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Communication with AI, communication between AIs – field tests

Authors: Fostikov, Aleksandra;

Communication with AI, communication between AIs – field tests

Abstract

Recent breakthrough in the development of the AI as well as open access to some of its models created an opportunity to test them. Therefore practical tests of the following models were performed: ChatGPT 3.5, Perplexity and Bing. Although all three are based on the GPT family development with which the OpenAI broke into the market, they are fundamentally different in their capabilities. All three are available in the form of the simple chatbot interface that is needed for human-AI dialogue in the natural language. The test trials that we executed were based on two types of communications. Firstly, we tested human – AI communication with individual models. In these cases, the emphasis was placed on various issues related to everyday life, but those communications also include the playing with AI, in order to examine how they perceive our natural reality and language. Then, attention was paid to the communication between AIs themselves. That conversation was conducted through an intermediary, that is, in this case, the author of this paper. In those cases, the author used the copy paste method to bridge their inability to communicate with each other, except in guided experiments. The communications between AIs unveiled that some questions have special interest to themselves. In addition, it should be noted that the communication between natural and artificial intelligence, that is, human-AI, differs from that between two AIs. Except presentations of above-mentioned tests, this paper also stressed out some conclusions based on derived data. At the end, the supplementary resources are added.

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
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