According to experts, ChatGPT, an AI-powered chatbot that can write code and simulate human conversations, will revolutionize application development and the developer profession.
As described by OpenAI, the model converses in a conversational manner, challenges incorrect premises, admits mistakes, answers follow-up questions, and rejects inappropriate requests.
Currently, ChatGPT can’t write complex code, such as that for banking applications, but Rob Zazueta, a freelance technical consultant in Concord, California, believes it will become proficient in the next decade.
Charlotte Dunlap, an analyst at GlobalData, says the effects will occur much sooner than Zazueta predicted.
It is impossible to predict exactly how these advances will be implemented, according to Montreal AI Ethics Institute founder and principal researcher Abhishek Gupta.
As he noted, no one could have predicted the ubiquity of generative AI systems and the many forms they are taking today. In three to 10 years, it’s impossible to predict what will happen.
Software Engineering Jobs Of The Future
Rather than writing boilerplate code, developers will be able to focus on areas such as complex application architecture and cybersecurity in the near future, Gupta said.
ChatGPT already writes really good working code, according to Zazueta. “Using that, I can cut through boilerplate stuff quickly and focus on the more intensive work the AI is not yet capable of handling,” He said.
Zazueta said ChatGPT may replace some aspects of programming, such as writing generic functions and boilerplate code, but it won’t replace programmers entirely.
Zazueta said the goal is to structure a program, follow the logic, and make it more than the sum of its parts.
Nonetheless, ChatGPT could lead to new job titles. Prompt engineering, for instance, will become in-demand in the AI era. According to Gupta, prompt engineers understand how to write model inputs for chatbots to get the best results.
“In order to achieve your goals, you must have the right incantation in place,” he explained.
GlobalData’s Dunlap said that AI coders such as ChatGPT will also drive an increase in demand for data science-trained software developers. Data science platforms and languages like Go and Python, for example, are used by engineers to design, build, and test applications.
What Are The Benefits Of Using Chatgpt?
There are several benefits to using ChatGPT as a language model, including:
- Generating human-like text: ChatGPT can be used to generate text that is similar to how a human would write or speak, such as writing creative fiction, generating chatbot responses, or even composing emails.
- Improving natural language understanding: ChatGPT can be used to provide context to a given text, such as understanding the sentiment of a tweet or identifying the named entities in a news article.
- Language Translation: ChatGPT can be used to translate text from one language to another, such as translating a customer service chat from English to Spanish.
- Text Summarization: ChatGPT can be used to summarize a given text into a shorter version, such as summarizing a long news article or research paper.
- Text completion: ChatGPT can be used to complete a partially written text, such as completing a sentence or a paragraph.
- Cost-effective: Training large language models can be expensive, but using a pre-trained model like ChatGPT can be a cost-effective solution for many NLP tasks.
- Customizable: You can fine-tune the model on a specific domain or task to make it more accurate and efficient. For example, fine-tuning the model on a dataset of customer service transcripts will make it more accurate at answering customer service-related questions.
In addition, ChatGPT can be used in various applications such as question answering, story generation, code generation, data generation, and many more.
A dataset only going up to 2021 was used to train OpenAI’s bot using machine learning. Which is why it can’t answer questions about current events.
There isn’t much you can do with it right now and OpenAI is still in its testing phase which is why the system is having some difficulty scaling. Some of its other drawbacks include:
- ChatGPT is in its beta testing and does contain some bugs which need to be fixed.
- In addition, you can’t really contribute to its development since it is a closed-source project.
- The users have fewer options at their disposal because it is not as adopted as other chatbots.
- Also, ChatGPT relies heavily on machine learning algorithms, and these algorithms are in turn dependent on the data they are trained on. It is possible that Chat GPT can reproduce errors or biases if the data it is trained on contains errors or is inaccurate.
It is important for engineers to be able to multitask and create better software faster with anything that allows them to do so.
With these tools, developers can rapidly create amazing technology without having to do robotic tasks that are not worthwhile in terms of time and education.