Deep Dive into AutoGPT: The Autonomous AI Revolutionizing the Game

8 min readApr 24, 2023

AutoGPT is a powerful tool that uses GPT-4 and GPT-3.5 via API to create full projects by breaking them into sub-tasks and using the internet and other tools in an automatic loop.

In this article, we will explore everything you need to know about AutoGPT, including what it is, how it works, and its benefits and limitations.

In order to use AutoGPT effectively, it is important to understand how its feedback loop works. In this article, we will explore the core of AutoGPT’s feedback loop and how it can be used to improve the accuracy and effectiveness of AutoGPT.

What is AutoGPT?

AutoGPT is an AI agent that can attempt to achieve a goal in natural language by breaking it into sub-tasks and using the internet and other tools in an automatic loop.

It uses OpenAI’s GPT-4 or GPT-3.5 APIs and is among the first examples of an application using GPT-4 to perform autonomous tasks. AutoGPT is a powerful tool that can automate the process of generating high-quality content quickly and efficiently.

It is among the first examples of an application using GPT-4 to perform autonomous tasks. AutoGPT can be used for a variety of tasks, including research, coding, and story improvement.

The core of AutoGPT’s feedback loop

AutoGPT is an AI-driven application that aims to revolutionize the way we approach problem-solving through a series of steps designed to optimize performance and accuracy.

One of the key features of AutoGPT is its feedback loop, which consists of five crucial steps: Plan, Criticize, Act, Read Feedback, and Plan. In this article, we will explain each of these steps and their significance in the AutoGPT feedback loop.

Plan: AutoGPT devises a plan for achieving the desired outcome, breaking down complex tasks into smaller steps.
Criticize: The plan is evaluated for feasibility and efficiency, identifying potential issues and areas for improvement.
Act: AutoGPT executes the planned actions using its multi-functional capabilities, such as web browsing and data retrieval.
Read Feedback: AutoGPT analyzes feedback generated from its actions, learning from previous performance to improve future outcomes.
Plan (Revised): Based on feedback, the initial plan is revised, allowing for continuous refinement of the problem-solving strategy.

Each of these steps is essential to the overall effectiveness of AutoGPT, and understanding how they work together is key to using AutoGPT effectively.

What is the mechanism behind Auto-GPT?

The mechanism behind Auto-GPT is centered around its use of GPT-4 or GPT-3.5 APIs. These powerful language models serve as the foundation for the AI agent, allowing it to understand and process natural language goals. By breaking these goals into smaller, manageable sub-tasks, Auto-GPT can tackle complex problems efficiently.

Autonomy through Self-Prompting:

One of the key features of Auto-GPT is its ability to self-prompt.

This means that the AI agent can operate with minimal human intervention, making it a versatile and useful tool for a wide range of applications.

Auto-GPT’s self-prompting capabilities enable it to adapt its approach based on new information or resources, allowing it to navigate through tasks and achieve the desired outcome.

Internet and Tool Integration:

To further enhance its capabilities, Auto-GPT also utilizes the internet and various tools to assist in completing tasks.

This integration allows the AI agent to access a wealth of information and resources, ensuring that it can find the most relevant and accurate data to support its problem-solving process.

How AutoGPT works?

AutoGPT is powered by GPT-3.5, a state-of-the-art language model that is capable of generating high-quality text in a wide range of styles and formats. It can be used to automate a wide range of tasks, from writing articles to generating code.

It starts by iterating on its own prompts and building upon them in each iteration, which enables the AI to generate new ideas and concepts based on previous work.

Three Key Inputs:

AutoGPT requires three main inputs from the user:

AI Name
AI Role
up to five goals

The AI Name and AI Role define the specific purpose and functionality of the AI agent, while the goals provide a clear outline of the tasks to be accomplished.

The Execution Agent:

Each task is managed by an “Execution Agent” (GPT-4), which provides input to one or more other GPT-4 agents[4]. This approach allows for the addition of new sub-tasks to be completed by the agent, ultimately enabling AutoGPT to unravel complex tasks and achieve the desired outcome.

The Reasoning Stage:

Once a prompt is generated, AutoGPT moves on to the “reasoning” stage[5]. At this stage, the AI analyzes the prompt and formulates a plan to achieve the desired outcome. The process involves breaking down the prompt into smaller sub-tasks, which the AI then executes autonomously.

How to install and run Auto-GPT

Auto-GPT is an experimental open-source application that leverages the power of GPT-4 and GPT-3.5 to perform tasks autonomously without human input.

Github source code： https://github.com/Significant-Gravitas/Auto-GPT
Creator：https://www.significantgravitas.com/

Step 1: Set up API keys

Before installing Auto-GPT, you will need to obtain API keys for OpenAI.

Step 2: Install Auto-GPT

To install Auto-GPT, you will need to download the application from its official repository on GitHub

Open your terminal and run the following command:

$ git clone https://github.com/your-repository/auto-gpt.git

Next, navigate to the downloaded folder and install the required packages using the following commands:

$ cd auto-gpt
$ pip install -r requirements.txt

Step 3: Configure Auto-GPT with API keys

Once you have installed Auto-GPT and defined the AI’s role and goals, you will need to configure the application with your OpenAI and PineCone API keys. Edit the configuration file (e.g., config.yaml) again with a text editor, and input your API keys in the appropriate fields. Save the file and close the text editor.

Step 4: Run Auto-GPT and monitor the results

With everything set up, you can now run Auto-GPT and let it perform the tasks autonomously. To run Auto-GPT, use the following terminal command:

$ python auto_gpt.py
or
$ ./run.sh

Monitor the results and provide feedback to the AI, if necessary, to refine its performance and improve its understanding of the given objectives.

Limitations of Auto GPT

Auto-GPT lacks the ability to convert a chain of actions into a reusable function for later use, making it inefficient and costly for users to start from scratch each time they want to solve a problem.

This limitation highlights an unrealistic expectation compared to problem-solving in the real world, wasting both time and money.

Unfortunately, Auto-GPT’s current implementation does not allow for the separation of development and production, forcing users to pay the full cost for minor changes.

This raises concerns about its practicality in real-world environments and highlights its limitations in providing a sustainable and cost-effective solution for large-scale problem-solving.

Is Auto-GPT truly cost-free?

Auto-GPT offers impressive capabilities, but its high cost presents a significant hurdle to its practical use in production environments. The GPT-4 model, which Auto-GPT relies on, can be expensive as each step in a task requires a call to the model, which often maxes out tokens to provide better reasoning and prompting. GPT-4 tokens are charged at $0.03 per 1,000 tokens for prompts and $0.06 per 1,000 tokens for results. For example, a small task requiring 50 steps, with each step maxing out the 8K context window, would cost $14.4.

This cost can quickly add up, making Auto-GPT’s current implementation unaffordable for many organizations and users. While Auto-GPT shows great promise, its cost is a significant barrier that needs to be addressed before it can be widely adopted.

The Key Differences Between ChatGPT and Auto-GPT

ChatGPT and Auto-GPT applications built on Generative Pre-trained Transformer (GPT) technology.

While ChatGPT and Auto-GPT share a common foundation, they differ significantly in their functionality and purpose.

The Differences Between ChatGPT and Auto-GPT, Autonomy, Application and Accessibility

1.Autonomy:

One of the most striking differences between ChatGPT and Auto-GPT lies in their level of autonomy.

ChatGPT is designed primarily for chatbot applications and requires human prompts to generate responses and complete tasks.

Auto-GPT, on the other hand, can function autonomously without human intervention. It generates its own prompts to achieve the given goals, making it capable of independently completing tasks without constant guidance.

2.Application

ChatGPT is specifically designed and optimized for dialogue, making it an ideal choice for chatbot applications.

Auto-GPT, conversely, is built to perform a wider range of tasks autonomously. It can access websites and search engines to gather data required to complete tasks, making it a versatile tool for various purposes.

3.Accessibility

Auto-GPT is an open-source project, which allows developers the freedom to modify its code and tailor it to their specific needs.

ChatGPT, however, may have more restrictions depending on the platform it is being accessed from.

Final, Why I stoped using AutoGPT?

In conclusion, my initial experience with AutoGPT was quite impressive due to its ability to understand my goals, generate prompts automatically, and fetch the most recent information from the internet. The simplicity and ease of use, along with its internet connectivity, made it an appealing tool for automating tasks and enhancing productivity.

However, after using AutoGPT for a couple of days, I found some limitations that led me to stop using it. Firstly, the speed at which AutoGPT operates can be slow, taking up to 2–4 minutes to scrape and analyze a few articles from the internet, whereas manually searching for and selecting articles takes me about a minute. Secondly, the costs associated with AutoGPT can be quite high, especially when using the OpenAI API. In just one morning, I ended up spending $1 on API usage.

In summary, while AutoGPT has some remarkable features and potential for automating tasks and improving productivity, its limitations in terms of speed and costs may deter some users from adopting it for long-term use. Users should carefully evaluate their needs, requirements, and budget before committing to using AutoGPT extensively.