At Reliance Industries' 47th Annual General Meeting, chairman Mukesh Ambani talked about JioBrain.
To streamline AI adoption, Jio is developing a comprehensive suite of tools and platforms that span the entire AI lifecycle. This is what the company calls JioBrain.
JioBrain enables the company to accelerate AI adoption across Jio, driving faster decisions, more accurate predictions and better understanding of customer needs.
At Reliance Industries’ 47th Annual General Meeting, chairman Mukesh Ambani talked about JioBrain, an AI-driven initiative set to transform how Reliance operates. JioBrain is designed to integrate artificial intelligence into every aspect of Jio’s processes, from decision-making to customer service, making them smarter and more efficient. So, what exactly is Jio Brain, and how will works? Let’s break it down.
What Is JioBrain?
To streamline AI adoption, Jio is developing a comprehensive suite of tools and platforms that span the entire AI lifecycle. This is what the company calls JioBrain.
The goal is to make every process smarter, faster, and more efficient. JioBrain enables the company to accelerate AI adoption across Jio, driving faster decisions, more accurate predictions and better understanding of customer needs.
Also read: Jio brings new Rs 198 Unlimited 5G Data plan with only 14 days of validity: Is it worth it?
“We are also starting to use Jio Brain to drive a similar transformation across other Reliance operating companies, and to fast-track their AI journey as well,” Mukesh Ambani said. “I anticipate that by perfecting Jio Brain within Reliance, we will create a powerful AI service platform that we can offer to other enterprises as well,” he added.
Also read: Reliance Industries developing India’s own ChatGPT, Hanooman
How JioBrain works?
JioBrain combines 5G’s fast speeds, low delays, and massive connectivity with powerful machine learning features like detecting issues, predicting future trends, and automating tasks. The platform can train and use machine learning models both at the network edge and in the service provider cloud. This allows communication service providers (CSPs) to apply machine learning not only to the network but also to a wide range of 5G services and industrial applications, such as AI for images and videos at the edge, probing at the edge, and use cases in healthcare, education, gaming, and entertainment. These capabilities offer better operational control, automated processes, and new ways to generate revenue.
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Ayushi Jain
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