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Speed, security among key features of next-generation AI

Jul 14. 2019
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By Nophakhun Limsamarnphun
The Nation

Mobility, industrial Internet of Things (IoT), cloud, and security will be the key features of the next-generation artificial intelligence (AI) and edge computing eco-systems, according to experts of US-based tech giant Cisco.

All these features will be put together at a faster speed and treated as a single fabric for cutting-edge networks as the number of AI devices, for example, is set to increase sharply in coming years.

According to Anuj Kapur, Cisco’s senior vice president for AI and machine learning, the advent of fifth-generation (5G) cellular network will lead to the use of more connected devices on a larger scale over cloud-based computing facilities.

Unlike the current 4G network, which has been mainly used by consumers and platforms such as Wechat, Uber, Grab and the likes, the upcoming 5G will see more enterprises tapping its potential.

For example, hospitals, corporate campuses, smart factories, smart cities, autonomous vehicles and public security systems are among potential users of 5G connectivity which is 10-100 times faster than 4G.

In Thailand, the National Broadcasting and Telecom Commission has urged telecom carriers to roll out 5G services quickly to upgrade the country’s crucial infrastructure, but private investors are not sure if there are enough use cases to generate revenues that can justify the big investment.

Kapur said during a recent Cisco Live conference that South Korea and Japan are leading the efforts to launch 5G networks commercially, with Japan planning to test its 5G use cases during the upcoming Tokyo 2020 Summer Olympics.

Rakuten of Japan, an online shopping platform, has also entered the telecom sector by launching its 5G mobile network which is expected to synergise with e-commerce and other platforms.

According to Kapur, finance and banking, retail, manufacturing, tele-medicine and healthcare should be among the first sectors to take advantage of 5G along with AI and machine-learning capabilities.

Data processing will be much faster and more accurate, but the cost will be cheaper. For example, a cancer doctor can more quickly and accurately diagnose patients and get better treatment options using the global database of comparable cases.

In the hospitality and retail sectors, businesses will also benefit from having better customer relations and loyalty programmes to boost sales and do predictive marketing campaigns.

Besides 5G, the upcoming Wi-Fi 6 technology will further enhance AI and machine-learning programmes leading to a wider use of programmable APIs (application programme interface).

Human workers, meanwhile, will shift to do more valuable tasks as networks become more intent-based to meet business needs.

In addition, networks can be further extended into oil refinery operations, warehouses or factories via IoT-connected devices and sensors to create smart factories and refineries.

In the oil and gas sector, pipeline corrosion, for example, can also be monitored by the smart network as part of a preventive maintenance and long-term saving programme.

Scott Harrell, Cisco’s senior vice president for enterprise network, said during the Cisco Live conference that a campus of the future, for example, will use Wi-Fi 6 indoor and 5G outdoor in a wireless-first network featuring AI and virtual reality (VR) capabilities.

A software-defined network will not be interrupted as problems can be solved predictively and automatically, while a wireless-enabled cloud with Wi-Fi sensors such as those in an oil refinery will facilitate predictive asset maintenance.

Speaking at the Cisco Live conference, Amy Chang. Cisco’s senior vice president, said cognitive collaboration using AI and machine-learning capabilities will change how people work on LinkedIn, Webex and other platforms while healthcare and other sectors will benefit from better patient and customer experience.

According to Cisco, software innovation has made running and securing networks easier using AI and machine-learning capabilities to cover an entire enterprise network from campus and wide-area networks to data centres and IoT edge.

This will reduce the burden on IT teams who could better focus on more creative tasks, leaving network management to these new capabilities for more visibility, greater insights and better guided actions.

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