I have been exploring two highly active applications on GitHub for the past week: Auto-GPT and AgentGPT, and trying to deploy them on my local machine. After using these applications, here are my impressions:
Auto-GPT is a console-based program that generates questions based on the user’s central idea and searches for answers using ChatGPT. It was designed for the GPT-4.0 model and is also backward-compatible; it can use the GPT-3.5 model. AutoGPT has various built-in interfaces like Pinecone and DALL-E, which provide efficient search caching, image generation, and many other interfaces. The program’s most impressive feature is its ability to generate questions based on user requests and, using Google’s search engine, provide more specific requirements for the GPT-3.5 or GPT-4.0 models. AutoGPT can also generate multiple assistants and handle multiple workflows simultaneously.
This program is an effective model training tool, connecting GPT to the network, and provides a seamless workflow. However, the program’s main issue is its output; it is often unsatisfactory or may not be produced at all, and the generated outputs for different projects can be chaotic. Most importantly, the program seems unable to define a perfect or correct standard for the output, turning the entire task into an infinite loop. This is currently the most significant issue that needs to be resolved in the program.
On the other hand, AgentGPT is a web-based UI interface that uses the AutoGPT kernel. It addresses some of Auto-GPT’s interface issues and offers better display quality and ease of use. However, it shares the same drawbacks as Auto-GPT. AgentGPT is not deployed locally, making it more challenging to obtain results.As we delve deeper into the exploration of GPT, I believe that a truly usable version will be available soon.
AI is really here, and I am confident of this.
