telecom

The Verge has an interesting article that discusses the other side of 5G, which was touted as the revolutionary future of mobile communication, promising to unleash a wave of transformative technologies from autonomous vehicles to remote surgery. Yet, three years after its hyped debut at CES 2021, the reality of 5G falls short of those initial expectations.

AWS Telco Network Builder (TNB) enables communication service providers (CSPs) to specify their network requirements using telecom industry standards.

Reliance Jio is India’s leading telco (and the world’s third largest) with a massive subscriber base of over 424.5 million across India as of December 2022.

Why are China and the U.S. sparring over 5G? Sino-American rivalry has loomed large through the 5G era, turning what was once a routine network-investment cycle into a geopolitical arms…

While 5G technology has undoubtedly revolutionized the telecommunications industry, it has not yet met the lofty expectations that were set for it in 2023.

5G technology holds immense potential for transforming urban development and creating sustainable, resilient, and livable smart cities. By leveraging 5G’s capabilities, cities can optimize infrastructure, enhance public safety, and improve the overall quality of life for their residents.

With its ultra-low latency, high bandwidth, and massive connectivity, 5G is poised to reshape the way we deliver and receive medical care.As healthcare providers chart their digital strategies for the…

In this blog, we will delve into the technical aspects of the intersection between 5G and financial services, exploring the opportunities, challenges, and transformative potential that this convergence offers.

Per the WSJ, here’s what you need to know about how much the technology has, and hasn’t, changed things. Drew FitzGerald, Alexandra Wexler in Johannesburg and Yang Jie in Tokyo contributed to this article.

As AI becomes more pervasive in the enterprise, edge computing will play an increasingly important role. AI models are often data-intensive and require real-time processing to be effective. Edge computing provides the ideal platform for running AI models at the edge of the network, where the data is generated.