If you are a computer programmer or software engineer, you may be amazed at the capabilities demonstrated by modern software applications.
ChatGPT was announced in public beta just before Christmas. It is powered by the GPT-3 Large Language Model (LLM) designed to use generative AI and natural language processing (NLP) to produce text that is nearly indistinguishable from human writing. It’s a chatbot. Due to its impressive features, it quickly went viral and has amassed millions of users so far.
Ask them to write Shakespearean-style poems about trees or articles about industrial applications of AI and you’ll get it.
Novelists, copywriters, and journalists believe ChatGPT has the potential to produce impressive results, but it’s not yet to the point where they’re ready to worry about their work. The prose texts it produces lack personality, are somewhat prone to factual errors, and are designed primarily to contain all the necessary information. This means that you do not consider whether your output is funny, amusing, scary, or can evoke other emotions that the writer is trying to convey. All of these factors are important if you need to put on.
But when it comes to writing code, none of that matters. All that matters is that the created program does what it’s supposed to do. Either it works or it doesn’t. An interpreter that takes human (or machine) generated code and runs it as an application doesn’t give up reading halfway through just because it’s not interesting enough!
Are ChatGPT and NLP a threat to programming and software engineering jobs?
Despite all this, ChatGPT and other NLP technologies available today don’t seem to make all coders, programmers, and software engineers redundant anytime soon.
First, you can only write relatively simple programs. If you ask for something too complex, such as a sophisticated game or business application, acknowledge your weaknesses and communicate that the task is currently beyond your capabilities.
Computers haven’t yet told us, for example, what kind of code or application we need to accomplish what we’re trying to do. Even if we knew it because we said it, ChatGPT in particular cannot (at this time) try to create this software that specifically gives us as a user a competitive edge over users of another software.
For example, you can’t say, “Please create an e-commerce platform that sells more effectively than Amazon.” Even if you want this, you should invest the time and effort to first figure out what’s good about Amazon’s platform and then find ways to improve it.
For this reason, ChatGPT (and other current NLP-based tools) are not designed to create software designed to give a business an edge, or really to compete with human creativity and ingenuity. However, it is still of limited effectiveness when creating custom software.
The thing to note here is that while we can do our best to extrapolate what will happen in the future, no one really has a crystal ball. It’s no exaggeration to say that many people used to having conversations were a little shocked by ChatGPT’s superior features.
Future developments could actually speed us up to the point where human programmers and many other types of specialists are no longer needed at all. But for the time being, we can be confident that there is still a wide range of skills required to develop software that computers cannot replicate anytime soon.
So how can programmers today use ChatGPT and other NLP tools?
Programmers who spoke about ChatGPT and potential future evolutions of the technology said it was not a threat, but a very valuable tool at the moment.
You can quickly generate a framework and use it to outline building your application, and fill in questions like how your data should be structured and what user interface features you want.
As a result of this, it is very useful as an adjunct to “box ticks”. In other words, make sure your code structure covers all the bases your application needs to do its job.
It’s often written that as soon as ChatGPT duplicates a job title, it creates a new one. ChatGPT appears to have features that make many routine tasks significantly faster, both in coding and in other roles, but this requires a new skill set. This includes developing the skills necessary to come up with prompts to get you to do what you want.
As mentioned before, they shrug their shoulders when you tell them to write complex software. But if you divide the tasks it needs to do that into chunks and tell it to start processing those chunks one by one, it’s more likely to start getting somewhere.
So all those years spent learning to code and software engineering are unlikely to go to waste. It takes that knowledge and experience to choose the right prompts and make sure the ChatGPT output is on the right track.
One coder who spoke to us about this situation said: For example, come up with your own idea of what kind of application you want. ”
Besides writing new code, another useful feature of ChatGPT is debugging existing code (or code it has written itself). Any programmer will tell you that debugging (the process of finding and fixing errors) is often a tedious process that requires going through large amounts of code to solve problems. Not only can ChatGPT automate this process, but it can also explain why your code isn’t working, according to people who have already used it to help them code.
Over the past five years or so, I’ve spent a lot of time talking to people about how AI could impact their jobs and industries, and almost every conversation mentions One word that comes to mind is “augmentation.”
What this means is that those who are able to take on an emerging kind of technology and figure out how to use it to enhance their own skills are more likely to succeed. is meant to be used to automate low-value repetitive tasks that take up a lot of your time. At the same time, we must figure out how to make the most of the time this frees up and use more effectively the skills that computers cannot yet replace. Creative thinking, strategic planning, problem solving, and emotional intelligence are prime examples. Whether a computer programmer or a doctor, adopting this approach to the disruptive emergence of his AI tools and applications in this industry is the best way to remain useful and relevant in the age of AI. It’s a way.
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