ChatGPT for Deverlopers and Code Completion
ChatGPT can write code. Now researchers say it's good at fixing bugs, too
A developer's new best friend? ChatGPT is up with the best when it comes to automatically debugging code. But whether it saves developers' time or creates more work remains to be seen.
OpenAI's ChatGPT chatbot can fix software bugs very well, but its key advantage over other methods and AI models is its unique ability for dialogue with humans that allows it to improve the correctness of an answer.
Elon Musk Opinion On chatGPT
Researchers from Johannes Gutenberg University Mainz and University College London pitted OpenAI's ChatGPT against "standard automated program repair techniques" and two deep-learning approaches to program repairs: CoCoNut, from researchers at the University of Waterloo, Canada; and Codex, OpenAI's GPT-3-based model that underpins GitHub's Copilot paired programming auto code-completion service.
Also: How to get started using ChatGPT
"We find that ChatGPT's bug fixing performance is competitive to the common deep learning approaches CoCoNut and Codex and notably better than the results reported for the standard program repair approaches," the researchers write in a new arXiv paper, first spotted by New Scientist.
It’s Time to Pay Attention to A.I. (ChatGPT and Beyond)
The best AI chatbots: ChatGPT and other interesting alternatives to try
AI chatbots and writers can help lighten your workload by writing emails and essays and even doing math. They use artificial intelligence to generate text or answer queries based on user input. ChatGPT is one popular example, but there are other noteworthy chatbots.
That ChatGPT can be used to solve coding problems isn't new, but the researchers highlight that its unique capacity for dialogue with humans gives it a potential edge over other approaches and models.
The researchers tested ChatGPT's performance using the QuixBugs bug-fixing benchmark. The automated program repair (APR) systems appear to be at a disadvantage as they were developed prior to 2018.
Also: The best AI art generators: DALL-E 2 and alternatives
ChatGPT is based on the transformer architecture, which Meta's AI chief Yann LeCunn highlighted this week was developed by Google. Codex, CodeBERT from Microsoft Research, and its predecessor BERT from Google are all based on Google's transformer method.
OpenAI highlights ChatGPT's dialogue capability in examples for debugging code where it can ask for clarifications, and receive hints from a person to arrive at a better answer. It trained the large language models behind ChatGPT (GPT-3 and GPT 3.5) using Reinforcement Learning from Human Feedback (RLHF).
While ChatGPT's ability for discussion can help it to arrive at a more correct answer, the quality of its suggestions remain unclear, the researchers note. That's why they wanted to evaluate ChatGPT's bug-fixing performance.
The researchers tested ChatGPT against QuixBugs 40 Python-only problems, and then manually checked whether the suggested solution was correct or not. They repeated the query four times because there is some randomness in the reliability of ChatGPT's answers, as a Wharton professor found out after putting the chatbot through an MBA-like exam.
Also: The developer role is changing radically
How I Coded An Entire Website Using ChatGPT
ChatGPT solved 19 of the 40 Python bugs, putting it on par with CoCoNut (19) and Codex (21). But standard APR methods only solved seven of the issues.
The researchers found that ChatGPT's success rate with follow-up interactions reached 77.5%.
The implications for developers in terms of effort and productivity are ambiguous, though. Stack Overflow recently banned ChatGPT-generated answers because they were low quality but plausible sounding. The Wharton professor found that ChatGPT could be a great companion to MBA students as it can play a "smart consultant" -- one who produces elegant but oftentimes wrong answers -- and foster critical thinking.
"This shows that human input can be of much help to an automated APR system, with ChatGPT providing the means to do so," the researchers write.
"Despite its great performance, the question arises whether the mental cost required to verify ChatGPT answers outweighs the advantages that ChatGPT brings."
Can ChatGPT replace Programmers? What are ChatGPT OpenAI limitations
Let’s see how capable this chat bot is and whether it can replace programmers. In addition, we will discuss its limitations and what type of tasks can be performed by ChatGPT.
Will ChatGPT Replace Software Engineers? (full analysis)
Working of ChatGPT
Let’s talk about working of ChatGPT in brief, ChatGPT is a large language model based on GPT3 and GPT 3.5. This AI tool applies machine learning algorithms to a massive corpus of text to respond to user requests using language that sounds surprisingly human.
According to OpenAI, ChatGPT increases its capability through reinforcement learning that relies on human feedback. The business hires human AI trainers to interact with the model, taking on the roles of both the user and the chatbot. Trainers compare responses provided by ChatGPT to human responses and rate their quality to reinforce human-like conversational approaches.
ChatGPT can replace programmers
Artificial intelligence (AI) scientists have been impressed by the skills of AlphaCode, an artificial intelligence system that can often compete with humans in solving simple computer science problems. Google’s sister company DeepMind, an AI based in London, released the tool in February and has now published its results in Science, showing that AlphaCode beat about half of humans in code competitions.
Social media users have been mesmerized by the ability of another chatbot, called ChatGPT, to produce sometimes meaningful-sounding (and sometimes sublimely ridiculous) mini-essays — including short computer programs — on demand. But these state-of-the-art AIs can only perform relatively limited tasks, and researchers say they are nowhere near being able to replace human programmers.
ChatGPT and AlphaCode are “big language models” — neural network-based systems that learn to perform a task by digesting vast amounts of existing human-generated text. In fact, the two systems use “virtually the same architecture,” says Zico Kolter, a computer scientist at Carnegie Mellon University in Pittsburgh, Pennsylvania. “And while there are of course minor differences in training and execution, the main difference, if any, is that they are simply trained on different data sets and therefore for different tasks.”
This Is Better Than ChatGPT (With Prompting Guide)
While ChatGPT is a general-purpose conversation tool, AlphaCode is more specialized: it was trained exclusively on how people answered questions from software writing competitions. “AlphaCode was designed and trained specifically for competitive programming, not software engineering,” David Choi, a research engineer at DeepMind and co-author of the paper, told Nature in an email.
Limitations of ChatGPT
Wrong answers
ChatGPT is a large-scale language model that is constantly trained to improve response accuracy. However, since this is a completely new technology, the model has not yet undergone sufficient training. Therefore, the AI chatbot may provide wrong answers. Because of this, StackOverflow banned ChatGPT, saying: “Overall, because the average rate of getting correct answers from ChatGPT is too low, posting answers generated by ChatGPT is substantially harmful to our site and to users who ask or search for correct answers.”
Training data limitations and bias issues
Like many AI models, ChatGPT has limitations in its training data. Both limitations in the training data and biases in the data can have a negative impact on model output. In fact, ChatGPT has shown a bias when it comes to training minority data groups. Therefore, it is important to improve the transparency of model data to reduce the bias of this technology.
Sustainability
There is a thread of conversation on Twitter about how many graphics processing units (GPUs) are needed to run ChatGPT. The bottom line is that ChatGPT is very expensive to run. Since ChatGPT is a free product, there are currently a lot of questions about how sustainable the technology is in the long term.
ChatGPT's OpenAI Projects to Reach $1 BILLION Revenue SOONER!
4 ways devs can use ChatGPT to be more productive
Four ways in which ChatGPT can maximize your productivity as a developer, as well as four reasons why it is not an -be-all and end-all solution to writing code. Using ChatGPT to its fullest potential while avoiding its pitfalls will allow your productivity to skyrocket!
We’ll cover:
How ChatGPT can help devs write better code
1. Making coding more accessible
2. ChatGPT as a research assistant
3. Reducing tedium with ChatGPT
4. Using ChatGPT for natural language processing
4 areas where ChatGPT falls short
1. Human judgment is still required
2. ChatGPT can’t problem solve
3. ChatGPT doesn’t have multiple perspectives
4. ChatGPT can’t get you hired
Start leveraging AI for yourself
How ChatGPT can help devs write better code
ChatGPT is not the first machine learning tool to serve as a coding assistant.
How ChatGPT Works Technically For Beginners
Autocomplete and text-generation software has been helping us type code and even email faster for several years. We also have GitHub Copilot, which uses a production version of OpenAI’s GPT-3 to suggest improvements and flag potential problems in our code. As a coding assistant, ChatGPT distinguishes itself from Copilot with the ability to formulate detailed responses to conversational prompts instead of basic pre-programmed commands.
Here are four distinct ways using ChatGPT can make your life as a developer simpler.
1. Making coding more accessible
Throughout the history of computer science, we’ve seen technological advancements that have enabled many more people to become developers. Largely thanks to methods of abstraction, it has become easier for more and more people to leverage complex technologies once only understood by highly specialized engineers.
For instance, high-level programming languages, in tandem with compilers and IDEs, allow today’s engineers to write human-readable code without having to write machine code (which is in binary and not human-friendly). Similarly, the improvement of AI assistants like Copilot is a promising sign that we’re still moving toward making coding a more accessible and enjoyable experience for all.
Benefitting from abstraction doesn’t necessarily mean that developers would be any less skilled or knowledgeable. Similarly, not knowing how a car engine works doesn’t make you a bad driver, and using autocomplete doesn’t make you a bad engineer. We can still build beautiful applications while benefiting from high-level languages like Java or machine learning tools like ChatGPT.
How ChatGPT is Trained
2. ChatGPT as a research assistant
ChatGPT has been trained on over 45 terabytes of text data from various sources, including CommonCrawl, WebText2, and code in Python, HTML, JavaScript, and CSS.
ChatGPT generates responses based on this vast training dataset — and conveniently does so in response to human input. The ability to interpret human input can make ChatGPT a helpful research assistant. While its results still need validation, it can provide accurate results that can save us from scouring search engine results or StackOverflow. It can even offer further explanations that will aid coders in learning and understanding new concepts.
This benefit can help us streamline our search for new and relevant knowledge while coding. No developer knows everything, and questions are bound to pop up in your mind every now and then. Hopping over to the OpenAI tab and having ChatGPT answer questions can save a lot of time spent researching. You shouldn’t use ChatGPT to pull all of your information, but this is an excellent method to get an answer in a matter of seconds.
3. Reducing tedium with ChatGPT
ChatGPT will make coding more productive and bug-free. As it accommodates more complex requirements, we can look forward to it helping eliminate grunt work and accelerate productivity and testing.
As assistants such as ChatGPT evolve, many of the tedious tasks that have occupied developers could go away in the next decade, including:
Automating unit tests
Generating test cases based on parameters
Analyzing code to suggest security best practices
Automating QA
Another major benefit is automating the mundane task of creating documentation. ChatGPT can help developers generate documentation for their code, such as API and technical documentation. For example, ChatGPT can analyze your code and extract valuable information such as function and variable names, descriptions, and usage examples. It can then use this information to create detailed reports that are easy to navigate. This automation can save developer teams significant time and effort that would otherwise be dedicated to manually constructing the necessary documentation.
Other forms of documentation, such as user manuals, release notes, troubleshooting guides, and more, can also be expedited by ChatGPT. Although this chatbot cannot be a replacement for understanding your code, it is a great tool for efficiently maintaining proper documentation so that other teams (and new team members) can easily understand the dev team’s workflow.
Relieving developers of menial tasks can free them to think about more complex issues, optimizations, and higher-level concerns, such as an application’s implications for its users or business. Allowing this new AI chatbot to perform these actions, such as data processing, will open up your work schedule to focus on more critical and creative projects.
Some people think assistant tools make developers lazy. We strongly disagree. Once you’ve learned something, there’s no cognitive or productivity benefit to retyping the same line of code repeatedly. Why reinvent the wheel if the best code for a particular task has already been tried and tested? Besides, the problem you’re solving is probably more complicated than copying/pasting a few code snippets.
This benefit is analogous to how APIs simplified devs’ lives. For instance, the payment processing that Stripe now hides behind a single API once required developers to write 1,000 lines of code.
What Are The Top 10 Limitations Of ChatGPT?
4. Using ChatGPT for Natural Language Processing
Natural language processing (NLP) is a subset of machine learning that uses software to manipulate and produce natural languages, such as the text that appears when you ask ChatGPT a question or the speech you hear from an AI bot like Alexa or Siri. Tasks such as translating between languages, text analysis, speech recognition, and automatic text generation all fall under the umbrella of natural language processing.
Here are a few examples of how ChatGPT can aid developers with natural language processing.
Sentence parsing: ChatGPT can parse natural language inputs and extract the desired information, such as entities and actions. This information can be used to identify the necessary requirements.
Text classification: ChatGPT can classify natural language inputs into predefined categories such as functional requirements, non-functional requirements, or constraints.
Summarization: ChatGPT can summarize natural language inputs into a more concise and actionable form, which can help developers quickly understand the key requirements.
Dialogue-based: ChatGPT can assist in a dialogue-based approach, where developers can ask follow-up questions to gather more clarification on the requirements.
Using natural language processing techniques, ChatGPT can help devs gauge the requirements expressed in natural language. They can then transform this information into actionable requirements to guide development.
It’s important to note that these examples pertain to one natural language processing use case. Your approach will depend on the context and conditions of your project.
4 areas where ChatGPT falls short
ChatGPT is not magic. It looks at a massive corpus of data to generate what it considers the best responses based on existing code.
Accordingly, it definitely has its limitations. Be wary of these limitations while utilizing ChatGPT to your benefit.
Let's build GPT: from scratch, in code, spelled out.
1. Human judgment is still required
ChatGPT is a valuable tool, but it surely doesn’t replace human judgment. Its learning models are based on consuming existing content — some of which contain mistakes and errors.
No matter what code snippet is generated by ChatGPT, you still need to apply your judgment to ensure it’s working for your problem. ChatGPT generates snippets based on code written in the past, so there’s no guarantee that the generated code is suitable for your particular situation. As with any snippet you find on StackOverflow, you still have to ensure your intention was fully understood and that the code snippet is suitable for your program.
Ultimately, we can’t blindly copy/paste code snippets from ChatGPT, and the consequences of doing so could be severe.
2. ChatGPT can’t problem-solve
Problem-solving is an essential skill that developers need to have, which is why machine-learning and text-based tools won’t take over developer jobs anytime soon.
As a developer, your job involves understanding a problem, coming up with several potential solutions, then using a programming language to translate the optimal solution for a computer or compiler. While machine learning tools can help us type code faster, they can’t do problem-solving for us.
While ChatGPT can enable many people to become better, more efficient developers, it’s not capable of building large-scale applications for humans. In the end, we still need human judgment to discern between good and bad code. Even if we’re receiving help when writing code, we’re not running out of big problems to solve.
Relying on ChatGPT to solve your problems with plagiarized code is dangerous. For one thing, inserting code you copied into your applications indiscriminately introduces great security, legal, and ethical risks, even if you’re borrowing from a machine-learning tool. Besides, the tech industry still wants critical thinking developers, and you’re not going to convince anyone you have those attributes by stealing code.
Suffice it to say, plagiarism is definitely not the correct use of ChatGPT.
Microsoft: ChatGPT For Free - Join The Waitlist!
3. ChatGPT doesn’t have multiple perspectives
ChatGPT has a limited perspective. Its suggestions are based on the data it is trained with, which comes with many risks.
For one, if ChatGPT mistakes a highly repeated code snippet as a best practice, it can suggest and perpetuate a vulnerability or inefficiency.
ChatGPT is fully capable of generating incorrect answers, but like any other answer, it will do so with utmost confidence. Unfortunately, no metric helps manage expectations about the potential error in a response. This is a disadvantage against other sources we visit for guidance. Sites like StackOverflow or GitHub are capable of giving us more multidimensional data. We can validate others’ suggestions by looking at their context, responses, upvotes, etc. In this sense, other sources are better equipped to touch on the nuances of real-world problems.
ChatGPT’s limited perspective can make it something of an echo chamber, which can be very problematic. We’ve long known that machine learning algorithms can inherit bias, so AI is vulnerable to adopting harmful biases like racism, sexism, and xenophobia. Despite the guardrails that OpenAI has implemented, ChatGPT is also capable of inheriting bias. (If you’re interested, reporter Davey Alba discussed ChatGPT’s susceptibility to bias on Bloomberg.)
All in all, we have to take every ChatGPT response with a massive grain of salt — and sometimes, it might be easier just to write your code from scratch than to work backward to validate a generated code snippet.
Why OpenAI’s ChatGPT Is Such A Big Deal
4. ChatGPT can’t get you hired
Though it can generate a code snippet, ChatGPT is not the end of coding interviews. Besides, the majority of the coding interview consists of problem-solving — not writing code. Writing code will only take about 5-10 minutes of a 45-minute coding interview. If you’re curious about how to prepare for interviews efficiently, check out this full breakdown of the Amazon coding interview.
The rest of the coding interview requires you to give other hireable signals. You still need to ensure that you’re asking the right questions to articulate and understand your problem and narrating your thought process to demonstrate how you narrow your solution space. ChatGPT can’t help you with any of this. However, these critical thinking and problem-solving skills carry just as much weight in your hireability as your coding competency.
Don’t rely on ChatGPT too heavily. Instead, rely on your knowledge and skills to get the job!
Start leveraging AI for yourself
Generating Music with ChatGPT and MuseScore 4
Machine learning tools help us perform tasks more efficiently, but they don’t replace our need to think. Sometimes they’re right, and other times they’re incredibly (and hilariously) wrong. ChatGPT will help you immensely in your daily life, but it stops well short of doing your job for you.
While assistants like Siri and Alexa can help us with basic tasks, they can’t help us with complex efforts like making substantial life changes. Similarly, ChatGPT can’t help us with complex problems, nor can it replace innovation. But these technologies help alleviate menial tasks that distract us from tackling more ambitious issues (such as improving AI technologies).
As a developer, you shouldn’t stop investing in your learning or long-term coding career. If anything, be open to incorporating these tools into your life in the future. If you are interested, you can learn how to leverage AI for yourself.
With these resources, you’ll get up to speed quickly through hands-on work with ML techniques and tools, including deep learning, NLP, GPT-3, and integrating the OpenAI API.
Conclusion
The real question by the end of this topic is – Can AI write blogs and replace Google or Human interactions? The answer is clearly NO, as of now because there are a lot of dependencies relying on human intelligence and this trending technology. Although this technology is a charm still the ratio of bugs and inaccurate answers is high in ChatGPT (Generative Pre-trained Transformer). On the other hand, Google works with a different mechanism and its metrics are based on websites. But the amount of fame that this technology has been getting is highly appreciable and we hope for brighter days in this technology.
Frequently Asked Questions (FAQ)
1. Who built ChatGPT?
Ans: ChatGPT is an AI-based model that was launched by OpenAI in Nov 2022 and works on automating chatbot technology. It is also considered the advanced version of traditional support chat systems. It was founded back in 2015 by Elon Musk, Ilya Sutskever, Wojciech Zaremba Greg Brockman, and Sam Altman. and became sensational overnight. The company’s current CEO is Sam Altman.
2. Is ChatGPT free to use?
Ans: Since it is still in the development phase and their team is continuously working to make ChatGPT more smooth and interactive so currently it is free to use and open to all. However, the company has not disclosed any future plans regarding the usage.
3. Will ChatGPT replace Google?
Ans: The answer to this is “NO”, ChatGPT is an AI-based trained model that works on generating output based on human interaction (provided inputs) and there are times when ChatGPT is not even answering the relevant answers. On the other hand, Google is an internationally established brand that is being served as a home brand for search engines for every third person in the world. Google offers many other services that are more precise, vast, and accurate. So, ChatGPT is likely not going to replace Google completely.
4. Who owns Open AI?
Ans: Open AI is an AI-based research lab that has two different verticals, i.e.
OpenAI LP
OpenAI INC
The organization was founded by Elon Musk, Ilya Sutskever, Wojciech Zaremba Greg Brockman, and Sam Altman.
5. Will ChatGPT take jobs?
Ans: The concept of ChatGPT is so unique that it gained popularity in a matter of no time. But, since it’s in a new phase and there are tons of work required to generate quality output. So, the answer is “NO” it’s not going to take jobs in the upcoming years.
6. What are ChatGPT Alternatives?
Coding Made Easy with ChatGPT - AI Webinar - Feb 22, 2023
Ans: Since its launch, many companies have come out offering different tools for AI-based content, among which are listed below:
ADVANTAGES OF CHATGPT:
Generates human-like text: ChatGPT is trained on a large corpus of text and can generate text that is difficult to distinguish from text written by a human.
Can be fine-tuned: ChatGPT can be fine-tuned on specific tasks such as question answering, dialogue systems, and text summarization.
Can handle a wide range of topics: ChatGPT has been trained on a diverse set of text, which means it has the ability to handle a wide range of topics.
Can generate long-form text: ChatGPT is capable of generating long pieces of text, such as articles or essays, which can be useful for content creation.
Can be integrated with other systems: ChatGPT can be integrated with other systems such as chatbots, virtual assistants, and language translation systems.
DISADVANTAGES OF CHATGPT:
Lack of context awareness: ChatGPT does not have the ability to understand the context of the conversation or the user’s intent, which can lead to irrelevant or nonsensical responses.
Can generate biased or offensive content: Since ChatGPT is trained on a dataset that reflects the biases of its source data, it can generate biased or offensive content if not properly monitored.
Lack of common-sense knowledge: ChatGPT does not possess common sense knowledge, it may struggle to understand and respond to certain types of questions or requests that involve common-sense reasoning.
Over-reliance on training data: ChatGPT’s performance is directly tied to the quality and quantity of the training data.
Can be computationally expensive: Running ChatGPT requires a significant amount of computational resources, which can be costly and impractical for some applications.
BENEFITS OF CHATGPT:
Automation of tasks: ChatGPT can automate tasks such as text generation, content creation, and customer service, which can save time and increase efficiency.
Improved customer service: ChatGPT can be integrated into customer service systems to provide quick and accurate responses to customers, improving the overall customer experience.
Increased productivity: ChatGPT can assist with writing, research, and data analysis, which can increase productivity in various industries.
Personalization: ChatGPT can be fine-tuned to understand the specific language and style of a given industry or company, providing a more personalized experience for customers.
Creative applications: ChatGPT can be used in creative applications such as writing fiction, poetry, or song lyrics, which can be beneficial for artists, writers and other creatives.
More Information:
https://openai.com/blog/chatgpt/
https://www.geeksforgeeks.org/what-is-chatgpt/
https://levelup.gitconnected.com/how-to-use-chatgpt-for-developers-4e7f354bbc02
https://medium.com/@tanyamarleytsui/coding-with-chatgpt-b50ab3fcb45f
https://platform.openai.com/docs/introduction/overview
https://www.projectpro.io/article/chatgpt-application-examples/713