AT&T touted a range of network technology initiatives in a new blog post. Among the topics touched on were 5G, artificial intelligence (AI), mobile edge computing (MEC), and software defined networking (SDN).

“While people keep asking what the killer app will be on this generation of networks, we think the network itself is the killer app,” Jeremy Legg, AT&T’s CTO, wrote in the blog post

The post starts with an interesting history of AT&T role in its development of telecommunications and then describes its current initiatives. Some highlights:

Software-defined networking: AT&T says most of its traffic – more than 614.6 petabytes on an average day – now travels on SDNs. From 2018 until the end of last year, global network traffic increased more than 200%. The carrier expects a five-fold increase between 2021 and 2025.

Mobile-access edge computing: Edge computing – bringing computing to the farthest point in the network and closest to end users – is still in a nascent stage, Legg noted in the AT&T technology blog post. The carrier launched its first edge zones in 2022. This enables development of cloud-based software that runs on local networks that minimizes latency and enables connections to nearby cloud facilities.

Connected cars and 5G: AT&T has millions of vehicles networked via 4G, with 5G coming soon. Functionality will increase and the focus will shift more fully from entertainment to safety and mission critical functions, the post predicts. 5G enables “hyper precise” positioning, which will be critical for intelligent transportation systems.

Artificial intelligence: The post discusses Ask AT&T, an assistant for the carrier’s employees. Beyond that, the company is partnering with companies such as Nvidia to further optimize AI. The goal, the post says is “democratizing AI and putting it in the hands of citizen data scientists.”

Ask AT&T, which was announced earlier this week, is the carrier’s move into the generative AI sector. This form of AI generates content. AT&T’s version, which is aimed at helping employees do their jobs, is based on chatGPT.

Initial use cases are network optimization; upgrading legacy software code and environments; customer support; providing quick and simple answers to HR questions and reducing employee meeting time by providing automated summaries and action items.

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