I was closely following the AI community at that time, and a recent letter that urged a pause on AI development provoked my thoughts.

# Introduction

The rapid pace of AI development, especially after the release of GPT-4, has been nothing short of breathtaking. As an avid follower of the AI community since the inception of ChatGPT, I have been amazed by the incredible tools and papers that are being released week after week. However, amidst the excitement, a recent open letter calling for a halt to AI development for at least six months has made me pause and reflect on the direction in which AI is heading and has sparked my curiosity about what the future of AI will look like.

As I took a step back from eagerly following the rapid pace of AI advancements, I realized the need to gain a deeper understanding of what AI truly entails. AI, or artificial intelligence, encompasses the creation of computer systems that possess the ability to perform tasks that traditionally require human intelligence, such as language comprehension, pattern recognition, and decision-making. With remarkable advancements in machine learning and deep learning, AI has made significant strides in various domains, ranging from natural language processing and image recognition to autonomous vehicles and robotics.

# Behind the Curtain

Indeed, when it comes to AI, there are numerous subfields and applications to explore. However, for the purpose of this discussion, it is relevant to narrow the focus on ChatGPT, which has emerged as one of the most recent and highly regarded language models (LLMs) in the AI community. What sets ChatGPT apart and contributes to its exceptional performance compared to its competitors Bard and Claude are three of the key factors: large-scale labeled training data, continual improvement through fine-tuning, and the innovative concept of Chain- of-Thought. While the first two factors are important, I would like to focus on Chain-of- Thought as it is a significant aspect that will be further discussed in relation to AutoGPT.

Jason, a prominent AI researcher who is part of the team working on ChatGPT at OpenAI, made a noteworthy discovery in his paper (Wei et al., 2022)[1]: traditional prompting methods often require the model to solve complex multi-step problems in one step, which contrasts with the human cognitive approach of solving complex reasoning problems in a step-by-step manner. In response, Jason proposed a simple yet effective prompting method that explicitly incorporates the human thought process, known as “chain of thought,” into the prompt message using natural language. This innovative approach allows for a more human-like reasoning process in large language models like ChatGPT, leading to improved performance and enhanced problem-solving capabilities.

According to the research findings, the use of chain-of-thought prompting does not have a positive impact on performance for smaller models, and only results in performance gains when applied to models with approximately 100 billion parameters. The qualitative analysis revealed that smaller-scale models generated coherent but logically inconsistent chains of thought, leading to lower performance compared to standard prompting methods. However, the use of chain-of-thought reasoning showed promising results at larger model scales, and chain-of-thought prompting demonstrated greater performance gains when applied to more complex problems.

The possibility of the non-open source version of ChatGPT being customized for user inputs and tasks, with implicit Chain-of-Thought (CoT) prompting, cannot be ruled out. This could potentially guide the large language model to achieve more prominent performance.

# AutoGPT: The future of AGI?

AutoGPT is a Python application that is designed to operate autonomously using GPT-4, a powerful language model. It has been developed as an experimental open-source tool that requires minimal human intervention. One of the unique features of AutoGPT is its ability to self-prompt, which means it can generate prompts on its own to complete a given task. Users can simply specify the desired end goal, and AutoGPT will automatically generate all the prompts needed to achieve that goal. This capability makes AutoGPT a highly autonomous tool with the potential to streamline and simplify various tasks.

According to information shared in a Github post (Significant-Gravitas, 2023)[2], AutoGPT boasts features such as internet access, long-term and short-term memory management, text generation using GPT-4, and file storage and summarization capabilities with GPT-3.5. The wide range of capabilities offered by this application is truly remarkable, allowing users to request completion of even advanced tasks with minimal prompts.

The underlying mechanism behind AutoGPT’s ability to reason and achieve goals autonomously remains unknown. However, its capacity to engage in independent reasoning aligns it with human-like information processing capabilities. Some people have even described AutoGPT as a promising glimpse of Artificial General Intelligence (AGI), which could potentially revolutionize the way we work by replacing numerous roles currently performed by humans.

# Final Words

Presently, the field of artificial intelligence (AI) raises numerous concerns among people. These concerns include ethical issues, such as bias and fairness in AI decision-making, the potential for job displacement, data privacy and security concerns, and the impact of AI on society at large. The rapid pace of AI development has also made it challenging for people to keep up with the latest advancements, leading to a fear of missing out (FOMO). This sense of urgency and the fear of falling behind may cause some individuals to question whether AI development should be halted, as echoed by those who advocate for open letters and calls for caution. However, deep down, we all know that this question is rhetorical.

# References

[1] Wei, J., Wang, X., Schuurmans, D., Bosma, M., Chi, E.H., Xia, F., Le, Q., & Zhou, D. (2022). Chain of Thought Prompting Elicits Reasoning in Large Language Models. ArXiv, abs/2201.11903.

[2] Significant-Gravitas. (2023, April 16). Auto-GPT. [Software repository]. GitHub. https://github.com/Significant-Gravitas/Auto-GPT