What Are OpenAI Codex and GPT 3.5-Turbo: Benefits, and Use Cases For 2023
Artificial intelligence (AI) enabled coding tools have become a huge success in recent years, and with the release of tools like OpenAI Codex software developers can expect a huge increase in their capacity to take on more complex projects.
OpenAI Codex was released in 2021 and quickly became a game changer for programmers, coders, and developers. Since then, tons of similar tools have hit the market, leaving software developers spoiled for choice.
While OpenAI Codex was deprecated in March 2023, developers were not left empty-handed. The creators of OpenAI Codex made sure to create a better, more advanced tool called GPT 3.5-Turbo. While not everyone is happy about dropped support for Codex, GPT 3.5-Turbo does have promising possibilities linked to it!
At Aloa, we are always staying ahead of the trends when it comes to software development. Exploring the best tools and solutions has become part of our mission, improving our network with resources that add value and usability to their goals.
In this blog, we'll dive deeper into what OpenAI Codex is, why it was deprecated. We will also compare OpenAI Codex to its successor, GPT 3.5 Turbo. Finally, we’ll go into detail about the benefits of AI-enabled coding tools, some use cases, and how they change the software development landscape.
Let's get started!
What Is OpenAI Codex?
OpenAI Codex is a powerful AI model developed by OpenAI, designed specifically for programming tasks. It is an advanced version of the Generative Pre-trained Transformer (GPT) model, widely used for natural language processing tasks.
The OpenAI Codex takes the capabilities of GPT to the next level by providing developers with a tool that can understand and generate code in various programming languages. Codex has been pre-trained on vast code and text data, including public code repositories, documentation, and programming forums.
However, it is essential to remember that Codex no longer receives developers' support. Codex users are encouraged to start using GPT-3.5 Turbo, a more advanced version trained to assist in creating for the same purpose as Codex but with better capabilities.
What is GPT-3.5 Turbo?
GPT-3.5 Turbo is the successor of OpenAI Codex, with the former released in 2023 as an advancement in programming AI. It's a more sophisticated version than its predecessor, offering better accuracy and faster processing times for code-generation tasks. GPT-3.5 Turbo has been specifically designed for various use cases, including natural language processing and machine learning.
Because OpenAI Codex was deprecated by its developers, it no longer receives update support. So users are highly encouraged to switch over to GPT-3.5 Turbo for their coding projects. However, GPT 3.5- Turbo is not your only option when it comes to software development coding tools.
Though highly intuitive, GPT 3.5-Turbo is not your only option when it comes to software development coding tools. The market is full of other options, each with its own unique advantages.
- Snips Code AI, which has been used for language translation and visual development tasks; Kite, which offers powerful auto-completion capabilities
- Atomist is designed to provide developers with an automated code assistant.
Each of these tools offers similar results as GPT 3.5, making it easier to generate basic code snippets and providing helpful tips for developers. With that in mind, Codex and GPT 3.5-Turbo can be leveraged to unlock the potential for developers in 2023 by providing tools and support to help them create better code faster.
How To Use OpenAI Codex vs. How To Use GPT 3.5-Turbo
Codex and GPT 3.5- Turbo function similarly, with the latter providing better accuracy and speed. When using either, developers must provide context to the AI model with a code snippet or query. The difference lies primarily in their ability to detect errors and suggest corrections.
Codex will only suggest corrections, while GPT 3.5- Turbo can automatically detect and fix potential errors in code.
You can apply the same steps to using OpenAI Codex as with GPT 3.5-Turbo, so you don't need to go above and beyond when making the switch. Following a few simple steps, developers can use either tool with ease:
To get the most out of OpenAI Codex or GPT 3.5-Turbo, developers should:
- Familiarize themselves with the capabilities and limitations of the model.
- Experiment with different prompts and code snippets to discover the best ways to interact with the model.
- Integrate Codex into their development workflow, using the API to access the model from their preferred development environment.
Once you've familiarized yourself with these elements, you can then follow the 3 step process to start using OpenAI Codex for your development project:
Step 1: Use precise descriptions.
Codex and GPT 3.5 Turbo can generate numerous types of code based on what you're after. However, you must precisely describe what you're after for the best results. Using generalized instructions often leads to codes that do not apply to the task. When you provide descriptions, it's essential to provide as many details as possible. This will allow the code generator to give you more accurate results.
When you provide descriptions, it's essential to provide as many details as possible to produce quality code that you can use for your intended purposes. The best way to go about drafting your instruction is to include phrases that specify:
- The type of language you are after
- The datasets it needs to source
- The kind of software or output you are developing
You can also include additional instructions revolving around actionable terms such as:
These are just examples, so draft your instructions based on your needs. A completed example may look like this:
#Write a node.js script that can scrape a website, chop it up into relevant chunks, and put them in an array.
Here's a quick screenshot of the example above:
Properly stringing together actionable and instructive prompts will help you get the best results.
Step 2: Use examples to guide the model into getting the results you're after.
Aside from using a highly specific set of instructions to guide the AI model, providing examples further increases the likelihood of generating high-quality code that meets your needs.
Examples can be data sets, code snippets, or other input forms related to what you're trying to do.
This gives the code generator a better understanding of what kind of output you're after, allowing it to learn from your examples and produce more accurate results. You can also explore forums and community discussions like GitHub, Stack Overflow, or Reddit to understand better the kind of inputs Codex needs to generate the best results.
When teaching your AI model how to generate the right stuff, having a library of learning resources at your disposal makes it easier for you to streamline code development.
Step 3: Use contextual information and conversational history.
Once you've provided the model with the necessary instructions, don't forget to refine your results. Codex and GPT 3.5-Turbo are designed to learn from their mistakes, so refining your results will help them improve and become more accurate over time.
Using contextual information such as data structures, functions, and variables to guide the model is one of the best ways to refine your results. Additionally, applying conversational history in the form of feedback, comments, and updates makes it easier for code generators to understand more about a project, allowing them to generate better code.
You can also use a combination of automated testing and manual review techniques to ensure that only quality code is generated. Doing so enables you to iterate quickly and produce better results in the long run.
OpenAI Codex vs. GPT 3.5-Turbo Features
OpenAI Codex and GPT 3.5-Turbo come with numerous features that enhance the ability of developers, programmers, and coders to accomplish their tasks productively.
Let's go through each feature in more detail:
OpenAI Codex vs. GTP 3.5-Turbo Code Generation
Open AI Codex includes the ability to generate code in any language. It also includes the ability to auto-complete, conduct syntax checking, and detect errors. It also supports an AI editor with syntax highlighting for various languages.
On the other hand, GPT 3.5-Turbo's features include more advanced auto-complete and syntax-checking capabilities, error correction, code generation in any language, natural language processing (NLP) support, and a Visual Development Environment (VDE). It also has the ability to generate entire classes of code with the help of AI.
OpenAI Codex can generate code documentation, including comments, function descriptions, and API documentation. This can help developers maintain well-documented codebases and improve their projects' overall readability and maintainability.
With GPT 3.5-Turbo, users can leverage an AI-powered auto-documentation tool to generate code documentation and comment blocks automatically. This feature is useful for quickly adding comments and helping developers keep their projects up to date with the latest standards.
Error Detection and Debugging
OpenAI Codex can assist developers in detecting errors in their code and suggesting potential fixes. By leveraging the model's understanding of programming languages and best practices, developers can quickly identify and resolve issues in their code.
GPT 3.5-Turbo enhances Codex's error detection capabilities with an AI-powered debugger. This tool can detect, locate, and fix errors in code to save developers time and effort.
Code Review and Analysis
Developers can use Codex and GPT 3.5-Turbo to review and analyze their code, identifying areas for improvement and potential optimizations. This can help ensure the code is efficient, maintainable, and adheres to best practices.
With GPT 3.5-Turbo, code review, and analysis is improved by an AI-powered code test platform. This tool can detect errors, suggest improvements, and provide feedback on coding performance.
OpenAI Codex and GPT 3.5-Turbo both offer powerful coding tools that help developers create better code faster while improving accuracy and speed. As AI technology continues to improve in the coming years, these tools will become increasingly important for developers in 2023 and beyond.
However, GPT 3.5-Turbo does extend the capabilities of Codex by offering more advanced features. It also can generate entire classes of code with the help of AI. With their range of features, users can dramatically reduce the amount of time spent in development cycles while improving accuracy and speed.
Benefits Of OpenAI Codex and GPT 3.5-Turbo For Software Development
Traditionally, coding often takes up hours upon hours of time to create, refine, and optimize. Because of that, programmers and software developers often need to set long project deadlines to accommodate client goals in relation to developer
In using OpenAI Codex or GPT 3.5-Turbo, developers not only decrease the time it takes to create a working code, but they are also able to reap more benefits like:
Increase Capacity and Productivity
Using code-generating tools like Codex and Turbo exponentially increases your capacity to produce high-quality, usable codes that can be used for a variety of applications. This means that you'll be able to take on more projects and increase your productivity without compromising quality.
Additionally, the model-based learning technology behind such technology enables it to quickly produce accurate, high-quality code with minimal supervision from developers. This reduces the likelihood of errors and bugs popping up in your code.
Enhanced Ability to Spot Errors and Debug
In the event there are bugs or errors in your code, OpenAI Codex and GPT 3.5-Turbo provide built-in tools to help you quickly detect and solve coding errors that plague all development projects. With that, developers can eliminate hours of tedious tasks best spent on outputs that require human intervention to complete.
Using the AI model's deep learning technology, it can figure out why a particular function or set of data isn't working as expected and provide suggestions on how to best fix them. This helps developers save time and also makes it easier to spot errors before they become bigger problems.
Enable Knowledge Building and Upskilling
Codex and Turbo both allow developers to explore new technologies and build on their existing knowledge without having to start from scratch. This makes it easier for experienced developers to expand their skill sets while at the same time introducing newcomers to coding basics in an easy-to-understand way.
Break Into New Industries
Since Codex and Turbo can be used to learn new coding skills, developers can start to break into new industries with greater ease. Whether you're looking to venture into software engineering or even machine learning, AI-powered code generators are a comprehensive tool that makes it easier for developers to get up and running quickly.
Increase Earning Potential (Whether Freelancer, Agency, or Business)
Once you are able to break into new industries, it becomes easier to offer your potential clients more services. With the help of AI-powered coding, developers can accomplish tasks faster and provide their clients with quality code in a shorter turnaround time. This opens the door for better opportunities, higher earning potential, and even larger projects.
Precautions To Take When Using AI Code Generating Software
While the capabilities and potential of AI code-generating software are impressive by far, it still has a long way to go if it wants to be the go-to option for coders and programmers. With that said, make sure to keep in mind these precautions when using Codex to support your development needs.
AI Code Generating Software is best used as support, not your end-all-be-all solution.
Like a handful of other AI code generators, Codex and Turbo use machine learning and deep learning to generate output. The output is based on pre-existing code and can be used to supplement your own programming work. You'll still need to debug the generated code, clean it up and make sure that the output is valid within your project's framework.
Codex and Turbo are not programmers. And it's also not going to take your job (if you're a programmer). Coding is just part of what programmers do. Developers of these tools observe that in their current state, Codex and Turbo may somewhat reduce the cost of producing software by increasing programmer productivity, but it won't replace the other tasks that software developers regularly do, such as conferring with colleagues, writing, designing specifications, and upgrading existing software stacks.
Mistaking these tools for a programmer can also lead to "over-reliance," where a programmer blindly approves any code generated by the model without revising it. Given the obvious and subtle mistakes AI generators can make, overlooking this threat can entail quality and security risks. "Human oversight and vigilance are required for safe use of code generation systems like Codex," OpenAI's researchers warn in their paper.
Generating Code is not understanding code.
The ability of AI coders to generate or complete lines of code may be impressive, but it doesn't mean it understands what that code is for. With that in mind, be wary of generated codes that have nothing to do with what you are trying to create.
There have been cases wherein the tool will generate unrelated or irrelevant output because it assumes so based on your patterns and its understanding of your patterns.
Always follow responsible coding practices.
OpenAI Codex and Turbo are chock-full of datasets and information, not all of them meant for public use. In some cases, data scavengers or malicious hackers have been able to "trick" the software into generating code that contains sensitive or private information. It is advised to not use such software on such data and always stick to responsible coding practices when using the tool.
OpenAI Codex and GPT 3.5-Turbo have made strides in helping developers become more productive and efficient with their coding tasks, but it's important to remember that it is only a tool and should never replace cautious coding practices.
No Free Lunch
The "No Free Lunch" Theorem states that when searching for a solution to an optimization problem, no algorithm performs best on every possible class of input. Practically, this means you have to be aware of the limitations and boundaries of OpenAI Codex and GPT 3.5-Turbo and use them responsibly.
You can't expect it to solve all your problems – in some cases, manual coding will still be necessary. In the case of these tools, using specific instructions and datasets will help you get the best out of it – but only if you use proper instructive phrases. However, generalized instructions will come at a cost by yielding lower-quality code that may or may not be useful in your project.
At the end of the day, OpenAI Codex and GPT 3.5-Turbo can help you boost your programming efficiency, but it's important to remember that it still requires human intervention and oversight for use in production environments.
A developer will always have a place at the table – now more than ever! So don't forget to brush up on your coding skills and make use of OpenAI Codex and GPT 3.5 Turbo to reach new heights of productivity.
The potential for developers in 2023 is vast, and with AI code-generating software, we have only just begun to unlock it. With its vast datasets and deep learning abilities, Codex and Turbo can help developers become more productive and efficient with their coding tasks.
However, it is important to remember that human oversight and vigilance are required to use code generation systems safely. Also, applying its capabilities to suit your needs and goals as a business means working with experts to make sure you get the best out of it.
If you're ready to take advantage of OpenAI Codex's and GPT-3.5 Turbo's capabilities, reach out to Aloa and see how you can apply this new technology to create productive and insightful software that supports your growth and development as a business!