In one of my blog post, I shared my thoughts on Github Copilot, a powerful AI-based code completion tool that revolutionized the way we write code. As a full-stack developer, I was excited to dive deeper into the world of AI and explore the ways in which it can be used to enhance my efficiency and productivity.
In this post, I would like to continue that conversation by focusing on another exciting AI-based technology which you might've recently heard of: ChatGPT. As a language model, ChatGPT has the ability to understand and generate natural language, making it a valuable tool for a wide range of applications. Whether it's automating mundane tasks, improving communication with colleagues and clients, or even writing code, the possibilities are truly endless.
ChatGPT is a language model developed by OpenAI, which utilizes deep learning to understand and generate natural language. It is capable of performing a variety of language-based tasks. For example, if you ask ChatGPT, "Could you write me a song about AIs taking over society", it will. Its potential is endless.
It's worth noting that ChatGPT is a general-purpose model, and it's used in various industries such as customer service, content creation, and many more. It's one of the most powerful language model available today, and it's constantly updated and improved. As I write this blog post, ChatGPT is available for free, try it out here.
The Great Replacement
The idea of having a machine that can understand and generate natural language with such accuracy raises some interesting questions. What does this mean for the future of our industry?
As a full-stack developer, I see ChatGPT more as an assistant than a developer. While, it has the ability to write an entire app on its own, I found that I always needed to review its code. In my opinion, it is not yet at the point where it can fully replace human effort. Its code can works, but aren't ready for production. Its possibilities are endless, but have limits (I know it's contradictory). For example, on fdf, a 42 school's project, I asked him to explain the Xiaolin Wu's line algorithm and blend it with my current Bresenham's algorithm. His explanations were clear and understandable, which isn't always the case with what you find, but his code didn't work.
Studies also show that AI and technology could be a source of new opportunities, but it's worth noting that these are just statistics, and the impact of AI and automation on jobs and productivity is a complex and ongoing topic.
What makes it strong?
One key difference between ChatGPT and Github Copilot, is that ChatGPT is focused on natural language processing, while Github Copilot is focused on code completion. I am impatient to see how people will integrate it, once its API will be public.
From automating mundane tasks to writing code, ChatGPT has the potential to revolutionize the way we work. Let's dive into how to make the most of it.
ChatGPT understands and generates natural language based on context. It is important for the user to provide as much context as possible to get the most accurate and relevant results. For example, if you are using ChatGPT for a chatbot application, providing the context of the conversation will help the model understand the user's intent and provide a more appropriate response.
As well as explaining your intentions, you can also make your intentions its intentions. Just like humans, ChatGPT will "imagine" itself in the context you give it and give more serious responses.
Finally, don't forget to correct ChatGPT too! It doesn't have a rocket science either, even though it relies on more data than a human being has. Mistakes are robotic, (also from being human lol)!
It's all about context.