Baby AGI up and running in 5 minutes with just Colab: Pioneering the Path to Artificial General Intelligence

Exploring the revolutionary issue management system and its implications for the future of AI

Introduction

The development of artificial intelligence has experienced a surge in recent years, and distinctions have been made between Artificial Narrow Intelligence (ANI) and Artificial General Intelligence (AGI). ANI is focused on a specific domain, while AGI possesses the potential to understand, learn, and apply intelligence across diverse domains. Baby AGI is one of the first attempts at achieving AGI using OpenAI. In this article, we’ll delve into the Baby AGI project, its use cases, and its components, including Task Creation, Prioritization, and Execution agents. We’ll also demonstrate how to set it up in Google Colab within just five minutes.

ANI vs. AGI: The Shift Towards General Intelligence

Artificial Narrow Intelligence (ANI) refers to AI systems that are designed to perform specific tasks within a particular domain. These AI models excel in their domain but struggle when confronted with tasks outside their area of expertise.

Artificial General Intelligence (AGI), on the other hand, aims to create an AI system capable of understanding, learning, and applying intelligence across a wide range of tasks and domains, similar to human intelligence. Baby AGI is a groundbreaking project, seeking to harness the power of OpenAI in pursuit of AGI.

Introducing Baby AGI: A Leap Towards Artificial General Intelligence

Baby AGI is an advanced “issue management” system, designed to revolutionize the way businesses and organizations approach problem-solving. Instead of focusing on a specific task domain, Baby AGI aims to address diverse issues autonomously.

Use Cases for Baby AGI

1. Product development: Baby AGI can streamline the process of creating and launching new products by automatically generating a list of necessary steps, prioritizing them, and executing each step based on context and objective.
2. Customer service: Baby AGI can efficiently manage customer inquiries by identifying issues, prioritizing responses based on urgency, and providing context-sensitive solutions.
3. Marketing campaigns: Baby AGI can help design and execute marketing campaigns by generating relevant tasks, prioritizing them, and providing data-driven insights to optimize campaign performance.

Baby AGI’s Core Components: Task Creation, Prioritization, and Execution Agents

1. Task Creation Agent: This agent uses OpenAI’s API to create new tasks based on current objectives and the outcome of previous tasks. It takes four parameters: objective, outcome of the previous task, task description, and the current task list. A prompt is sent to OpenAI’s API, which returns a list of new tasks as strings. The agent then returns these tasks as a list of dictionaries.
2. Prioritization Agent: The prioritization agent orders and prioritizes the list of tasks. It uses OpenAI’s API to reprioritize the task list by taking one parameter: the ID of the current task. After sending a prompt to OpenAI’s API, it returns the newly prioritized task list as a numbered list.
3. Execution Agent: The execution agent serves as the core of the system, using OpenAI’s API to process tasks. It takes two parameters: the objective and the task. It sends a prompt to the OpenAI API, which returns the task result as a string.

Image by Yohei (Creator of Baby AGI)

Setting Up Baby AGI in Google Colab in 5 Minutes

Follow these steps to set up Baby AGI in Google Colab:

1. Open Google Colab and create a new Python 3 notebook.
2. In the first cell, enter : !git clone https://github.com/fenago/babyagi.git
3. In the next cell, enter: %cd babyagi
4. Then, execute: !pip install -r requirements.txt
5. From here, you are going to need to add your pinecone and openai keys:

!cp .env.example env.txt
# then open the txt file and add the keys

This will create env.txt in your folders. Open that and add your keys

6. Once your keys are added to env.txt — you must copy it back into .env:

%cd babyagi   # If you have to reset your env, make sure to cd back into babyagi
!cp env.txt .env

6. Run the babyagi.py script and you have your autonomous automation:

!python babyagi.py

If you want another goal (as opposed to Solve world hunger) then edit .env with your new goal.

Conclusion

Baby AGI marks an important milestone in the pursuit of Artificial General Intelligence. By leveraging OpenAI, this issue management system can autonomously generate tasks, prioritize them, and execute them according to predefined objectives. With potential applications in various domains, Baby AGI showcases the power and potential of large language models like GPT. As we continue to explore the limits of AI and strive towards AGI, projects like Baby AGI offer a glimpse into the future of artificial intelligence and its impact on industries around the world.

Image by Yohei (Creator of Baby AGI)