GPT-4 is the clear winner in a battle royale to see which large language model would make the best real-world agent, according to scientists.
Typically, these models are benchmarked based on their ability to output text perceived as human-like or by their scores on plain-language tests designed for humans. By comparison, far fewer papers have been published on the subject of LLM models as agents.
Traditional machine learning agents like the one in the video above aren’t typically built as LLMs due to the prohibitive costs involved with training models such as ChatGPT and Claude. However, the largest LLMs have shown promise as agents. These include having models perform functions in an SQL database, work within an operating system, plan and perform household cleaning functions, shop online, and several other high-level tasks that require step-by-step problem solving.
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