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Summary: Consultation paper on Leveraging Artificial Intelligence and Big Data in Telecom Sector

A consultation paper by the Telecom Regulatory Authority of India (TRAI) seeks comments on deploying AI and Big Data for telecom

What may be the most appropriate definition of Artificial Intelligence (AI)? What are the broad requirements to develop and deploy AI models in telecom sector? What are the challenges faced by telecom service providers in adopting AI? How can big data (BD) in the telecom sector be utilised for developing AI models? These are some of the questions that the Telecom Regulatory Authority of India (TRAI) is looking to deal with in its new consultation paper which seeks to understand how artificial intelligence and big data can be used in the telecom sector. The paper is open for consultation till September 16, 2022 and one can send their counter comments till September 30, 2022. The feedback can be sent to Asit Kadayan, Advisor (QoS) TRAI, on the following email— advqos@trai.gov.in. The comments and counter-comments will be posted on TRAI’s website. Why it matters: The paper is important as several industrial sectors around the world have invested heavily into AI and big data to augment their business. The rapid adoption of these technologies necessitates a cogent policy on how they can be used to drive growth in the telecom sector. Understanding AI And Big Data TRAI noted in the paper that there was no globally accepted definition of AI. It offered multiple definitions provided by different agencies such as ETSI which defined it as “a computerised system that uses cognition to understand information and solve problems”. “Governments, regulatory agencies, international agencies, and other forums have adopted varying definitions depending on the context…

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I cover several beats such as Crypto, Telecom, and OTT at MediaNama. I can be found loitering at my local theatre when I am off work consuming movies by the dozen.

MediaNama’s mission is to help build a digital ecosystem which is open, fair, global and competitive.

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