AI in Networks Market
SK Telecom unveils plans for AI Infrastructure at SK AI Summit 2024
Introduction:
During the two-day SK AI Summit 2024 [1.], SK Telecom CEO Ryu Young-sang unveiled the company’s comprehensive strategy which revolves around three core components: AI data centers (AIDCs), a cloud-based GPU service (GPU-as-a-Service, GPUaaS), and Edge AI. SK Telecom is planning to construct hyperscale data centers in key regions across South Korea, with the goal of becoming the AIDC hub in the Asia Pacific region. Additionally, the company will launch a cloud-based GPU service to address the domestic GPU shortage and introducing ‘Edge AI’ to bridge the gap between AIDC and on-device AI. This innovative approach aims to connect national AI infrastructure and expand globally, in collaboration with partners both in South Korea and abroad.
Note 1. The SK AI Summit is an annual event held by the SK Group, where global experts in various AI fields gather to discuss coexistence in the era of artificial general intelligence (AGI) and seek ways to strengthen the ecosystem.
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Constructing AI Data Centers in South Korea’s key regions:
SK Telecom plans to start with hyperscale AIDCs that require more than 100 megawatts (MW) in local regions, with future plans to expand its scale to gigawatts (GW) or more, to leap forward as the AIDC hub in the Asia Pacific region.
By extending the AIDC to national bases, centers can secure a stable power supply through the utilization of new renewable energy sources such as hydrogen, solar and wind power, and easily expand to global markets through submarine cables. SK Telecom anticipates building AIDC cost-effectively when the data center combines SK Group’s capabilities in high-efficiency next-generation semiconductors, immersion cooling, and other energy solutions, along with its AI cluster operation.
Prior to this, SK Telecom plans to open an AIDC testbed in Pangyo, Korea, in December, which combines the capabilities of the SK Group and various solutions owned by partner companies. This facility, where all three types of next-generation liquid cooling solutions—direct liquid cooling, immersion cooling, and precision liquid cooling—are deployed, will be the first and only testbed in Korea. It will also feature advanced AI semiconductors like SK hynix’s HBM, as well as GPU virtualization solutions and AI energy optimization technology. This testbed will provide opportunities to observe and experience the cutting-edge technologies of a future AIDC.
Supplying GPU via cloud to metropolitan areas:
SK Telecom plans to launch a cloud-based GPU-as-a-Service (GPUaaS) by converting the Gasan data center, located in the metropolitan area, into an AIDC to quickly resolve the domestic GPU shortage.
Starting in December, SK Telecom plans to launch a GPUaaS with NVIDIA H100 Tensor Core GPU through a partnership with U.S.-based Lambda. In March 2025, SK Telecom plans to introduce NVIDIA H200 Tensor Core GPU in Korea, gradually expanding to meet customer demand.
Through the AI cloud services (GPUaaS), SKT aims to enable companies to develop AI services easily and at a lower cost, without needing to purchase their own GPUs, ultimately supporting the vitalization of Korea’s AI ecosystem.
Introducing ‘Edge AI’ to open a new opportunity in telco infrastructure:
SK Telecom plans to introduce ‘Edge AI,’ which can narrow the gap between AIDC and on-device AI, using the nationwide communication infrastructure.
Edge AI is an infrastructure that combines mobile communication networks and AI computing, offering advantages in reduced latency, enhanced security, and improved privacy compared to large-scale AIDCs. Additionally, it enables large-scale AI computing, complementing the existing AI infrastructure, compared to on-device AI.
SKT is currently conducting research on advanced technologies and collaborating with global partners to build AIDC-utilizing communication infrastructure and develop customized servers. The company is also carrying out various proof of concept (PoC) projects across six areas, including healthcare, AI robots, and AI CCTV, to discover specialized Edge AI services.
“So far, the competition in telecommunications infrastructure has been all about connectivity, namely speed and capacity, but now the paradigm of network evolution should be changed,” said Ryu Young-sang, CEO of SK Telecom. “The upcoming 6G will evolve into a next-generation AI infrastructure where communication and AI are integrated.”
Developing a comprehensive AIDC solution to enter global market:
SK Telecom plans to develop a comprehensive AIDC solution that combines AI semiconductors, data centers, and energy solutions through collaboration with AI companies in Korea and abroad, with the aim of entering the global market.SK Telecom aims to lead the global standardization of Edge AI and collaborate on advanced technology research, while working towards the transition to 6G AI infrastructure.
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About SK Telecom:
SK Telecom has been leading the growth of the mobile industry since 1984. Now, it is taking customer experience to new heights by extending beyond connectivity. By placing AI at the core of its business, SK Telecom is rapidly transforming into an AI company with a strong global presence. It is focusing on driving innovations in areas of AI Infrastructure, AI Transformation (AIX) and AI Service to deliver greater value for industry, society, and life.
For more information, please contact [email protected] or visit our LinkedIn page www.linkedin.com/company/sk-telecom
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References:
SKT-Samsung Electronics to Optimize 5G Base Station Performance using AI
SK Telecom (SKT) and Nokia to work on AI assisted “fiber sensing”
Huawei’s “FOUR NEW strategy” for carriers to be successful in AI era
At the 10th Ultra-Broadband Forum (UBBF 2024) in Istanbul, Turkey, James Chen, President of Huawei’s Carrier Business, delivered a speech entitled “Network+AI, Unleashing More Business Value.”
“To explore the potential of AI, the ‘FOUR NEW’ strategy — new hub, new services, new experience, and new operation is crucial. It helps carriers to expand market boundaries, foster innovative services, and enhance market competitiveness, while also optimize network O&M and achieve business success. Huawei is committed to working with global carriers and partners to unleash more business value and forge a win-win digital and intelligent future through the “FOUR NEW” strategy.”
James Chen, President of Huawei’s Carrier Business, delivering a keynote speech
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Huawei believes that its “FOUR NEW” strategy is key to unleashing more business value through the combination of networking and AI.
- New Hub: The new Hub is the AI Hub for home services. The core of the AI Hub is the development of AI agents. AI agents need to connect people, things, and applications, understand and respond to the requirements of family members, control smart devices to meet family requirements, and connect AI applications to expand the boundaries of home services. The new hub helps carriers achieve business breakthroughs in the home market.
- New Services: Carriers enable new services and aggregate high-quality contents with AI to gradually build a home AI application ecosystem. AI not only can upgrade traditional services, such as interactive fitness and motion-sensing games, but also innovate home services, such as home service robots, health care, and education, etc. It improves quality of life and gradually builds a home AI ecosystem.
- New Experience: New services such as cloud gaming, live commerce, AI searches for photos and videos, are emerging one after another. These services have high requirements on network quality, including latency, uplink and downlink bandwidth, and jitter. This brings new network monetization opportunities to carriers. Carriers can seize monetization opportunities through new business models, such as latency-based charging, upstream bandwidth-based charging, and AI-function based charging. High-quality service experience requires high-quality networks. Carriers build “Premium vertical and premium horizontal” high-quality networks to support high-quality service experience and business monetization. The key to building a “Premium vertical and premium horizontal” network is to build 1 ms connections between data centers and 1 ms access to a data center.
- New Operation: As carriers’ network scale is getting larger, autonomous driving network is becoming more important. AI supports high-level network autonomous driving and improves network operation efficiency. Huawei’s L4 autonomous driving network based on the Telecom Foundation Model helps operators reduce customer complaints, shorten the complaint closure time, improve service provisioning efficiency, reduce the number of site visits, and accelerate fault rectification.
In the wave of digital intelligence transformation, the “FOUR NEW” strategy is not only the embodiment of network technology innovation, but also the important driving force for continuously releasing network business value. New Hub, New Services, New Experience, and New Operation support each other and together form a complete road to digital intelligence business success.
In the future, Huawei will continue to remain customer-centric, work with global carriers and partners to explore the digital intelligence era, accelerate the release of the business value of network + AI, and embrace a prosperous intelligent world.
References:
Huawei’s First-Half Net Profit Rose on Strong Smartphone Sales, Car Business
China Unicom-Beijing and Huawei build “5.5G network” using 3 component carrier aggregation (3CC)
Despite U.S. sanctions, Huawei has come “roaring back,” due to massive China government support and policies
Huawei to revolutionize network operations and maintenance
Reuters & Bloomberg: OpenAI to design “inference AI” chip with Broadcom and TSMC
Bloomberg reports that OpenAI, the fast-growing company behind ChatGPT, is working with Broadcom Inc. to develop a new artificial intelligence chip specifically focused on running AI models after they’ve been trained, according to two people familiar with the matter. The two companies are also consulting with Taiwan Semiconductor Manufacturing Company(TSMC) the world’s largest chip contract manufacturer. OpenAI has been planning a custom chip and working on its uses for the technology for around a year, the people said, but the discussions are still at an early stage. The company has assembled a chip team of about 20 people, led by top engineers who have previously built Tensor Processing Units (TPUs) at Google, including Thomas Norrie and Richard Ho.
Reuters reported on OpenAI’s ongoing talks with Broadcom and TSMC on Tuesday. It has been working for months with Broadcom to build its first AI chip focusing on inference (responds to user requests), according to sources. Demand right now is greater for training chips, but analysts have predicted the need for inference chips could surpass them as more AI applications are deployed.
OpenAI has examined a range of options to diversify chip supply and reduce costs. OpenAI considered building everything in-house and raising capital for an expensive plan to build a network of chip manufacturing factories known as “foundries.”
REUTERS/Dado Ruvic/Illustration/File Photo Purchase Licensing Rights
OpenAI may continue to research setting up its own network of foundries, or chip factories, one of the people said, but the startup has realized that working with partners on custom chips is a quicker, attainable path for now. Reuters earlier reported that OpenAI was pulling back from the effort of establishing its own chip manufacturing capacity. The company has dropped the ambitious foundry plans for now due to the costs and time needed to build a network, and plans instead to focus on in-house chip design efforts, according to sources.
OpenAI, which helped commercialize generative AI that produces human-like responses to queries, relies on substantial computing power to train and run its systems. As one of the largest purchasers of Nvidia’s graphics processing units (GPUs), OpenAI uses AI chips both to train models where the AI learns from data and for inference, applying AI to make predictions or decisions based on new information. Reuters previously reported on OpenAI’s chip design endeavors. The Information reported on talks with Broadcom and others.
The Information reported in June that Broadcom had discussed making an AI chip for OpenAI. As one of the largest buyers of chips, OpenAI’s decision to source from a diverse array of chipmakers while developing its customized chip could have broader tech sector implications.
Broadcom is the largest designer of application-specific integrated circuits (ASICs) — chips designed to fit a single purpose specified by the customer. The company’s biggest customer in this area is Alphabet Inc.’s Google. Broadcom also works with Meta Platforms Inc. and TikTok owner ByteDance Ltd.
When asked last month whether he has new customers for the business, given the huge demand for AI training, Broadcom Chief Executive Officer Hock Tan said that he will only add to his short list of customers when projects hit volume shipments. “It’s not an easy product to deploy for any customer, and so we do not consider proof of concepts as production volume,” he said during an earnings conference call.
OpenAI’s services require massive amounts of computing power to develop and run — with much of that coming from Nvidia chips. To meet the demand, the industry has been scrambling to find alternatives to Nvidia. That’s included embracing processors from Advanced Micro Devices Inc. and developing in-house versions.
OpenAI is also actively planning investments and partnerships in data centers, the eventual home for such AI chips. The startup’s leadership has pitched the U.S. government on the need for more massive data centers and CEO Sam Altman has sounded out global investors, including some in the Middle East, to finance the effort.
“It’s definitely a stretch,” OpenAI Chief Financial Officer Sarah Friar told Bloomberg Television on Monday. “Stretch from a capital perspective but also my own learning. Frankly we are all learning in this space: Infrastructure is destiny.”
Currently, Nvidia’s GPUs hold over 80% AI market share. But shortages and rising costs have led major customers like Microsoft, Meta, and now OpenAI, to explore in-house or external alternatives.
References:
AI Echo Chamber: “Upstream AI” companies huge spending fuels profit growth for “Downstream AI” firms
AI Frenzy Backgrounder; Review of AI Products and Services from Nvidia, Microsoft, Amazon, Google and Meta; Conclusions
AI sparks huge increase in U.S. energy consumption and is straining the power grid; transmission/distribution as a major problem
Generative AI Unicorns Rule the Startup Roost; OpenAI in the Spotlight
SKT-Samsung Electronics to Optimize 5G Base Station Performance using AI
SK Telecom (SKT) has partnered with Samsung Electronics to use AI to improve the performance of its 5G base stations in order to upgrade its wireless network. Specifically, they will use AI-based 5G base station quality optimization technology (AI-RAN Parameter Recommender) to commercial 5G networks.
The two companies have been working throughout the year to learn from past mobile network operation experiences using AI and deep learning, and recently completed the development of technology that automatically recommends optimal parameters for each base station environment. When applied to SKT’s commercial network, the new technology was able to bring out the potential performance of 5G base stations and improve the customer experience.
Mobile base stations are affected by different wireless environments depending on their geographical location and surrounding facilities. For the same reason, there can be significant differences in the quality of 5G mobile communication services in different areas using the same standard equipment.
Accordingly, SKT utilized deep learning, which analyzes and learns the correlation between statistical data accumulated in existing wireless networks and AI operating parameters, to predict various wireless environments and service characteristics and successfully automatically derive optimal parameters for improving perceived quality.
Samsung Electronics’ ‘Network Parameter Optimization AI Model’ used in this demonstration improves the efficiency of resources invested in optimizing the wireless network environment and performance, and enables optimal management of mobile communication networks extensively organized in cluster units.
The two companies are conducting additional learning and verification by diversifying the parameters applied to the optimized AI model and expanding the application to subways where traffic patterns change frequently.
SKT is pursuing advancements in the method of improving quality by automatically adjusting the output of base station radio waves or resetting the range of radio retransmission allowance when radio signals are weak or data transmission errors occur due to interference.
In addition, we plan to continuously improve the perfection of the technology by expanding the scope of targets that can be optimized with AI, such as parameters related to future beamforming*, and developing real-time application functions.
* Beamforming: A technology that focuses the signal received through the antenna toward a specific receiving device to transmit and receive the signal strongly.
SKT is expanding the application of AI technology to various areas of the telecommunications network, including ‘Telco Edge AI’, network power saving, spam blocking, and operation automation, including this base station quality improvement. In particular, AI-based network power saving technology was recently selected as an excellent technology at the world-renowned ‘Network X Award 2024’.
Ryu Tak-ki, head of SK Telecom’s infrastructure technology division, said, “This is a meaningful achievement that has confirmed that the potential performance of individual base stations can be maximized by incorporating AI,” and emphasized, “We will accelerate the evolution into an AI-Native Network that provides differentiated customer experiences through the convergence of telecommunications and AI technologies.”
“AI is a key technology for innovation in various industrial fields, and it is also playing a decisive role in the evolution to next-generation networks,” said Choi Sung-hyun, head of the advanced development team at Samsung Electronics’ network business division. “Samsung Electronics will continue to take the lead in developing intelligent and automated technologies for AI-based next-generation networks.”
SK Telecom and Samsung Electronics researchers discussing verification of AI-based 5G base station quality optimization technology.
SK Telecom and Samsung Electronics researchers discussing verification of AI-based 5G base station quality optimization technology.
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SKT said it is expanding the use of AI to various areas of its communications network, such as “Telco Edge AI,” network power reduction, spam blocking and operation automation, including basestation quality improvement.
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References:
SK Telecom (SKT) and Nokia to work on AI assisted “fiber sensing”
South Korea has 30 million 5G users, but did not meet expectations; KT and SKT AI initiatives
SKT Develops Technology for Integration of Heterogeneous Quantum Cryptography Communication Networks
India Mobile Congress 2024 dominated by AI with over 750 use cases
Markets and Markets: Global AI in Networks market worth $10.9 billion in 2024; projected to reach $46.8 billion by 2029
According to research firm Markets and Markets, the global AI in Networks market is expected to be valued at USD 10.9 billion in 2024 and is projected to reach USD 46.8 billion by 2029 and grow at a CAGR of 33.8% from 2024 to 2029. AI in networks market is experiencing high growth driven by increasing adoption of 5G technology, edge computing, IoT connected devices, and expansion of smart cities. Increasing deployment of 5G networks has led to the vast amount of network data, generated by high bandwidth application such as video streaming and online gaming, driving network operators to integrate AI driven solutions to manage network data and allocate resources to reduce network congestion. Network operators are also integrating AI driven solutions to automate network operations and predictive maintenance, to reduce human dependency and errors, leading to efficient network management.
Network operators invest heavily in developing AI-driven solutions to manage and optimize network traffic. AI in networks allows operators to efficiently perform network management tasks such as traffic routing, resource allocation, and network security. As the 5G technology advances, the demand for cybersecurity solutions will also rise, driving the AI in networks market.
Constraint: Data privacy and security concerns in AI in networks
Integration of artificial intelligence technology in the networking leads to various risks affiliated with collecting, storing, and transmitting network traffic data. AI driven network collect users and network operations data information, creating a high risk environment of privacy breaches, due to the rising cyberthreats. These cyberattacks may lead to unauthorized access to network and user data, disrupting network operations. Additionally, data generated by connected and Iot devices such as smartphones, smart home systems, surveillance system is collected by network, leads to concerns regarding unauthorized surveillance and cyberattacks.
Opportunity: Increasing prevalence of smart city initiatives
Rapid urbanization has led to the exapsnion of smart cities globally. Countries around the world are investing heavily towards smart infrastructure by integrating advanced technologies such as artificial intelligence (AI). For instance, smart city ecosystem consist of various sensors and connected and IoT devices, and to ensure efficient transmission and processing of data generated by these sensor and devices. AI driven network solutions play a vital role in collecting and processing of data, identifying anomalies and equipment failure based on present and historical data, helping network operator to schedule maintenance in advance and reduce downtime.
Challenge: Rapid change in the technology landscape
As the technology landscape evolves rapidly, AI presents a major challenge in the network market. As new technologies appear and current technology evolves, companies in the ecosystem must continuously invest in the research and development of changing market demand and advancements. Additionally, intense competition in the market and pressure to offer innovative solutions further restrict companies from maintaining market leadership. Companies’ negligence in identifying the technological shift can result in a decline in market share and revenue.
AI in networks market in North America will hold the highest market share during the forecast period.
The AI in networks market for North America is expected to hold the highest market share during the forecast period. This growth is attributed to the presence of leading AI and network technology companies in the region. These companies are investing heavily towards the advancement of technologies such as AI, 5G, edge computing, due to the high internet penetration rate in the region. The demand for high bandwidth network application such as video streaming and online gaming also on the rise, driving the investments and innovations towards AI driven solutions in network management.
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References:
https://www.marketsandmarkets.com/Market-Reports/ai-in-networks-market-131514910.html