1,982 research outputs found
Mapping Big Data into Knowledge Space with Cognitive Cyber-Infrastructure
Big data research has attracted great attention in science, technology,
industry and society. It is developing with the evolving scientific paradigm,
the fourth industrial revolution, and the transformational innovation of
technologies. However, its nature and fundamental challenge have not been
recognized, and its own methodology has not been formed. This paper explores
and answers the following questions: What is big data? What are the basic
methods for representing, managing and analyzing big data? What is the
relationship between big data and knowledge? Can we find a mapping from big
data into knowledge space? What kind of infrastructure is required to support
not only big data management and analysis but also knowledge discovery, sharing
and management? What is the relationship between big data and science paradigm?
What is the nature and fundamental challenge of big data computing? A
multi-dimensional perspective is presented toward a methodology of big data
computing.Comment: 59 page
The Turing Deception
This research revisits the classic Turing test and compares recent large
language models such as ChatGPT for their abilities to reproduce human-level
comprehension and compelling text generation. Two task challenges --
summarization, and question answering -- prompt ChatGPT to produce original
content (98-99%) from a single text entry and also sequential questions
originally posed by Turing in 1950. We score the original and generated content
against the OpenAI GPT-2 Output Detector from 2019, and establish multiple
cases where the generated content proves original and undetectable (98%). The
question of a machine fooling a human judge recedes in this work relative to
the question of "how would one prove it?" The original contribution of the work
presents a metric and simple grammatical set for understanding the writing
mechanics of chatbots in evaluating their readability and statistical clarity,
engagement, delivery, and overall quality. While Turing's original prose scores
at least 14% below the machine-generated output, the question of whether an
algorithm displays hints of Turing's truly original thoughts (the "Lovelace
2.0" test) remains unanswered and potentially unanswerable for now
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