ChatGPT

ChatGPT explained: What are its benefits and limitations?

ChatGPT is a machine learning model far more advanced than previous chatbots regarding conversational interaction. It is a sibling model to InstructGPT that follows prompt instructions and provides detailed responses. It is a variant of the GPT-3.5 language-generation software.

The dialogue format of ChatGPT allows for follow-up questions, challenging incorrect premises, admitting errors, and dismissing inappropriate requests. This machine learning model can help with various Natural Language Processing (NLP) tasks, and its high scalability makes it ideal for use in large-scale applications.

ChatGPT

Chatbots have been a source of fascination for decades. However, most of them are still relatively primitive, capable of answering rudimentary questions on help desk pages or addressing the issues of dissatisfied customers. However, the world of NLP is slowly entering a new chapter with ChatGPT’s ability to converse through multiple queries and generate software code.

Background

OpenAI’s ChatGPT: Artificial intelligence (AI) research firm OpenAI recently announced ChatGPT, a prototype dialogue-based AI chatbot capable of understanding and responding in natural language.

Soon will be able to implement in software: So far, OpenAI has only made the bot available for evaluation and beta testing, but API access is expected next year. Developers can integrate ChatGPT into their software with API access.

ChatGPT’s abilities are already quite remarkable, although it is still in beta testing. Besides amusing responses like the pumpkin one above, people are already finding real-world applications and use cases for the bot.

Benefits of Chat GPT

ChatGPT, as a machine learning model, can help with various NLP-related tasks. Because of its training on a large text dataset, it can understand and respond to multiple questions and requests. Some of its potential advantages are as follows:

  • Increased efficiency and precision in NLP-related tasks
  • Answers to a wide range of questions in a timely and accurate manner
  • Assistance with a wide range of tasks requiring natural language comprehension and generation.

Limitations of Chat GPT

ChatGPt’s ability to follow a conversation is noteworthy. However, as with many previous chatbots, it comes with its baggage:

Plausible sounding but incorrect information 

ChatGPT occasionally responds with plausible-sounding but incorrect information, and correcting this can be difficult because there currently needs to be a source of truth during RL training. 

However, if trained to be more cautious, it may end up declining questions that it can correctly answer. Furthermore, supervised training can lead to model misinterpretation because it focuses on what the model knows rather than what the human demonstrator knows.

Sensitive to minor changes in input

If the input phrasing is slightly changed or the same prompt is issued multiple times, the ChatGPT’s response may need consistency. In such cases, the model may claim not to know the answer or may correctly answer.

The problem of bias

The ChatGPT model can be highly verbose due to biases in the training data, over-optimization, and specific phrases overused. One example is that it frequently reiterates that it is a language model trained by OpenAI.

It needs to elicit clarification.

When a user enters an ambiguous query, the current model makes a guess. It should ideally ask clarifying questions.

Respond to inappropriate or harmful requests as follows.

While the model usually declines inappropriate requests, it occasionally responds to harmful instructions. Moderation API typically regulates unsafe content but sometimes exhibits false negatives and positives. The good news is that appropriate user feedback is being considered to improve the current system.

Will AI eventually replace all of our daily writing?

ChatGPT is only partially accurate: Even OpenAI admits it needs to be more precise. It is also clear that some of ChatGPT’s essays need more depth than an actual human expert might exhibit when writing on the same subject.

 

ChatGPT lacks the depth of the human mind and the nuance that a human can often provide. For example, when asked on ChatGPT how to deal with a cancer diagnosis. The responses were courteous but generic. These are the responses you’d find in any general self-help book.

It lacks human-like experiences: AI has a long way to go. After all, it lacks the same experiences as humans.
ChatGPT does not excel at coding: ChatGPT only writes basic code. As several reports have shown, ChatGPT has yet to quit there. However, a future in which basic code is written using AI appears plausible.