What Drawbacks Does ChatGPT-3.5 Have?

ChatGPT-3.5 has caused quite a stir with its ability to perform a variety of tasks. These include answering user questions, writing songs and poems, translating, generating computer code and interacting in a human-like manner. However, despite the advanced features of this AI chatbot, there were still a few critical limitations that affected its performance and accuracy. We're going to dive into each of them. Inability to understand the context. ChatGPT-3.5 struggles to understand the subtle nuances of human language. It doesn't grasp the context when it consists of jokes or sarcasm. The problem is that it does not think the way people do and does not have the imagination to get the idea behind indirect sayings. Problems with generating long and structured texts. GPT-3 has been trained in a way it can produce longer responses. But in reality, when you ask it to give a lengthy answer to your questions, it starts repeating the same information over and over. So the output is long, but the context is vague and inaccurate. ChatGPT-3.5's shorter replies, on the other hand, can be quite informative. Unable to handle multiple tasks simultaneously. OpenAI's chatbot operates best if you give it only one task to work on. Trying to get multiple answers to your questions at once will reduce its accuracy and effectiveness. It's trained to perform one specific task at a time, such as answering questions or generating text. When ChatGPT is asked to perform multiple tasks simultaneously, it may become confused and give inappropriate or irrelevant responses. Generate biased data. The data used to train ChatGPT originally consisted of biases and prejudices. The training data reflects historical inequalities or stereotypes present in society. That's why, we can't expect the chatbot to give us completely objective outputs. Grammatical and accuracy troubles. Since ChatGPT is only a language model, it generates texts from vast amounts of training data. It originally may contain grammatical errors and misspellings, and due to the limitations of current AI technology, the chatbot isn't able to detect and fix these issues. In addition, ChatGPT generates responses based on probabilities, which means that the model may occasionally generate outputs that are grammatically incorrect or contain typos.

What Makes ChatGPT-4 Better Than ChatGPT-3.5: 3 New Functionalities

Longer Context OpenAI's new chatbot is capable of processing up to 25,000 words at once, which is 8 times more than its predecessor managed. In this way, GPT-4 can be successfully used for larger content creation, document search and analysis and longer conversations. Thanks to an advanced deep-learning approach that uses more data and more computation, OpenAI's GPT-4 can process longer inputs and generate more coherent and contextually appropriate outputs. Visual Inputs GPT-4 accepts not only text inputs, but also images, and can create labels, analyzes and classifications. For instance, you can provide a picture of different products and ask the chatbot what dish you can make from them. The parallel use of text and images allows users to better specify what they want to ask ChatGPT and what they want to receive as an output. The language model can handle a wide variety of visual documents, including infographics, photos, diagrams and screenshots. This new feature is still in its infancy, however, as it requires more research and revision to make it work accurately. The software is capable of labeling objects on an image, but you can't expect it to describe your image in a coherent way. Better Creativity ChatGPT-4 offers a higher level of creativity than its predecessor. Users can effectively collaborate with it to write multiple pieces of content that require originality: poems, songs, or screenplays. The chatbot is able to give surprising, clever and imaginative answers and come up with novel ideas or concepts that people may not have even thought of. However, the model hasn't yet reached the creativity of humans, because it can't provide users with truly breakthrough outputs, as they're ultimately the result of its training data and programming.