GPT-4: New Features and Use Cases Compared to Previous Language Models

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GPT  4

GPT-4: New Features and Use Cases Compared to Previous Language Models

Introduction

GPT-4 has recently been released, and opinions on its performance have been mixed. In this blog post, I will explore the new features and use cases of GPT-4 compared to the previous large language models by OpenAI. I will provide specific examples using the GPT-4 model and compare its outputs to the previous GPT-3.5 model available on ChatGPT.

What Makes GPT-4 Different?

  1. Improved Problem Solving Abilities: GPT-4 can tackle difficult problems with greater accuracy, thanks to its broader general knowledge and problem-solving abilities. It can handle more complex questions and provide more detailed answers compared to previous models.

  2. Increased Token Limit: GPT-4 allows you to read and generate up to 25,000 words, providing a much larger token limit compared to GPT-3.5. This means it can handle more input and generate more extensive output. If you’re working on longer-form content like blog posts, articles, ebooks, or fictional stories, GPT-4 makes it easier.

  3. Support for Writing Code in Major Languages: While previous language models had some code-writing capabilities, GPT-4 has improved this feature, allowing you to write more complex code in all major programming languages.

  4. Enhanced Math Capabilities: GPT-4 excels in solving complex math equations, enabling you to tackle more advanced mathematical questions compared to GPT-3.5.

  5. Image Understanding: A major differentiating factor of GPT-4 is its ability to understand images as inputs. You can provide an image to GPT-4, and it will comprehend the context and generate outputs based on the image. This feature has various applications, such as aiding visually impaired individuals in understanding their surroundings.

  6. Safer Usage: GPT-4 incorporates more guardrails, making it safer to use. These guardrails ensure responsible and ethical usage of AI.

Examples of GPT-4 Outputs Compared to GPT-3.5

  1. Complex Answers: GPT-4 delivers more comprehensive and nuanced answers to complex questions. For instance, when asked about human beings’ free will, GPT-4 provided a detailed response, presenting various perspectives on the issue. In comparison, GPT-3.5’s answer was less detailed and comprehensive.

  2. Longer Form Content: GPT-4’s increased token limit allows for the generation of longer content. By providing a simple prompt, such as writing a 1500-word blog post about making money online as a teenager using Markdown, GPT-4 can generate a well-formatted and coherent blog post. The formatting is improved compared to GPT-3.5, making it easier to read and understand.

  3. Math Problem Solving: GPT-4 demonstrates superior performance in solving complex math equations. It provides accurate solutions and is better equipped to handle advanced mathematical queries compared to GPT-3.5.

  4. Image Understanding (not available for demonstration): While GPT-4 has the capability to understand images, the feature is not yet fully accessible in ChatGPT. It is expected that you will be able to upload images or provide descriptions for the model to understand the context.

Conclusion

GPT-4 introduces several notable advancements over previous language models. Its enhanced problem-solving abilities, increased token limit, code-writing support, improved math capabilities, image understanding, and safer usage make it a powerful tool. GPT-4’s ability to generate detailed and high-quality outputs with minimal instructions is impressive. Although it may be slower at times, further refinements and optimizations are expected. GPT-

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