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Review what is ChatGPT
ChatGPT is a language model based on OpenAI's GPT-3.5 architecture, designed to provide a wide range of language understanding and generation capabilities. It learns language patterns and contexts by training on large amounts of text data, and is able to answer questions, provide explanations, generate text, and more. The goal of ChatGPT is to have a natural and smooth dialogue with users, and to meet users' information needs as much as possible.
As a powerful language model, ChatGPT can be applied in multiple domains and scenarios. It can be used to answer frequently asked questions, provide facts and background knowledge, and help users solve problems and obtain information. It also enables creative text generation such as writing, story writing, and poetry. ChatGPT excels in language understanding and generation, and can adapt to different contexts and conversation topics.
Although ChatGPT has powerful language processing capabilities, it also has some limitations. Its answers and generation are based on its training data and as such can be subject to data bias and misleading. It may not provide up-to-date, time-sensitive information as its training data is as of September 2021. Moreover, it may not be able to provide personalized recommendations or specialized domain expertise due to the lack of real-time contextual and environmental information.
Despite these limitations, ChatGPT is still a very useful and flexible tool that can be used in a variety of scenarios, including education, entertainment, decision-making assistance, etc. It is able to interact with the user and provide meaningful answers and text generation based on the user's input.
1. Currently optimized items (feelings in use)
- Incorporate context (intensity enhancement)
- Fault Continuity (Optimization)
- Knowledge follow-up (before 18 years)
- Replenish
2. Combined with the context
ChatGPT uses context to answer questions by serializing and encoding the input. It is based on the Transformer architecture, which contains multiple encoder layers with self-attention mechanisms.
When a user asks a question, ChatGPT first encodes the question text. Then, it combines the encoded question with the previous dialogue history (context) to form a complete input sequence. The sequence includes previous dialogue turns and the current question.
The encoder processes this input sequence by learning the semantic and associated information in the context. It analyzes each word in the sequence and focuses on different parts to understand important contextual content. Through iterations of multiple encoder layers, ChatGPT is able to capture broader contextual information and form a comprehensive understanding of the question.
Based on the encoder's processing, ChatGPT can obtain relevant information from the context and generate appropriate answers. Generated answers may refer to previous conversations in order to be contextual and provide coherence. It can combine the knowledge of the language model and the linguistic patterns in the training data to generate appropriate, coherent and meaningful responses.
In this way, ChatGPT is able to leverage the context to understand the context, meaning and intent of the question and generate responses consistent with it. This context-sensitive answering mechanism enables ChatGPT to better adapt to diverse contexts and user needs in dialogue and question answering tasks.
3. Fault continuity
ChatGPT's fault continuity refers to its ability to maintain a certain degree of coherence and understanding when processing context in a conversation, and to continue to adapt and respond even in the presence of faults or interruptions.
This fault continuity is achieved through ChatGPT’s serialization processing and self-attention mechanism. When a new dialogue turn starts, ChatGPT combines the previous dialogue history with the current input to form a complete sequence. In this way, the model is able to understand the previous context and incorporate it into the current conversation.
Even when there are gaps or breaks in the conversation, ChatGPT is able to maintain contextual understanding and coherence as much as possible. This is because the model has a self-attention mechanism, which is able to assign attention weights at the encoder level, focusing on relevant parts, not just the most recent input.
This attention mechanism allows ChatGPT to capture contextual information across dialogue turns and use it to generate coherent answers. The model can address context changes and information loss caused by faults through a comprehensive understanding of previous dialogue history and current input.
Although ChatGPT has some fault continuity, it still has some limitations. Long dialogue histories may negatively affect the performance of the model and lead to confusion or loss of information. Furthermore, if the gaps in the dialogue are too pronounced or lack sufficient contextual clues, the model may misunderstand or generate inaccurate responses.
Therefore, when having a conversation with ChatGPT, it is important to maintain contextual coherence and provide a clear description of the question, which helps the model better understand and respond to your needs.
Obviously, compared with the previous fault-based continuation, this optimization can be said to be a very convenient function for the code, which greatly reduces the time to judge whether there is a problem in the fault during development.
4. Knowledge follow-up
The emergence of GPT4 obviously made this 3.5 tool start to grow. I believe that after continuing to collect relevant and useful data, the knowledge in 2023 is understandable.
Summarize
From these points, it can be found that in just three months, it has updated all five years of knowledge. At present, all parts of the world use OpenAI to call APIs to make their own artificial intelligence tools. Although it may be a bit offensive, I think it is still chatgpt in essence, and very few of them can add different functions or refreshing functions. Recently, Microsoft has also started to get in the limelight. The combination of WIN11+BING+CHATgpt does not know whether it will become the future evolution route. But I believe that AI will be everywhere in the future.
