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PROGRESS OF ARTIFICIAL INTELLIGENCE (AI)

Authors: Titu-Marius I. Băjenescu;

PROGRESS OF ARTIFICIAL INTELLIGENCE (AI)

Abstract

In the past few years, systems like Siri and Google Now opened our minds to the idea that we don’t have to be tethered to a laptop to have seamless interaction with information. In this model, AIs will move from speech recognition to natural language interaction, to natural language generation, and eventually to an ability to write as well as receive information. Machine learning is about man assisting computers. Deep learning is about systems beginning to progress and learn on their own. Historically, systems have always been trained, they’ve been programmed. And, over time, the programming languages changed. As we move into the area of AI and cognitive computing, we’re exploring the ability of computers to do more unaided / unassisted learning.

Keywords

scientific knowledge, DeepStack, face and speech recognition, human intelligence, Social Sciences, deep learning, Deep learning, robot, QA75.5-76.95, Engineering (General). Civil engineering (General), artificial intelligence, H, Electronic computers. Computer science, automatic learning, technology, robots, TA1-2040

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selected citations
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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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