LaTM, CREATOR, and other closed-loop frameworks for LLM tool usage…

In recent overviews, we’ve got explored the utility of augmenting large language models (LLMs) with external tools. These models will be taught to leverage tools in a wide range of ways. Nevertheless, we must always realize that existing tool-following LLMs leverage only a limited set of potential tools [3], whereas the range of problems we wish to resolve with LLMs is almost limitless! With this in mind, it becomes clear that such a paradigm is limiting — we are going to at all times have the opportunity to search out scenarios that require tools that don’t yet exist. On this overview, we are going to explore recent research that goals to resolve this problem by providing LLMs with the talents to create their very own tools. Such an approach draws an interesting analogy to human life, as the power to fabricate tools led to major technological advancements. Now, we explore the impact of comparable techniques upon the evolution of LLMs.

“In response to the teachings learned from the evolutionary milestones of humans, a vital turning point was that humans got the power to fabricate their very own tools to handle emerging challenges. We embark on an initial exploration to use this evolutionary concept to the realm of LLMs.” — from [1]

Prior to learning more about tool-making LLMs, there are a number of background concepts that we’d like to refresh. We have now covered a lot of these ideas in recent overviews, but we’ll briefly go over them again now to make our discussion of recent publications more comprehensive and comprehensible.

Why should we use tools?

In prior overviews, we’ve got learned about a number of different sorts of tools that will be integrated with LLMs to enhance their performance, akin to:

• Basic Tools (calculators, search engines like google and yahoo, etc.) https://towardsdatascience.com/can-language-models-make-their-own-tools-cbc7c3777d22?source=rss—-7f60cf5620c9—4
• Deep Learning Model APIs https://towardsdatascience.com/can-language-models-make-their-own-tools-cbc7c3777d22?source=rss—-7f60cf5620c9—4