Introduction to AI Agents: Getting Started With Auto-GPT, AgentGPT ...
AI agents such as Auto-GPT, AgentGPT, and BabyAGI are the latest advancements in the fast-paced world of AI. These agents are designed to work independently towards a goal with minimal or zero human input.
Auto-GPT is the fastest-growing open-source project in history, with 107,000 GitHub stars since its development began six weeks ago. Developers worldwide have recognized the potential of this new technology, as it provides the AI agent with internet access and the ability to run code, allowing it to solve a more comprehensive range of problems.
What are AI Agents?
AI agents are applications powered by large language models (LLMs) like GPT. They are designed to reduce the number of human interactions required for AI to complete a task. AI agents like AgentGPT and BabyAGI use GPT on a loop, where it is repeatedly called to break the user's request into solvable problems. The output from each step is refined until each subtask is completed successfully.
Auto-GPT takes this one step further by providing the AI agent with internet access and the ability to run code. It can perform research for itself via the Google Search API and execute shell and Python code, enabling it to write code and run it.
How Do AI Agents Work?
AI agents work by using an embedding workflow to store the text of the conversation as numbers. Each user prompt or AI response is stored as an array that represents the meaning of the text. These numeric arrays are stored in a vector database like Pinecone, which Auto-GPT and BabyAGI use, and the AgentGPT team is developing support for this feature.
AI agents generate words based on previous words in the conversation, and they have memory capabilities that LLMs lack. LLMs have short memories, but AI agents have an embedding workflow, which stores the entire conversation and can even remember previous conversations. Additionally, Auto-GPT can browse the web to find answers to questions, making it a helpful tool for current events or information.
Examples of Using AI Agents
It is still early days to figure out how to use AI agents. Examples so far are mostly variations of an automated personal assistant, like a next-generation IBM Watson Assistant.
Udit Goenka, the CEO of FirstSales.io, posted on Twitter that he used Auto-GPT to build a prospecting engine. The AI agent created a plan to search for companies that raised seed capital in the last year and extracted company names and URLs to create a list.
Similarly, Yew Jin Lim, a software engineer at Google, used Auto-GPT to create an email assistant. The AI agent performed tasks like adding an event to his calendar after receiving an email with details of the task to complete.
Things to Keep In Mind
While AI agents offer great potential, it is essential to keep some things in mind. Using any of the three AI agents discussed here to perform a complex task could involve hundreds or thousands of API calls.
It is a good idea to include breakpoints where human intervention is needed to provide permission for the AI to continue running. Auto-GPT can be provided with access to any API, but it is essential to avoid granting it access to perform tasks like buying stocks on your behalf or gaining write-access to your corporate database.
Some researchers argue that advanced AI provides larger or even existential threats. While initial attempts to use Auto-GPT to destroy humanity have been unsuccessful, it's worth bearing in mind the warning from Eliezer Yudkowsky, a Senior Research Fellow at the Machine Intelligence Research Institute.
In summary, AI agents are an exciting development that enables AI to work independently towards a goal with minimal human input. Auto-GPT is the fastest-growing open-source project, and developers worldwide recognize its potential. While the possibilities are endless, it is essential to take precautionary measures when utilizing this technology.
