Robotics & Machine Learning Daily News2024,Issue(Oct.17) :86-90.

Patent Issued for Computer implemented method for the automated analysis or use of data (USPTO 12106059)

Robotics & Machine Learning Daily News2024,Issue(Oct.17) :86-90.

Patent Issued for Computer implemented method for the automated analysis or use of data (USPTO 12106059)

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Abstract

By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News Daily News – From Alexandria, Virginia, NewsRx jour nalists report that a patent by the inventors Curran, Finlay (Cambridgeshire, GB ), Heywood, Robert (Cambridgeshire, GB), Roscoe, Harry (Cambridgeshire, GB), Tun stall-Pedoe, William (Cambridgeshire, GB), filed on November 22, 2023, was publi shed online on October 1, 2024. The patent’s assignee for patent number 12106059 is Unlikely Artificial Intellig ence Limited (Cambridgeshire, United Kingdom). News editors obtained the following quote from the background information suppli ed by the inventors: “1. Field of the Invention “The field of the invention relates to a computer implemented method for the aut omated analysis or use of data; one implementation is a voice assistant that is able to analyse, interpret and act on natural language spoken and text inputs. “2. Technical Background “Natural language (NL) is language evolved for humans such as the English langua ge. Although significant advances have been made in computers’ ability to proces s natural language, computers are still not able to deeply understand the meanin g of natural language and use that meaning internally. “For this reason most computer applications typically use structured data to sto re information that they need for processing-e.g. a relational database: designi ng the schema, populating the database and writing code to process the fields in the database.

Key words

Artificial Intelligence/Business/Compu ters/Cyborgs/Emerging Technologies/Machine Learning/Unlikely Artificial Inte lligence Limited

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出版年

2024
Robotics & Machine Learning Daily News

Robotics & Machine Learning Daily News

ISSN:
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