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In March of this year, OpenAI officially integrated a plug-in system (Plugins) on ChatGPT, which is regarded as its first step in building an AI empire.
At that time, in addition to the online plug-in system, OpenAI also presented two sincere works of its own: Web Browsing and Code Interpreter .
Not long ago, the web browsing plug-in was opened to all Plus users, allowing everyone to retrieve various data on the Internet in real time and interact with AI directly through ChatGPT.
With the birth of a series of plug-ins for network data access, the original functions of this tool are no longer eye-catching, and often due to the restrictions of various crawler rules, data capture fails, which is insignificant, and has gradually been used by users. Abandon it and use the more practical WebPilot instead.
Another plug-in released by OpenAI: the code interpreter, may be due to the influence of the user audience. After its release, it has received little attention from non-programmers. But in my personal opinion, this plug-in is the strongest plug-in that OpenAI can really take out.
Even today, in the current situation where various ChatGPT plug-ins are flourishing, the functional performance of this code interpreter is still outstanding for both programmers and ordinary users.
OpenAI also officially announced yesterday that this plugin will be officially open to all Plus users next week! Some people are already using it.
Let's review the power of this plugin again.
Code Interpreter (Code Interpreter) is a particularly powerful professional plug-in that allows you to directly use functions to generate various visual data charts by talking to ChatGPT.
It can also automatically acquire and analyze data content based on the Excel and CSV data you upload, produce a professional industry analysis report for you, and generate a variety of data charts in different styles, allowing you to more easily and directly understand the data hidden information, greatly saving workload.
Not only that, this plugin also supports uploading pictures, dynamically adjusting the size, grayscale, tone and other styles of pictures online, and generating download links for you.
Through it, you can enable ChatGPT to perform operations such as data analysis, chart creation, file editing, and mathematical operations, and it can also be interconnected with other plug-ins to create more and richer automated data analysis scenarios.
For example, you can use it to upload a video file, and let it call Python code to analyze and cut the video file online.
The invocation model of the code interpreter is placed in a sandbox protected by a firewall and allocates a small amount of temporary disk space.
The advantage of this is that users can use this plug-in to run various Python codes directly in ChatGPT in a safer way.
When the user communicates, the code will be saved in the persistent session, and it can be called at any time without interrupting the communication, further expanding the usage scenarios of ChatGPT.
Therefore, some people commented: "ChatGPT with a code interpreter is "the most useful and interesting artificial intelligence model I have ever used".
How about the specific effect, here I will put an official demonstration video for everyone to see.
The following video mainly demonstrates three parts:
Generate and modify charts through functions;
Parse the contents of the CSV file, obtain and analyze tabular data, and generate visual charts;
Upload pictures, dynamically adjust picture size, gray scale, tone, and generate download links.
At present, many users have begun to use this plug-in to analyze search engine algorithms, user behavior and various index rankings to monitor the dynamics of competitors, seek product differentiation, and continuously optimize and iterate their own products to explore more many potential users.
For developers, its original intention is quite similar to GitHub Copilot X, both to use AI to create a tool that can help people improve work efficiency.
Because it can automate complex analysis, merge and clean data, and even reason about data in a human-like way.
After the "code interpreter" is officially released next week, more interesting and practical application scenarios should be born. At that time, we will discuss and share the tutorial and practical usage of the plugin with you in the community.
Since the AIGC is quite popular this year, we have also established an AI community to explore more prospects and applications in the field of artificial intelligence.
If you want to learn more about practical AI technologies and applications, as well as new developments in ChatGPT, you can click the link below to join our community for further discussions.
Community entrance: ChatGPT community, officially launched!
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