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A lot has happened in the year 2023. We have seen the growth and emergence of large language models (LLMs) and their particular use as fundamental drivers for autonomous agents. We have seen it for ourselves, many people have adopted these freelance agents and integrated them into organizations and more companies are interested in LLMs.
And yes, they have been successful.
But don’t you want to know more? Of course.
Researchers from the Gaoling School of artificial intelligence at Renmin University of China have teamed up to conduct a Complete Survey on LLM-Based Freelance Agentsin which they offer a systematic review of the field of LLM-based autonomous agents from a holistic perspective.
The researchers delve into the construction of autonomous agents based on LLM, as well as a comprehensive overview of the various applications in a variety of fields, such as social sciences, natural sciences, and engineering.
So let’s get into it.
Below is a snapshot of the growth trend in the field of LLM-based freelance agents, through the number of articles published from January 2021 to August 2023.
As you can see, in the space of two years, LLMs have achieved notable successes, showing the general public that ai applications have the potential to achieve human-like intelligence. Comprehensive training data sets and a substantial number of model parameters work hand in hand to achieve this.
Therefore, it seems that there is a large amount of funding and research in this field, making it imperative to provide a systematic overview of the rapidly developing field to comprehensively understand the complexities behind it and the benefits it will bring to inspire future research.
This is what this research team from the Gaoling School of artificial intelligence is doing.
Image by LLM-Agent Survey
LLM-based autonomous agent architecture design
The goal of LLM-based autonomous agents is for them to have the ability to perform various tasks as if they had human capabilities. For this to be possible, it is necessary to delve into the design of the architecture of autonomous agents based on LLM:
- What architecture should be designed to best utilize LLMs?
- How to enable the agent to acquire capabilities to perform specific tasks
As part of the systematic review, the researchers understood that LLMs must fulfill specific functions and learn autonomously from the environment in order to evolve as humans. This is where rational design agent architectures come into play.
Researchers have proposed a unified framework to summarize the number of modules developed to improve LLMs:
- Profile: Identify the role of the agent
- Memory: Places the agent in a dynamic environment and allows it to remember past behaviors.
- Planning: Place the agent in a dynamic environment and plan future actions.
- Action: translate the agent’s decisions into specific results.
The profiling module has a direct impact on the memory and planning modules, and together these three modules influence the action module.
Image by LLM-Agent Survey
To go deeper into each module, read the article: A Survey on Autonomous Agents Based on Large Language Models.
In this article, you can delve into the applications of LLM-based autonomous agents and the proposed evaluation strategies in three distinct areas: social sciences, natural sciences, and engineering. LLM-based autonomous agents have demonstrated significant potential to influence multiple domains, so it is important to understand how these applications are evaluated and the strategies used.
Image by Survey of LLM-Based Freelance Agents
As part of the research process, they also have a interactive table which contains more comprehensive articles related to LLM based agents.
As we can see, more and more people are breaking even when it comes to LLM. More people want to know what it is really about, the architecture, the evaluation strategies and how it will affect our future. Will this help build more trust around LLMs and ai applications in general or are we going to learn the truth about them?
nisha arya is a data scientist and freelance technical writer. She is particularly interested in providing professional data science advice or tutorials and theory-based data science insights. She also wants to explore the different ways in which artificial intelligence can benefit the longevity of human life. A great student looking to expand her technological knowledge and writing skills, while she helps guide others.
