Last week, OpenAI introduced a new chatbot called ChatGPT. ChatGPT is a large language model trained by OpenAI. It uses state-of-the-art natural language processing techniques to generate human-like responses to input text. ChatGPT is designed to be able to hold a conversation on a wide range of topics and can provide helpful information and answer questions. It is not a real person, but a sophisticated piece of artificial intelligence software.
ChatGPT’s ability to answer questions and generate text is based on its training and its ability to process and analyze language data. By leveraging the latest advances in natural language processing and machine learning, ChatGPT can provide human-like responses to a wide range of questions and statements.
Note: A profile created by OpenAI
It is interesting to note that ChatGPT has been trained to decline inappropriate requests, such as those that may be illegal in nature. However, it is important to remember that ChatGPT is not perfect and may sometimes generate incorrect information or biased content. Additionally, ChatGPT’s knowledge of the world and events after 2021 is limited, as its training data only goes up until that year. These limitations should be kept in mind when interacting with ChatGPT and relying on its responses.
Since ChatGPT is so competent, did you notice these paragraphs above were written by ChatGPT? Even the all pictures above that is created by DALL·E, a deep learning models developed by OpenAI to generate digital images from natural language descriptions.
Except for producing human-like text based on inputs, ChatGPT can also write some slightly more complex code out, such as a grid trading bot or even an MEV Bot.
If we try to enter a specific requirement in the Input field, such as “write a grid trading bot with Binance API”, we can get the following Python version of a grid buying code template (it will even tell us what kind of ideas it implements). But note that even if you enter the same command each time, you get a different version of the code, but chatGPT gives you the same idea for the same problem.
The following figure shows a part of the code.
We can continue to type “optimize the code above” to let the AI automatically optimize the above code. This process will be repeated two or three times until you are satisfied. We will see that chatGPT will give us ideas for each optimization, and the optimized code will become more concise.
So, can it handle MEVBOT if it encounters a higher complexity? Let’s type “Write an MEV BOT in python” and find that the MEV bot we get is not the maximal extractable value we know is on the chain, but the traditional grid trading bot based on Binance.
In general, ChatGPT is really capable. And with the continuous improvement of deep learning models, the promotion of open source models, and the possibility of commercialization of large model exploration in the future, ChatGPT is expected to accelerate its development.
Dr. Techy stronly highly recommended all of you guys to have a try with ChartGPT and have a conversation with AI!
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