Unleashing GPT-4: Can It Code a Complete Game from Scratch?

Unleashing GPT-4: Can It Code a Complete Game from Scratch?

Table of Contents:

1. Introduction to GPT-4
2. Testing GPT-4 on Chat GPT
3. Observations about GPT-4
4. Describing the Color Match Game
5. Pros and Cons of GPT-4's Game Coding Ability
6. Creating a Paragraph-to-Text Reader Webpage
7. Highlighting Each Sentence in the Text Reader
8. Limitations of Text-to-Speech Highlighting
9. Generating Images with DALL-E Based on a Prompt
10. Mid-Journey's Image Results and Upcoming Features

GPT-4: The Next Generation Language Model

GPT-4, the latest release from OpenAI, is making waves in the world of artificial intelligence. In a recent live stream and blog post, OpenAI showcased the capabilities of GPT-4, leaving many excited and eager to try it out. In this article, we will explore the new features of GPT-4 and its potential applications. From coding games to creating webpages, GPT-4 promises to be a powerful tool for developers and content Creators. Let's dive in and see what GPT-4 has to offer.

Testing GPT-4 on Chat GPT

As an early user of GPT-4, I had the opportunity to test its capabilities on Chat GPT. The option to use GPT-4 is available for plus users, with a limit of 100 requests every four hours. Intrigued by its potential, I decided to put GPT-4 to the test by creating a game with a detailed description. I requested a game that could be coded in 150 lines or less in a one-page HTML JavaScript file. The game was called "Color Match," and I wanted GPT-4 to generate both the descriptive text and the code.

Observations about GPT-4

During my testing of GPT-4, I made several observations. Firstly, I noticed that GPT-4 was slightly slower than its predecessor, GPT-3. However, I believe that OpenAI will address this issue and improve the speed in the coming weeks and months as they Continue to Roll out updates and improvements. Additionally, I found that GPT-4 produced more reliable code compared to GPT-3. Although it was not perfect and had some limitations, I was impressed with the results overall. Now, let's take a closer look at the Color Match game generated by GPT-4.

Describing the Color Match Game

The Color Match game is a fascinating creation by GPT-4. In this game, players are tasked with quickly matching a target color by adjusting RGB sliders. The goal is to match the target color in the shortest amount of time possible. The game interface features a target color box, a Current color box, and RGB sliders. Players click the start/reset button to begin the game. The target color is randomly generated, and a timer starts counting. Players adjust the RGB sliders to match the color, and when they successfully match the target color, the timer stops.

Pros and Cons of GPT-4's Game Coding Ability

GPT-4's game coding ability comes with its own set of pros and cons. On the positive side, GPT-4's code generation is significantly more reliable compared to its predecessors. It provides a complete HTML and JavaScript solution within a single file, eliminating the need for separate CSS files. This makes the code simpler and easier to manage. However, one limitation I encountered was that GPT-4 occasionally cut off the code, especially with longer code snippets. Despite this drawback, I was impressed with GPT-4's ability to generate a functional game in a short amount of time.

Creating a Paragraph-to-Text Reader Webpage

In addition to game coding, GPT-4 also proves its versatility in creating webpages. I decided to test GPT-4's capabilities by requesting a webpage that allows users to input paragraphs of text. The webpage would then Read each sentence of the text back to the user while highlighting it. GPT-4 swiftly generated the HTML and JavaScript code for this interactive text reader webpage. Upon testing, I found that GPT-4's approach involved reading each word separately, resulting in choppy audio. However, I had a solution in mind.

Highlighting Each Sentence in the Text Reader

To improve the reading experience of the text reader webpage, I modified the code generated by GPT-4 to read each sentence and highlight it accordingly. By making this adjustment, the reading became more Fluent, eliminating the choppiness caused by reading each word separately. Although there are limitations in highlighting words accurately using web text-to-speech capabilities, GPT-4's ability to generate the Core functionality of the web page within minutes was highly impressive.

Limitations of Text-to-Speech Highlighting

It's important to note that highlighting words while using text-to-speech technology presents challenges. The native web text-to-speech capabilities may not provide the necessary functionality to accurately highlight words as they are being spoken. As a result, achieving seamless word-by-word highlighting may require additional resources or alternative text-to-speech solutions. Despite these limitations, GPT-4's ability to generate the foundation of a text reader webpage is commendable.

Generating Images with DALL-E based on a Prompt

In addition to its language capabilities, GPT-4 is integrated with DALL-E, an image generation model. The combination of GPT-4 and DALL-E allows users to generate images based on Prompts. Although the AI is not yet capable of creating highly specific and detailed images, I decided to test GPT-4's image generation abilities by providing a prompt. The prompt requested an image of Trump and Biden wearing aprons and chef hats, standing side by side in a lively kitchen, enthusiastically tossing dough. The prompt further specified that the scene should include ingredients like berries and apples, with two pies on the counter.

Mid-Journey's Image Results and Upcoming Features

Curiosity led me to input the prompt into Mid-Journey, an image generation model, and the results were impressive. While Mid-Journey doesn't display text prompts correctly at the moment, it did generate a variety of images based on the provided description. The upcoming release of Mid-Journey Version 5 promises to bring even more significant advancements, including enhanced AI capabilities in various domains such as music and video creation. The pace of AI development continues to astound, and GPT-4 is at the forefront of this exciting progress.

Conclusion

GPT-4's introduction marks a significant milestone in AI development, offering a host of new capabilities and applications. From generating game code to creating interactive webpages, GPT-4 demonstrates its versatility and potential. While there are areas for improvement, GPT-4's ability to generate functional code and compelling image prompts is impressive. As AI continues to advance at a rapid pace, we can only imagine the possibilities that lie ahead.