OpenAI has trained a model called ChatGPT which interacts in a conversational way. The dialogue format makes it possible for ChatGPT to answer followup questions, admit its mistakes, challenge incorrect premises, and reject inappropriate requests. ChatGPT is a sibling model to InstructGPT, which is trained to follow instructions in a prompt and provide a detailed response. Stack Overflow is also discussing posting content generated using other Artificial Intelligence tools that are similar to ChatGPT on its platform. It will frame a new policy soon with clarity on all these issues. Does that mean No-Code and Low-Code Platforms might disappear due to ChatGPT.

According to Stack Overflow's blogpost, getting a correct answer on ChatGPT is too low at the moment and it could also substantially harm the site and the users who are looking for the right answer.  The blog post also writes that one concern is that many of the people posting the answers with the help of the AI chatbot have no real expertise in the subject.

How does it work?

Trained by AI and machine learning, the system is designed to provide information and answer questions through a conversational interface.

The AI is trained on a huge sample of text taken from the internet.

OpenAI said the new AI was created with a focus on ease of use. "The dialogue format makes it possible for ChatGPT to answer follow-up questions, admit its mistakes, challenge incorrect premises, and reject inappropriate requests," the research body said.

What are No-Code and Low-Code Platforms?

No-Code and Low-Code platforms are types of visual software development environments that allow enterprise developers and citizen developers to drag and drop application components, connect them together and create mobile or web apps. These platforms are often discussed synonymously with the development methods they embody.

No-Code and Low-Code platforms approach let professional developers quickly build applications by relieving them of the need to write code line by line. They also enable business analysts, office administrators, small-business owners and others who are not software developers to build and test applications. These people can create applications with little to no knowledge of traditional programming languages, machine code or the development work behind the platform's configurable components.

Limitations

• ChatGPT sometimes writes plausible-sounding but incorrect or nonsensical answers. Fixing this issue is challenging because (1) during RL training, there's currently no source of truth; (2) training the model to be more cautious causes it to decline questions that it can answer correctly; and (3) supervised training misleads the model because the ideal answer depends on what the model knows, rather than what the human demonstrator knows.

• ChatGPT is sensitive to tweaks to the input phrasing or attempting the same prompt multiple times. For example, given one phrasing of a question, the model can claim to not knowing the answer, but given a slight rephrase, can answer correctly.

• The model is often excessively verbose and overuses certain phrases, such as restating that it's a language model trained by OpenAI. These issues arise from biases in the training data (trainers prefer longer answers that look more comprehensive) and well-known over-optimization issues.

• Ideally, the model would ask clarifying questions when the user provided an ambiguous query. Instead, OpenAI's current models usually guess what the user intended.

• While OpenAI has made efforts to make the model refuse inappropriate requests, it will sometimes respond to harmful instructions or exhibit biased behavior. OpenAI is using the Moderation API to warn or block certain types of unsafe content, but the company expects it to have some false negatives and positives for now.