relationships
ClassAdminPanel-contains-ClassProduct
ClassAdminPanel-contains-ClassOrder
ClassAdminPanel-contains-ClassCustomer
ClassOrder {1}-has-{1..n} ClassProduct
ClassAdminPanel--*>ClassProduct (inheritance)
ClassProduct-.-*>ClassOrder (implementation)
After minor syntax changes (underlined), the generated diagram is following:
On the other hand, GPT-3.5 was not able to generate a diagram with samples but provided a general idea of what an eCommerce website admin panel process might look like. Instead of a detailed diagram, it describes the key components of the process, including managing products, orders, customers, payments, and integrating with payment gateways and shipping providers.
Response GPT-3.5-turbo:
Sorry, as an AI language model, I am not able to show you a sample online ecommerce website admin panel process.
However, I can provide you with a general idea of what an ecommerce website admin panel process might include.
An ecommerce website admin panel process typically involves managing products, orders, customers, and payments.
The admin panel may include features such as adding/editing products, managing inventory, processing orders, managing customer accounts, and generating reports.
The process may also involve integrating with payment gateways and shipping providers.
Example 2: Generating Entity Relationship Diagrams
When asked to show a company management system, GPT-4 generates a comprehensive diagram that outlines the entities involved in such a system (along with their respective attributes and relationships), respectively: Company, Employee, Department, and Project. The diagram generated by GPT-4 is highly detailed and provides a clear visual representation of the system.
Request: Show me a company management system
Response GPT-4:
Company
String id
String name
String address
String industry
Company {1}-contains-{1..n} Employee
Company {1}-has-{1..n} Department
Company {1}-undertakes-{1..n} Project
Employee
String id
String firstName
String lastName
String email
String phone
String position
String department
String salary
String startDate
String endDate
Employee {1}-memberOf-{1} Department
Employee {1..n}-participatesIn-{1..n} Project
Department
String id
String name
Department {1}-managedBy-{1} Employee (manager)
Department {1}-includes-{1..n} Employee
Project
String id
String name
String description
String startDate
String endDate
String status
Project {1}-involves-{1..n} Employee (teamMembers)
After minor changes (we removed the underlined), this diagram was provided by Gleek:
In contrast, GPT-3.5-turbo generates a much simpler diagram that includes only the entities and their attributes, without specifying their relationships. The diagram generated by GPT-3.5-turbo requires a significant amount of syntax changes to produce a legible visualization.
Response GPT-3.5-turbo:
EntityOne: Company
Datatype id
Datatype name
Datatype address
Datatype industry
EntityOne {1}-relationDescription-{1..n} EntityTwo
EntityTwo: Employee
Datatype id
Datatype firstName
Datatype lastName
Datatype email
Datatype phone
Datatype position
Datatype department
Datatype salary
Datatype startDate
Datatype endDate
EntityTwo: Department
Datatype id
Datatype name
EntityTwo {1}-relationDescription-{1} EntityTwo
EntityTwo: Project
Datatype id
Datatype name
Datatype description
Datatype startDate
Datatype endDate
Datatype status
EntityTwo {1}-relationDescription-{1..n} EntityTwo
After quite a lot syntax changes (underlined), outputted diagram was:
Overall, the comparison between GPT-4 and GPT-3.5-turbo shows that while both models are capable of generating diagrams, GPT-4 provides more detailed and comprehensive outputs compared to GPT-3.5-turbo. As the technology continues to advance, we can expect that future iterations of AI language processing models will continue to improve in generating high-quality visual representations of complex processes.
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