Related papers: Self-Supervised Inference of Agents in Trustless Environments

Self-Supervised Inference of Agents in Trustless Environments

URL: http://arxiv.org/abs/2409.08386v1
Date: Thu, 12 Sep 2024 20:32:07 GMT
Title: Self-Supervised Inference of Agents in Trustless Environments
Authors: Vladyslav Larin, Ivan Nikitin, Alexander Firsov,
Abstract summary: We propose a novel approach where agents can form swarms to produce high-quality responses effectively. This is accomplished by utilizing agents capable of data inference and ranking. We show that our approach is an order of magnitude faster than other trustless inference strategies reaching less than 125 ms validation latency.
Score: 44.99833362998488
License: http://creativecommons.org/licenses/by/4.0/
Abstract: In this paper, we propose a novel approach where agents can form swarms to produce high-quality responses effectively. This is accomplished by utilizing agents capable of data inference and ranking, which can be effectively implemented using LLMs as response classifiers. We assess existing approaches for trustless agent inference, define our methodology, estimate practical parameters, and model various types of malicious agent attacks. Our method leverages the collective intelligence of swarms, ensuring robust and efficient decentralized AI inference with better accuracy, security, and reliability. We show that our approach is an order of magnitude faster than other trustless inference strategies reaching less than 125 ms validation latency.

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