The Bridge Between Human and Machine: GPT's Language Decipherer

The Bridge Between Human and Machine: GPT’s Language Decipherer

ChatGPT has taken the world by storm, dazzling people with its human-like conversational abilities. But even as powerful as it is, it has limitations. While ChatGPT can proffer solutions to complex problems, it can’t actively implement them. Code Interpreter is OpenAI’s attempt to evolve ChatGPT from simply being an idea generator to an AI agent that can implement ideas to solve a problem.

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The implications of these new capabilities are profound. Here’s what you should know about the ChatGPT Code Interpreter feature and why it is so important.

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What Is ChatGPT’s Code Interpreter?

Code Interpreter, at its core, is a sandboxed Python programming environment within ChatGPT where you can perform a wide range of tasks by executing Python code. Unfortunately, because of being associated with coding or programming, it is often overlooked or misunderstood by many users. Although it is called “Code Interpreter” and utilizes the Python programming language to perform tasks, it isn’t a feature exclusive to people with programming skills. Sure, some programming skills could help you better utilize the feature, but you don’t need any coding experience to use it.

To better understand what the Code Interpreter feature does, it’s better to look at it from an operational perspective.

Before the Code Interpreter feature or any other ChatGPT plugin was added to ChatGPT, whichever problem you wanted ChatGPT to solve had to be one whose solution could be represented with text. Do you need ChatGPT to explain the meaning of generative AI ? Well, that’s something that can be solved by text generation. How about using ChatGPT to translate a text into another language ? That can be solved by text generation as well. In these problems, the solution can be provided as text.

But what if you want to solve a problem like generating a complex graph, editing an image, or grabbing a color value from an image? These are problems whose solutions you can’t represent as text—they require specific solutions. Without plugins like Code Interpreter, the best ChatGPT can do for you is describe how you’d do it. However, the Code Interpreter is like an under-the-hood tool that takes ChatGPT’s description of how you’d solve a problem and implement it using Python code. But how does this work?

How Does ChatGPT’s Code Interpreter Work?

Code Interpreter combines the power of a large language model with the power of Python programming to allow ChatGPT to be much more than just a text generator. These two components are vital to understanding how the Code Interpreter feature works. So, say, you want ChatGPT to split an image into two equal parts and invert the colors on one of the parts before adding them together to make a new image. How would ChatGPT pull that off?

Here’s how it would probably play out. Leveraging its GPT language model, ChatGPT will have an idea of how to solve this problem, and in this particular case, with Python programming. So, what ChatGPT does will be to write a Python script that will be able to split an image into two equal parts and invert the colors of one of the parts before adding them together to make a new one–you know, just as the user requested.

Now, since the Code Interpreter is a Python programming environment capable of running Python code, ChatGPT feeds the Python script that it generates into the Code Interpreter. After executing the Python script, it returns the resulting image to ChatGPT. Problem solved. It is akin to having a programmer write you a program to solve every problem you describe in real-time.

Why Is the Code Interpreter so Important?

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While the announcement of the release of the Code Interpreter feature did not create as much buzz as befitting its potential impact, it could be the single most important feature of the ChatGPT ecosystem in the long run, besides the underlying model itself. It is that important.

Although its current capabilities do not reflect its true potential, the Code Interpreter feature, or at least its operational model, will likely be the future of the ChatGPT AI chatbot. How so?

Current iterations of large language models , including the GPT-3.5 and GPT-4 models that power ChatGPT, are fundamentally limited. As we said earlier, they can describe how to solve a problem, but their ability to put the steps they suggest into practice is severely limited. This is why LLM-powered AI chatbots haven’t yet morphed into true AI assistants.

To paint a clearer picture, take Google Assistant as an example. You can ask Google Assistant to make a call, send a text message, or maybe even book an appointment with your dentist. Unlike the current chatbot models, Google Assistant will not just tell you how to do stuff; it can actually do stuff.

Google Assistant might not be a perfect example, but it is a microcosm of how current iterations of the ChatGPT chatbot could evolve thanks to the Code Interpreter feature. You’d be able to tell ChatGPT to extract images of all the cats in a video file and send them to your email address. Or maybe crawl Twitter and retrieve all the tweets that mention you. Or just about anything you can think of which can be done programmatically, and ChatGPT will fire up the Code Interpreter and write a program that performs that task, executes it, and returns the results in a matter of seconds. This ability of ChatGPT to produce real-world outcomes through Code Interpreter is what makes the feature so important.

While it’s impossible to accurately predict the trajectory of technology, it’s easy to imagine other AI companies like Google adopting similar interpreter models for their AI chatbots. Similar Code Interpreters implemented on other major AI chatbots may be the catalyst that makes AI chatbots a more practical and ubiquitous tool.

A Model for AI Chatbots

ChatGPT’s Code Interpreter ushers in a new paradigm for AI chatbots. By adding the ability to actively interpret instructions, write code, and execute programs, OpenAI has given ChatGPT the ability to produce real-world outcomes through conversation alone. This is a practical model that other AI chatbots can adopt to move beyond being information providers to being AI assistants capable of taking action.

Without a doubt, the Code Interpreter model is a pivotal development that will make ChatGPT and other AI chatbots that adopt a similar model far more capable and useful.