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AI will be key engine of fourth industrial revolution: Huawei India

Huawei invests in basic AI research, develops fundamental AI components like chipsets, all scenario hardware solutions, and full-stack software, enabling synergetic device-edge-cloud AI applications.

Artificial intelligence is one technology that can be applied across all sectors. Huawei has been working to leverage various AI-powered technologies with several telecom operators, local authorities, industries, and various partners.

DQINDIA Online | dqindia

Steve Kim, President of Cloud & AI Business Group, Huawei India, tells us more. Excerpts from an interview:

DQ: What is Huawei’s AI strategy and how does it intend to solve business challenges with it?

Steve Kim: We see AI as a new general-purpose technology. Just like railways and electricity in the 19th century, and automobiles, PCs, and the Internet in the 20th century, AI will be applied in every sector of our social economy. It will serve as a key engine of the fourth industrial revolution to drive economic advances in the global community.

However, we also recognize that AI is still in its early stages of development, and numerous gaps need to be closed before it can really become a general-purpose technology. Huawei’s AI strategy is designed to bridge these gaps and speed up AI adoption. Moreover, Huawei wants to bring value to customers in multiple areas to drive their adoption of AI.

Huawei invests in basic AI research, develops fundamental AI components like chipsets, all scenario hardware solutions, and full-stack software, enabling synergetic device-edge-cloud AI applications.

As part of this, Huawei announced and rolled out its AI strategy in 2018, along with product R&D and commercial use cases. In 2019, Huawei unveiled its Ascend series of AI processors; AI computing framework MindSpore; Atlas series of AI accelerator modules, accelerator cards, and servers; the world’s fastest AI training cluster; and Ascend-based, AI-powered cloud services.

Huawei has also built a full-stack, all-scenario AI portfolio. We collaborate with the global academia, industries, and partners to build an open ecosystem, and work to strengthen the existing portfolio with AI, and are aiming at using AI to drive internal operational efficiency.

DQ: How transformative do you think AI will be for the telecom industry and society as a whole?

Steve Kim: AI is a general-purpose technology and has been used in almost all industries. In the telecom industry particularly, some of the popular use cases include service chat robot, site maintenance, precise marketing, network equipment trouble shooting, etc. This new-age technology is expected to improve not only the user experience and network efficiency, but will also ensure that users get better bandwidth, less service breakage and the most needed information.

DQ: How does Huawei develop its industry solutions? How is the company doing in AI computing in terms of industry collaboration and the ecosystem?

Steve Kim: Huawei’s AI solutions are the result of its collaboration with partners from different industries. We position ourselves as the digital foundation or the “fertile soil”, providing an AI infra platform in the form of cloud resource or on-premise hardware, such as GPU, server, storage or AI fabric network. However, we feel that intelligence cannot be achieved by Huawei alone. Without our software partners, we can’t deliver these AI solutions. All our AI solutions are the result of our partnerships.

Since the launch of our Atlas AI computing series products, we have released more than 30 joint solutions with independent software vendors (ISVs), and teamed up with industry customers across Europe and Asia Pacific, including Sberbank, Yadex, Digi, NUS, AGS, SARADA, the Shanghai Astronomical Observatory, and the Peng Cheng Laboratory.

DQ: Which are the sectors that will see early development and adoption of AI?

Steve Kim: Huawei believes that AI can be applied across all sectors and has been working to leverage various AI-powered technologies by working with several telecom operators, local authorities, industries, and various partners. Having a strong network that is AI powered can further help various digitalizing sectors to fully transform:

•​Safe city and safe campus, to avoid crime and make a better city.
•​Intelligent traffic, to help maintain decent behavior of driving and traffic order.
•​Smart manufacturing, from predictive maintenance, to collaborative human-machine-interaction, to automated quality control.
•​Smart agriculture, where AI can help in pest control, watering, etc.
•​eHealth/Smart medical care with AI-assisted computer tomography (CT), which can be applied to diagnosis, such as for Covid-19.
•​Autonomous driving, where AI resources can help to achieve driving automation of level 3 and above by combining in-car intelligent computing with network and cloud resources.

Furthermore, AI enables automated mobile network operation and energy saving, of interest especially to network operators. At Huawei, embedded AI is already established in our high-end smartphones for intelligent photography enhancements, and as intelligent LAN-switches for data centers, whereas AI-enhanced communication products are yet to become mainstream.

DQ: Can the integration of AI in network technologies enable better networks?

Steve Kim: AI already plays an important part in the network technologies that we are building. In fact, the role of AI in network technologies, particularly for 5G is getting more and more important, so much that it may even become irreplaceable. This is mainly because of three reasons.

Firstly, the application of AI in mobile networks helps to achieve flexible autonomy of 5G network operations, and continuously improves network performance. In addition, it helps to reduce energy consumption.

Secondly, applying AI simplifies network operations and maintenance and accelerates site deployment. Automated site inventory and upgrade planning make the process more than 80% faster than traditional site deployment.

Thirdly, AI can be used on the service layer to provide end-to-end deterministic network services, which are needed by a wide range of industries. As mentioned earlier, even simple products like Ethernet switches can be improved significantly with embedded AI.

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