Latest Trends in Artificial Intelligence Technology: A Scoping Review
- URL: http://arxiv.org/abs/2305.04532v2
- Date: Tue, 23 May 2023 13:32:54 GMT
- Title: Latest Trends in Artificial Intelligence Technology: A Scoping Review
- Authors: Teemu Niskanen, Tuomo Sipola, Olli V\"a\"an\"anen
- Abstract summary: This study carries out a scoping review of the current state-of-the-art artificial intelligence technologies following the PRISMA framework.
The goal was to find the most advanced technologies used in different domains of artificial intelligence technology research.
- Score: 0.0
- License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
- Abstract: Artificial intelligence is more ubiquitous in multiple domains. Smartphones,
social media platforms, search engines, and autonomous vehicles are just a few
examples of applications that utilize artificial intelligence technologies to
enhance their performance. This study carries out a scoping review of the
current state-of-the-art artificial intelligence technologies following the
PRISMA framework. The goal was to find the most advanced technologies used in
different domains of artificial intelligence technology research. Three
recognized journals were used from artificial intelligence and machine learning
domain: Journal of Artificial Intelligence Research, Journal of Machine
Learning Research, and Machine Learning, and articles published in 2022 were
observed. Certain qualifications were laid for the technological solutions: the
technology must be tested against comparable solutions, commonly approved or
otherwise well justified datasets must be used while applying, and results must
show improvements against comparable solutions. One of the most important parts
of the technology development appeared to be how to process and exploit the
data gathered from multiple sources. The data can be highly unstructured and
the technological solution should be able to utilize the data with minimum
manual work from humans. The results of this review indicate that creating
labeled datasets is very laborious, and solutions exploiting unsupervised or
semi-supervised learning technologies are more and more researched. The
learning algorithms should be able to be updated efficiently, and predictions
should be interpretable. Using artificial intelligence technologies in
real-world applications, safety and explainable predictions are mandatory to
consider before mass adoption can occur.
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