AutoGPT is an artificial intelligence (AI) agent that can complete complex tasks without human intervention. You can ask AutoGPT to research difficult topics, suggest an investing allocation suitable for your personal situation, or create a gluten-free menu for your next dinner party.
Intrigued? Read on to learn more about AutoGPT and why the internet is abuzz about this next-generation AI tool.
Artificial Intelligence
What is AutoGPT?
What is AutoGPT?
AutoGPT is an open-source application that interfaces with GPT-4 and GPT-3.5, which are ChatGPT language models. But ChatGPT requires specific, human-written prompts; AutoGPT does not. Given a higher-level goal, AutoGPT self-generates the necessary prompts to reach the goal. The application then works through those prompts one by one.
As it works, AutoGPT gathers data to refine or validate its prompts and their outputs. The application then iterates until it completes the tasks and the top-level goal. As needed, AutoGPT will connect to and control other applications -- including your web browser. It can also store data in short- and long-term memory for processing later.
Two capabilities make AutoGPT buzzworthy and slightly creepy:
- It can plan the steps required to achieve a goal.
- It can learn and improve on its own results.
Implications of AutoGPT
Implications of AutoGPT
AutoGPT has far-reaching implications for businesses and individuals. The differentiator from other mainstream AI tools is AutoGPT's feedback loop that allows it to plan, learn, and improve.
With that approach, AutoGPT can streamline many processes that are labor-intensive for humans. For businesses, these include writing and debugging code, creating content, analyzing data, and developing business plans. Individuals can use the autonomous AI agent to help with budgeting and investing, event planning, and price research.
That's the optimistic view. The other side of the story is that AutoGPT today is in the earliest stages of its development. Outputs and actions taken by the AI agent could potentially be inaccurate or counterproductive.
AutoGPT also processes information literally, which can be problematic in decision-making scenarios. Consider the question of risk tolerance. Novice investors who haven't been through a major market downturn might tell AutoGPT they have a large appetite for risk. AutoGPT would accept that input and make recommendations accordingly.
A human financial advisor, on the other hand, can test and confirm that answer with additional probing questions, such as, "How would you feel if your portfolio dipped from $100,000 to $70,000 overnight?"
Deep Learning
How can I use AutoGPT?
How can I use AutoGPT?
AutoGPT is free and available for anyone to use, but it is not accessible from a web browser. You must install AutoGPT locally.
You also must set up an account with OpenAI to create API keys. Those keys facilitate AutoGPT's access to the ChatGPT language models.
There is a cost for connecting to the OpenAI APIs. GPT-4 API charges range from $0.03 to $0.12 per 1,000 tokens -- or about 750 words -- used.
You can find many online tutorials that walk through the AutoGPT installation process. The main steps are:
- Download a package manager.
- Download and install Git and Python.
- Download, install, and configure AutoGPT. Configuration involves updating a system file to include your OpenAI API key. You can then monitor your API usage and related costs in your OpenAI account.
The installation process can be intimidating for non-technical users since it all happens in the terminal. The text-based terminal is also where AutoGPT runs.
AutoGPT in practice
AutoGPT in practice
When you open AutoGPT, your first action is specifying a goal. The prompt is "I want Auto-GPT to:." I told the application to design a $100,000 investment portfolio with allocations for stocks, bonds, and cash -- assuming I have 20 years until retirement and I want to build wealth.
From any prompt, AutoGPT will return its thoughts, reasoning, plan, and criticism. In my test case, the application responded with the following:
- Thoughts: As an investment advisor, I should start by analyzing the current market conditions and reviewing the client's financial goals and risk tolerance. This will help me determine the appropriate asset allocation for their portfolio. I should also consider the client's time horizon and any specific investment preferences they may have.
- Reasoning: Analyzing the market and the client's financial goals and risk tolerance is the first step in developing an appropriate investment portfolio.
- Plan:
- Analyze the market conditions.
- Review the client's financial goals and risk tolerance.
- Consider the client's time horizon and investment preferences.
- Develop an appropriate asset allocation for their portfolio.
- Criticism: I need to ensure that I am taking into account all relevant factors when developing the investment portfolio and that I am not making any assumptions or taking unnecessary risks.
So far, so good. AutoGPT then put the plan into motion by using Google to collect information on the current market conditions.
Next, the application created a text file where I could document my financial goals, risk tolerance, time horizon, and investment preferences.
Here's where things go sideways. For some reason that's unclear, AutoGPT didn't stop and wait for my input but updated the text file on its own. It noted a moderate risk tolerance, long-term time horizon, and three financial goals: Save for retirement, buy a house, and pay for children's education.
In real life, only the retirement goal is applicable to me.
Still, AutoGPT kept working to answer the initial prompt of suggesting an asset allocation. Its recommended portfolio composition was 60% stocks, 30% bonds, and 10% cash. It also started researching specific holdings to fulfill the allocation but errored out and shut down -- not an ideal way to end my AI financial consultation.
Although AutoGPT is interesting and promising, the technology is still in its infancy. Despite its power to solve problems, it can make mistakes, misinterpret information, get diverted into nonessential tasks, and ultimately fail to reach the stated goal. In AutoGPT's current state, you could argue the application is more human in its flaws than in its capabilities.
