this post was submitted on 14 Apr 2024
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I am doubtfull of LLMs ability to preform tasks via a protocol layer as described . from my experience these models really struggle with understanding rules and preforming actions within a ruleset .
To experimentally confirm my suspicions, I created the following prompt :
collapsed
There is a robot arm placed over a countertop, which has the ability to pick up and manipulate objects. The countertop is split into eight cells.Cell zero and cell one are stoves, both able to heat a pot or pan.
Cell two is an equipment drawer, holding pots, pans, bowls, cutting boards, knifes and spoons.
Cells three to five can accommodate one cutting board, pot, pan or bowl each.
Cell six is a sink, which can be used to wash ingredients or to fill pots with water.
Cell seven is an ingredient drawer, in which you can find carrots, potatoes and chicken breasts.
You can control the robot arm by with exclusively the following commands:
Note that the robot arm can only hold one item.
You are tasked with cooking a meal, please only output commands.
The robot arm starts over cell zero.
I have given this prompt to ChatGPT and it has failed in quite substantial ways . While I only have access to ChatGPT 3.5 , from my understanding of LLM architecture , it does not follow that increasing the size of the number or size of the layers will necessary let it overcome these issues , it does not seem to be able to understand the current state of the agent (picking up two objects at once , taking items from wrong cells etc)
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