Chatbots and Zero Sales Resistance

Fuente: arXiv
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Bibliographic Details
Main Author: Succi, Sauro
Format: Preprint
Published: 2024
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author Succi, Sauro
author_facet Succi, Sauro
contents It is argued that the pursuit of an ever increasing number of weights in large-scale machine learning applications, besides being energetically unsustainable, is also conducive to manipulative strategies whereby Science is easily served as a strawman for economic and financial power. If machine learning is meant to serve science ahead of vested business interests, a paradigm shift is needed: from more weights and little insight to more insight and less weights.
format Preprint
id arxiv_https___arxiv_org_abs_2408_10291
institution arXiv
publishDate 2024
record_format arxiv
spellingShingle Chatbots and Zero Sales Resistance
Succi, Sauro
Machine Learning
It is argued that the pursuit of an ever increasing number of weights in large-scale machine learning applications, besides being energetically unsustainable, is also conducive to manipulative strategies whereby Science is easily served as a strawman for economic and financial power. If machine learning is meant to serve science ahead of vested business interests, a paradigm shift is needed: from more weights and little insight to more insight and less weights.
title Chatbots and Zero Sales Resistance
topic Machine Learning
url https://arxiv.org/abs/2408.10291