ChatGPT (Chat Generative Pre-trained Transformer) is a chatbot launched by OpenAI (Artificial Intelligence) in the month of November 2022. It is built on the top of OpenAI's GPT-3 family of large language models and is fine-tuned (an approach to transfer learning) with both supervised and Induration learning technics.
ChatGPT was launched as a prototype on November 30, 2022, and quickly garnered attention for its detailed reactions and articulate answers across many domains of knowledge. Its uneven factual purity was identified as a significant drawback. Following the publication of ChatGPT, OpenAI was valued at $29 billion.
Nitin Raj, CEO and co-founder of Riverum, says that in the coming days, we can expect some progress in AI technology, but the reality is that an error-free and perfect ChatGPT (or any other) is still a long way off. Have to decide.
Source: Safalta.comHe observes that while AI technology is advancing at a rapid pace, it is still limited in its ability to understand and respond to human emotion, which is necessary to be considered a truly intelligent chatbot.
ChatGPT (or any different chatbot) will demand huge amounts of data, both details and discussion, to have any chance of developing the intelligence necessary to respond accurately to human emotion. This requires not just data, but also time and trying to properly train the system to recognise and interpret emotional context. In addition, there are still many unknowns in terms of the exact type of data needed, making it hard to predict just how long it will take to train a system to the level of the perfect ChatGPT. That said, there is an expectation that in the near future, AI technology will become more advanced and able to better understand and react to human emotions. However, we are still a long path off from creating a perfect ChatGPT with human-like intelligence,” says Raj.
The Sensitive Factor
Eyebrows were raised when Google engineer Blake Lemoine, who was on its Responsible AI team, said that its conversational AI is ‘sensitive.’ They found it to contain "feelings, emotions. The sensitive factor of ChatGPT is the data that it was trained with the model trained using a large dataset of text, it may contain biases and stereotypes present in the data. Additionally, ChatGPT has been trained on text from the internet that may contain offensive or harmful language. It's important to be aware of these limitations when using the model with responsibility.
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· Experiment with it to help you find mistakes in your code. If you have a segment of code that you’re having trouble debugging, you can put that into ChatGPT with details about what you’re expecting versus what’s actually happening. The model may be capable to assist you with finding the issue.
· Experiment with it to help find edge cases in your code. The model has a lot of computational power so it may be able to generate edge cases for which your code will fail that you might not be capable to identify as quickly.
· Experiment with product ideas. Asking it production-related questions can get you a quick list of the possible use cases for your software based on other products and ideas it’s been trained on. This In general won’t yield out-of-the-box ideas but it will help you find gaps in your product in comparison to others.
· Experiment with it for writing test cases. ChatGPT is competent at writing unit tests and it's low risk to get test cases from the model, as they will simply fail if they are wrong and will be clearly incorrectly formulated if it’s not testing what it’s imaginary too. Also, as unit tests are generally straightforward, the probability that the model will get it right is high, given you enter in the format: test component X with the inputs a, b and c and hope the output to be Y.
· Experiment with it to get architectural and infrastructure options. When Evaluation of different strategies for a task you know will require infrastructure changes, it might be useful to ask for ChatGPT input. It can give your ideas but don’t fully rely on its answer, it should be no more than a source of inspiration if you’re not sure which way to go.
Related article: Why is Chat GPT required to use Natural Language?
· Do NOT experiment with it to learn how to code. The code that is generated is not guaranteed to be correct. It may be dynamic, but even if it is functional it might not be the best way to code. For example, I’ve Inform when I asked it to write React components it uses a general props item and does not explicitly define each property as is industry standard. Also, it does not automatically abstract the same code into functions so the code is usually overly-verbose.
· Do NOT experiment with it to generate code that requires a lot of contexts. If you’re hoping to have the model do your work, I have some bad news for you. It’s unthinkable to provide the model with the context of an entire codebase or product, so if you don’t already have a strong idea of how to approach the task then the ChatGPT will realistically not be very helpful.
· Do NOT experiment with it for school or university assignments. Aside from the data that the answer may not be correct, and also that probably other students will use it for a similar purpose leading to plagiarism detection, you will not learn. Solving assignments is what made me increase most during my formal education in software engineering. Not the lecture, the assignments are what taught me the most, so if you cheat using ChatGPT you’re only cheating yourself out of a better career.
Ways to get benefit from using ChatGPT:
- Natural Language Processing (NLP) tasks such as text generation, language translation, and language understanding.
- Text generation for creative writing and content creation.
- Chatbot development for customer service, e-commerce, and other industries.
- Language-based search and information retrieval.
- Language modelling for speech recognition
- Automated summarization and text summarization
- Text speech and recognition
Will ChatGPT will replace Humans?
ChatGPT is a powerful tool for natural language processing, but it is not capable of replacing humans as it can perform many language-based tasks with high accuracy, it lacks the ability to understand context, emotions, and common sense, which are key elements of human intelligence.
How ChatGPT is Helpful Chabot?
Chat GPT is helpful in many ways:
- Text generation and content creation
- Language Translation
- Language understanding
- Chatbot development
- Language-based search and information retrieval.
How ChatGPT decodes the code language?
ChatGPT is pre-trained on a large dataset of code and text, which allows it to learn the structure and syntax of code language. This pre-training enables the model to generate code that is coherent and fluent, while also understanding the meaning and purpose of the code. It's important to note that ChatGPT is not a full-fledged code editor or IDE, and it doesn't have the capability to detect errors or bugs in the code, its focus is to generate coherent and fluent code.