GPT4 hasn't figured it out yet, everyone is starting to switch to AutoGPT?
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Since I started following ChatGPT in December last year and had my first hands-on experience, I have been particularly concerned about some new changes in the AI field. To this end, I have also dug out some friends in my circle who specialize in AI products and technologies and formed a small group
Since I started following ChatGPT in December last year and had my first hands-on experience, I have been particularly concerned about some new changes in the AI field. To this end, I have also dug out some friends in my circle who specialize in AI products and technologies and formed a small group.
Over the past week, I have noticed that everyone is closely following a new project called AutoGPT. Moreover, these people almost daily share their task execution results in their social media or groups.
So, what is AutoGPT? What is its relationship with ChatGPT?
Here, I would like to briefly talk to you.
AutoGPT is an open source project based on GPT-4 capabilities, which can currently be downloaded, deployed, and installed through Github.
It can be seen that the current number of Stars for this project has exceeded 35k, and it has also gained popularity in foreign circles.

The biggest feature of AutoGPT is its ability to autonomously analyze and execute task instructions, and even ask new questions and answer them on its own.
This is different from ChatGPT. In ChatGPT's interaction mode, you propose an instruction, ChatGPT gives a response, and then you give it back.
The interaction mode of AutoGPT is when you propose a requirement or task, and it does not rush to give you an answer. Instead, it analyzes the problem, provides execution goals and specific tasks, and then begins execution.
Note that it will actually start executing.
For example, a foreign tester created a website through AutoGPT, and when he entered his own requirements, AutoGPT directly called the React framework to generate a front-end page.

AutoGPT also provides a capability to achieve storage. It can be understood as giving a GPT based model memory, and you can train an AI assistant locally to help you complete some daily execution tasks.
Because using the deployment process requires completing some development configurations and having OpenAI API keys, it is not very user-friendly for ordinary white users.
So, you can experience another AutoGPT based replacement product, AgentGPT.
This is a browser based tool, but it also requires OpenAI API keys to achieve long-term access and complete processes.
However, it doesn't matter if you don't have it. You can skip and experience the general process first.

You can give your AI a name and enter the tasks you want it to help you complete in the Goal input box.
For example, I asked it to help me achieve a goal of 'understanding what programmers mean by APIs'.
The system did not rush to provide an answer, but instead began to think and independently added three subtasks.

Among these three subtasks, one is to study the definition of APIs from trusted channels; One is to collect information about the specific applications of APIs in programming; Another aspect is to provide a comprehensive and detailed explanation of the specific significance of APIs in software development.
Next, AgentGPT began to independently execute its first sub task, searching for accurate definitions of APIs on the internet and providing information source URLs.

After the completion of the first subtask, AgentGPT began to automatically execute the second task, looking for some cases to help me understand.
From the execution results of the subtask, it can be seen that it provides examples of APIs used in application scenarios by Google Maps, Twitter, Facebook, and Amazon.

Finally, it automatically executed the third subtask, providing a comprehensive explanation of what the API really is.
Then I provided it with a new goal of calculating how many taxis there are in Beijing, and also raised this issue to ChatGPT.
It should be noted that neither of these experimental environments was completed based on GPT-4, and switching to GPT-4 would result in better results.

In AgentGPT, this issue is also divided into three subtasks.
One is to search through official channels, the other is to use computer vision recognition to call traffic surveillance cameras for statistics, and the other is to estimate the number of taxis in Beijing based on usage patterns using crowdsourcing data from taxi applications.
Obviously, these data are difficult to obtain, or even impossible to obtain, but at least AgentGPT provides some paths and ideas.
The same question was raised to ChatGPT, which was speechless.

So, derivative products like AutoGPT and AgentGPT represent smarter, more flexible, stronger execution, and higher efficiency.
In addition, regarding the important issue I mentioned earlier regarding the ability to write prompts, the emergence of AutoGPT may have given me a slap in the face.
From this perspective, writing a prompt is no longer an advantage for humans, but rather proposing accurate questions and goals.
The rest can be handed over to AI.
In my opinion, the biggest significance of AutoGPT lies in showcasing a possibility for us, which is the logical coherence of AI and its ability to serve vertical scenarios.
Perhaps this is also why some people call this "AI agent".
We ask about AI understanding, AI analysis, AI execution, and AI validation.
Perhaps the future is such a cyclical path.
It is said that GPT-5 will come this year, and our cognition and judgment may be refreshed at that time.
The future is every present that is happening.
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