Top

3GPP 5G NTN Standards Set To Dramatically Boost Mobile Satellite Addressable Market

Satellite communications is back in the limelight following the launch of Apple’s direct Satellite-to-Phone service earlier this year. Partnering with satellite operator Globalstar, the service provides SOS messaging for iPhone 14/15 users. Recently, the service was expanded to include roadside assistance via satellite as well. A host of similar services and partnerships have been announced between satellite operators and chip vendors/cellular operators during the past few months, including Inmarsat with Mediatek, Iridium with Qualcomm and most recently SpaceX with KDDI.

In addition to the incumbent operators, there are a number of new players such as AST SpaceMobile and Lynk Global. AST SpaceMobile has partnered with Rakuten Mobile and currently has one operational satellite in-orbit. It has been granted preliminary experimental licenses in Japan and in the US. Meanwhile Lynk launched a limited commercial “store-and-forward” service using three satellites in April. Both companies plan to launch full constellations over the next few years.

The Mobile Satellite Services (MSS) market has historically been a niche market due primarily to the fact that MSS is based on proprietary technologies. However, 3GPP is working with the satellite industry on a global standardized solution, called 5G Non-Terrestrial Networks (NTN). 5G NTN will enable seamless roaming between terrestrial and satellite networks, using largely standard cellular devices, i.e., eliminating the need for proprietary terminals and fragmented satellite constellations. This could dramatically increase the addressable market for mobile satellite services.

5G Non-Terrestrial Networks (NTN)

With the emergence of new Satellite-to-Phone services, there is now a widespread industry push to deploy NTN-based satellite networks as this would benefit the satellite industry and the wider mobile industry. However, 3GPP has been working on NTN for some time. For example, there has been an ongoing study on 5G NTN since 3GPP Release 15, while in 2022, 3GPP introduced two parallel workstreams in its Release 17 specifications addressing 5G satellite-based mobile broadband and low-complexity IoT use cases:

  • NR-NTN (New Radio NTN) – adapts the 5G NR framework for satellite communications, providing direct mobile broadband services as well as voice using standard apps. This will enable 5G phones operating on dedicated 5G NTN frequencies and existing sub-7GHz terrestrial frequencies to link directly with Release-17 compatible satellites. Release 17 also includes enhancements for satellite backhaul and the inclusion of 80MHz MSS uplink spectrum in L-band (1-2GHz) plus a similar amount of downlink spectrum in S-band (2-4GHz).
  • IoT-NTN – provides satellite support for low-complexity eMTC and NB-IoT devices, which expands the coverage for key use cases such as worldwide asset tracking (for example, air freight, shipping containers and other assets outside cellular coverage). IoT-NTN is designed for low data rate applications such as the transmission of sensor data and text messages.

Release 17 established the NR-NTN and IoT-NTN standards while the upcoming 5G Advanced Release 18 will introduce new capabilities, coverage/mobility enhancements and support for expanded spectrum bands. For example, there are plans to extend the NR-NTN frequency range beyond 10GHz by adding Fixed Satellite Services (FSS) spectrum in the 17.7-20.2GHz band for downlink and 27.5-30.0GHz for uplink.

Satellite IoT

Traditional mobile satellite operators such as Inmarsat, Iridium and Globalstar have been offering M2M/IoT type services for many years targeting various industry verticals, ranging from agriculture, construction and oil and gas to maritime, transportation and utilities. Some of the traditional FSS players, such as AsiaSat, Eutelsat and Intelsat, also offer M2M/IoT services over Ku or Ka bands.

Another player with a long history in satellite communications is San Diego-based chip vendor Qualcomm. The company was a founding partner and key technology provider in Globalstar and also developed satellite-based asset tracking service OmniTRACS. Qualcomm is still heavily involved in the satcom business and earlier this year announced Snapdragon Satellite, its Satellite-to-Phone service. More recently, it announced the availability of two Release 17 compatible GEO/GSO IoT-NTN satellite modems launched in collaboration with US-based Skylo, a NTN connectivity service provider, that enables cellular devices to connect to existing, proprietary satellite networks:

  • Qualcomm 212S Modem – a satellite-only IoT modem designed to enable stationary sensing and monitoring IoT devices to communicate with NTN-based satellites. The chipset is an ultra-low power device and can be powered from solar panels or supercapacitors.
  • Qualcomm 9205S Modem – enables IoT devices to connect to both terrestrial cellular and satellite networks and has integrated GNSS to provide location data. Typical applications include industrial applications requiring always-on, hybrid terrestrial and satellite connectivity for tracking assets such as agricultural machinery, shipping containers, livestock, etc.

Both devices are designed for low-power, cost optimized applications and support the Qualcomm Aware cloud platform, which provides real-time asset tracking and device management in off-grid, remote areas for IoT.

Most of the major chip vendors, such as MediaTek, Qualcomm and Sony Semiconductors, have already developed Release 17 compatible chipsets. This means that satellite-compliant 5G IoT devices could be available commercially by the end of 2023 and should become commonplace in 2024.

NTN Satellite Operators

Only a few NTN-based satellites have been launched to date. A noteworthy example is Spanish LEO operator Sateliot, the first company to deploy satellites complying with 3GPP’s Release 17 IoT-NTN standard. Sateliot currently has two satellites in orbit and recently carried out a successful roaming test between its satellite network and Telefonica’s 5G terrestrial network using an IoT device with a standard SIM card. Sateliot plans to start commercial activities in 2024. Ultimately, the company hopes to launch a total of 250 nanosatellites, which will enable it to offer global 5G IoT-NTN services.

No satellite operator presently supports 3GPP’s Release 17 NR-NTN standard for voice and data. Although AST SpaceMobile and Lynk Global have demonstrated two-way satellite-to-5G terrestrial communications, neither uses the NR-NTN standard, although they have plans to test the NR-NTN standard.

Satellite Déjà Vu?

Over two decades ago, the mobile satellite industry invested billions to launch a number of ground-breaking LEO-based voice and narrowband data constellations. Only a handful survived and even fewer have prospered. Will history repeat itself?

Although there are some parallels, Counterpoint Research believes that there are also some important differences this time. During the past 20 years, satellites have become much smaller, more capable and less expensive. Some of these satellites are based on CubeSat technology, which uses commercial, off-the-shelf (COTS) components, thus drastically reducing costs while accelerating time to market. This is particularly relevant to nanosatellites, many of whom are being developed to target the IoT-NTN market. Another important difference is that launch costs have decreased significantly due to the entry of new private launch companies, notably SpaceX.

Perhaps the most important differentiator between current and next-generation satellites, however, is that the latter will be based on 3GPP’s NTN standards. Historically, proprietary satellite systems have resulted in a limited range of low volume and hence expensive end user devices – a significant barrier to growth. As with 5G (and 4G before it), a common set of cellular-based standards will enable the mobile satellite industry – plus the vertical markets it serves – to benefit from the vast economies of scale of the cellular device ecosystem. This should result in higher volume chipset production, more affordable devices and services and hence a much larger market of end users. For instance, Sateliot estimates that the cost of satellite IoT connectivity will drop from hundreds of dollars per device per month to less than $10 per device per month.

Furthermore, the adoption of 5G NTN and its integration with terrestrial 5G will result in a truly seamless global telecoms network, with increased space segment capacity, resulting in more users benefiting from higher data rate services. This will lead to more applications and use cases thus creating more value-add for vertical market users. Clearly, this could lead to a significant expansion of the mobile satellite services market globally.

Related Posts

Podcast #70: Qualcomm Driving On-device Generative AI to Power Intelligent Experiences at the Edge

Generative AI like ChatGPT and Google’s Bard have disrupted the industry. However, they are still limited to browser windows and smartphone apps, where the processing is done through cloud computing. That is about to change soon as Qualcomm Snapdragon-powered devices will soon be able to run on-device generative AI.

At MWC 2023, Qualcomm showcased Stable Diffusion on a Snapdragon 8 Gen 2-powered Android smartphone. The demo showed how a smartphone can generate a new image with text commands or even change the background, without connecting to the internet. Running generative AI apps directly on a device offers several advantages, including lower operational costs, better privacy, security, and reliability of working without internet connectivity.

ALSO LISTEN: Podcast #69: ChatGPT and Generative AI: Differences, Ecosystem, Challenges, Opportunities

In the latest episode of ‘The Counterpoint Podcast’, host Peter Richardson is joined by Qualcomm’s Senior Vice President of Product Management Ziad Asghar to talk about on-device generative AI. The discussion covers a range of topics from day-to-day use cases to scaling issues for computing resources and working with partners and the community to unlock new generative AI experiences across the Snapdragon product line.

Click the play button to listen to the podcast

You can read the transcript here.

Podcast Chapter Markers

01:35: Ziad starts by defining generative AI and comparing it with machine learning and other types of AI.

03:56: Ziad talks about AI experiences that are already present in Snapdragon-powered devices.

06:24: Ziad addresses the scaling issue for computing resources used to train large language models.

09:46: Ziad deep dives into the types of day-to-day applications for generative AI on devices like a smartphone.

13:34: Ziad talks about the hybrid AI model, involving both cloud interaction and edge.

15:43: Ziad on how Qualcomm is leveraging its silicon chip capabilities to unlock generative AI experiences.

19:20: Ziad on how Qualcomm is working with its ecosystem and the developer community.

21:57: Ziad touches on the privacy and security aspect with respect to on-device generative AI.

Also available for listening/download on:

 

Global Smartphone Application Processor (AP) Market Share: By Quarter

Global Smartphone AP (Application Processor) Shipments Market Share: Q1 2022 to Q2 2023

Published Date: September 7, 2023

A repository of quarterly data for the global smartphone AP market based on smartphone AP/SoC shipment numbers.

Global Smartphone Application Processor (AP) Market Share: Q2 2023This data is based on the smartphone AP/SoC shipments

Note: Totals may not add up due to rounding

Global Smartphone Chipset Market Share (Q1 2022 – Q2 2023)
Brands Q1 2022 Q2 2022 Q3 2022 Q4 2022 Q1 2023 Q2 2023
Mediatek 36% 36% 35% 33% 33% 30%
Qualcomm 34% 32% 32% 19% 27% 29%
Apple 14% 13% 16% 28% 26% 19%
UNISOC 11% 11% 9% 11% 8% 15%
Samsung 5% 8% 8% 8% 4% 7%
HiSilicon
(Huawei)
1% 0% 0% 0% 0% 0%
Others 0% 0% 1% 1% 1% 1%

Source: Global Smartphone AP-SoC Shipments & Forecast Tracker by Model – Q2 2023

DOWNLOAD:

(Use the buttons below to download the complete chart)
    

Highlights:

Apple’s sales declined in Q2 2023 due to seasonality. Its Pro series did better.

MediaTek’s shipments increased slightly in Q2 2023 with reduced inventory levels and growing competition in the entry-level 5G smartphone market. New smartphone launches in the low-to-mid-end segments increased the shipments of Dimensity 6000 and Dimensity 7000 series. The Dimensity 9200 Plus was added to the premium tier.

Qualcomm’s shipments increased in Q2 2023 due to the Snapdragon 8 Gen 2’s adoption in Samsung’s flagship smartphones and by Chinese OEMs. The launch of Samsung’s Flip and Fold series also contributed to this growth. Qualcomm refreshed the Snapdragon 7 Gen 1, Snapdragon 6 Gen 1 and Snapdragon 4 Gen 1 series to gain some share back. However, the premium segment’s growth remained in focus.

Samsung’s shipments increased in Q2 2023. The Exynos 1330 and 1380’s launch added volumes to the low and mid-high segments.

UNISOC’s shipments grew in Q2 2023 after a weak Q1. It gained some share in the $100-$150 LTE segment. In H2 2023, as entry-level 5G smartphones pick up in regions like LATAM, SEA, MEA and Europe, UNISOC will gain some share.

For a more detailed smartphone AP-SoC shipments & forecast tracker, click below:

Global Smartphone AP-SOC Shipment & Forecast Tracker by Model – Q2 2023

This report tracks the smartphone AP/SoC Shipments by Model for all the vendors. The scope of this report is from the AP/SoC shipments from all the key vendors like Apple, Qualcomm, MediaTek, Huawei, Samsung, UNISOC and JLQ. We have covered all the main models starting from Q1 2020 to Q2 2023. We have also included a one-quarter forecast for Q3E 2023. This report will help you to understand the AP/SoC Market from the shipment perspective. Furthermore, we have also covered key specs for these AP/SoC covering market view by:

  • Network (4G/5G AP/SoC)
  • Foundry Details (like TSMC, Samsung. etc.)
  • Process node (5nm, 6nm, 8nm, etc.)
  • Manufacturing Process (FinFET, N7, N5, etc.)
  • CPU Cores Architecture and CPU Cores Count
  • Modem (External/Internal)
  • Modem Name
  • Secure Element Presence
  • Security Chip
  • AI Accelerator
       

For detailed insights on the data, please reach out to us at sales(at)counterpointresearch.com. If you are a member of the press, please contact us at press(at)counterpointresearch.com for any media enquiries.

Related Posts:

       

      

Related Posts

Podcast #69: ChatGPT and Generative AI: Differences, Ecosystem, Challenges, Opportunities

Generative AI has been a hot topic, especially after the launch of ChatGPT by OpenAI. It has even exceeded Metaverse in popularity. From top tech firms like Google, Microsoft and Adobe to chipmakers like Qualcomm, Intel, and NVIDIA, all are integrating generative AI models in their products and services. So, why is generative AI attracting interest from all these companies?

While generative AI and ChatGPT are both used for generating content, what are the key differences between them? The content generated can include solutions to problems, essays, email or resume templates, or a short summary of a big report to name a few. But it also poses certain challenges like training complexity, bias, deep fakes, intellectual property rights, and so on.

In the latest episode of ‘The Counterpoint Podcast’, host Maurice Klaehne is joined by Counterpoint Associate Director Mohit Agrawal and Senior Analyst Akshara Bassi to talk about generative AI. The discussion covers topics including the ecosystem, companies that are active in the generative AI space, challenges, infrastructure, and hardware. It also focuses on emerging opportunities and how the ecosystem could evolve going forward.

Click to listen to the podcast

Click here to read the podcast transcript.

Podcast Chapter Markers

01:37 – Akshara on what is generative AI.

03:26 – Mohit on differences between ChatGPT and generative AI.

04:56 – Mohit talks about the issue of bias and companies working on generative AI right now.

07:43 – Akshara on the generative AI ecosystem.

11:36 – Akshara on what Chinese companies are doing in the AI space.

13:41 – Mohit on the challenges associated with generative AI.

17:32 – Akshara on the AI infrastructure and hardware being used.

22:07 – Mohit on chipset players and what they are actively doing in the AI space.

24:31 – Akshara on how the ecosystem could evolve going forward.

Also available for listening/download on:

 

5G Advanced and Wireless AI Set To Transform Cellular Networks, Unlocking True Potential

The recent surge in interest in generative AI highlights the critical role that AI will play in future wireless systems. With the transition to 5G, wireless systems have become increasingly complex and more challenging to manage, forcing the wireless industry to think beyond traditional rules-based design methods.

5G Advanced will expand the role of wireless AI across 5G networks introducing new, innovative AI applications that will enhance the design and operation of networks and devices over the next three to five years. Indeed, wireless AI is set to become a key pillar of 5G Advanced and will play a critical role in the end-to-end (E2E) design and optimization of wireless systems. In the case of 6G, wireless AI will become native and all-pervasive, operating autonomously between devices and networks and across all protocols and network layers.

E2E Systems Optimization

AI has already been used in smartphones and other devices for several years and is now increasingly being used in the network. However, AI is currently implemented independently, i.e. either on the device or in the network. As a result, E2E systems performance optimization across devices and network has not been fully realized yet. One of the reasons for this is that on-device AI training has not been possible until recently.

On-device AI will play a key role in improving the E2E optimization of 5G networks, bringing important benefits for operators and users, as well as overcoming key challenges. Firstly, on-device AI enables processing to be distributed over millions of devices thus harnessing the aggregated computational power of all these devices. Secondly, it enables AI model learning to be customized to a particular user’s personalized data. Finally, this personalized data stays local on the device and is not shared with the cloud. This improves reliability and alleviates data sovereignty concerns. On-device AI will not be limited to just smartphones but will be implemented across all kinds of devices from consumer devices to sensors and a plethora of industrial equipment.

New AI-native processors are being developed to implement on-device AI and other AI-based applications. A good example is Qualcomm’s new Snapdragon X75 5G modem-RF chip, which has a dedicated hardware tensor accelerator. Using Qualcomm’s own AI implementation, this Gen 2 AI processor boosts the X75’s AI performance more than 2.5 times compared to the previous Gen 1 design.

While on-device AI will play a key role in improving the E2E performance of 5G networks, overall systems optimization is limited when AI is implemented independently. To enable true E2E performance optimization, AI training and inference needs to be done on a systems-wide basis, i.e.  collaboratively across both the network and the devices. Making this a reality in wireless system design requires not only AI know-how but also deep wireless domain knowledge. This so-called cross-node AI is a key focus of 5G Advanced with a number of use cases being defined in 3GPP’s Release 18 specification and further use cases expected to be added in later releases.

Wireless AI: 5G Advanced Release 18 Use Cases

3GPP’s Release 18 is the starting point for more extensive use of wireless AI expected in 6G. Three use cases have been prioritized for study in this release:

  • Use of cross-node Machine Learning (ML) to dynamically adapt the Channel State Information (CSI) feedback mechanism between a base station and a device, thus enabling coordinated performance optimization between networks and devices.
  • Use of ML to enable intelligent beam management at both the base station and device, thus improving usable network capacity and device battery life.
  • Use of ML to enhance positioning accuracy of devices in both indoor and outdoor environments, including both direct and ML-assisted positioning.

Channel State Feedback:

CSI is used to determine the propagation characteristics of the communication link between a base station and a user device and describes how this propagation is affected by the local radio environment. Accurate CSI data is essential to provide reliable communications. With traditional model-based CSI, the user device compresses the downlink CSI data and feeds the compressed data back to the base station. Despite this compression, the signalling overhead can still be significant, particularly in the case of massive MIMO radios, reducing the device’s uplink capacity and adversely affecting its battery life.

An alternative approach is to use AI to track the various parameters of the communications link. In contrast to model-based CSI, a data driven air interface can dynamically learn from its environment to improve performance and efficiency. AI-based channel estimation thus overcomes many of the limitations of model-based CSI feedback techniques resulting in higher accuracy and hence an improved link performance. The is particularly effective at the edges of a cell.

Implementing ML-based CSI feedback, however, can be challenging in a system with multiple vendors. To overcome this, Qualcomm has developed a sequential training technique which avoids the need to share data across vendors. With this approach, the user device is firstly trained using its own data. Then, the same data is used to train the network. This eliminates the need to share proprietary, neural network models across vendors. Qualcomm has successfully demonstrated sequential training on massive MIMO radios at its 3.5GHz test network in San Diego (Exhibit 1).

Wireless AI
© Qualcomm Inc.

Exhibit 1: Realizing system capacity gain even in challenging non-LOS communication

AI-based Millimetre Wave Beam Management:

The second use case involves the use of ML to improve beam prediction on millimetre wave radios. Rather than continuously measuring all beams, ML is used to intelligently select the most appropriate beams to be measured – as and when needed. A ML algorithm is then used to predict future beams by interpolating between the beams selected – i.e. without the need to measure the beams all the time. This is done at both the device and the base station. As with CSI feedback, this improves network throughput and reduces power consumption.

Qualcomm recently demonstrated the use of ML-based algorithms on its 28GHz massive MIMO test network and showed that the performance of the AI-based system was equivalent to a base case network set-up where all beams are measured.

Precise Positioning:

The third use case involves the use of ML to enable precise positioning. Qualcomm has demonstrated the use of multi-cell roundtrip (RTT) and angle-of-arrival (AoA)-based positioning in an outdoor network in San Diego. The vendor also demonstrated how ML-based positioning with RF finger printing can be used to overcome challenging non-line of sight channel conditions in indoor industrial private networks.

An AI-Native 6G Air Interface

6G will need to deliver a significant leap in performance and spectrum efficiency compared to 5G if it is to deliver even faster data rates and more capacity while enabling new 6G use cases. To do this, the 6G air interface will need to accommodate higher-order Giga MIMO radios capable of operating in the upper mid-band spectrum (7-16GHz), support wider bandwidths in new sub-THz 6G bands (100GHz+) as well as on existing 5G bands. In addition, 6G will need to accommodate a far broader range of devices and services plus support continuous innovation in air interface design.

To meet these requirements, the 6G air interface must be designed to be AI native from the outset, i.e. 6G will largely move away from the traditional, model-driven approach of designing communications networks and transition toward a data-driven design, in which ML is integrated across all protocols and layers with distributed learning and inference implemented across devices and networks.

This will be a truly disruptive change to the way communication systems have been designed in the past but will offer many benefits. For example, through self-learning, an AI-native air interface design will be able to support continuous performance improvements, where both sides of the air interface — the network and device — can dynamically adapt to their surroundings and optimize operations based on local conditions.

5G Advanced wireless AI/ML will be the foundation for much more AI innovation in 6G and will result in many new network capabilities. For instance, the ability of the 6G AI native air interface to refine existing communication protocols and learn new protocols coupled with the ability to offer E2E network optimization will result in wireless networks that can be dynamically customized to suit specific deployment scenarios, radio environments and use cases. This will a boon for operators, enabling them to automatically adapt their networks to target a range of applications, including various niche and vertical-specific markets.

Related Posts:

White Paper: Growing 5G+Wi-Fi RF Complexity Demands Innovative, Advanced & Tightly Integrated RFFE Solutions

Summary:

The rising adoption of advanced multimode cellular (5G, 4G) and wireless (Wi-Fi 6/6E/7) delivers powerful benefits while also driving significant RF complexity in smart connected devices. 5G and Wi-Fi 7 integration has multiple challenges that need cutting-edge RF design, components and end-to-end optimization. There are multiple players in the RF Front-End (RFFE) ecosystem, but most are specialists in only one or a few areas.

This paper highlights the technology potential of these powerful wireless technologies, complexity it brings and how product designers and manufacturers can solve these complexities with an advanced, end-to-end optimized and integrated RFFE solution.

Table of Contents:

  • Executive Summary
  • Proliferating 5G+Wi-Fi 7 A Massive Opportunity
  • 5G+Wi-Fi 7 Takes Wireless Performance to the Next Level
  • 5G+Wi-Fi 7 Coexistence Brings RF Complexity
  • 5G+Wi-Fi 7 Solutions for Potential Challenges to Performance Enhancement
  • Key Takeaways

Number of Pages: 

Authors:

Neil Shah

Research Vice President

  

Parv Sharma

Senior Analyst

  

Download the full white paper using the form below

Related Posts

Video: MySmartPrice x Counterpoint Present Tech in Focus: Smartphone Edition

MySmartPrice Tech in Focus concluded on June 21 with a huge response from the audience and brand representatives. The event witnessed over 250 registrations and 150 concurrent viewers watching the insights from the current smartphone landscape in India.  The panelists included:

Murlikrishnan B 

President

Xiaomi India

Sachin Kalantri 

Senior Director

Qualcomm

Tarun Pathak 

Research Director

Counterpoint Research

Sohail Khan 

Marketing Head

MySmartPrice


Check out the highlights from MySmartPrice Tech in Focus 2023:

MySmartPrice and Counterpoint Present Tech in Focus: Smartphone Edition

We are thrilled to unveil our upcoming joint webinar with MySmartPrice!

Tech in Focus is an initiative by MySmartPrice to bring the best minds in the tech ecosystem under one roof and discuss future trends backed by data. ​This time, MySmartPrice has teamed up with Counterpoint Research to bring a power-packed session around the changing smartphone landscape.

​The event will see data about the Smartphone ecosystem that Counterpoint Research shares and consumer preference insights that MySmartPrice shares.

​The event will also have a panel discussion with some of the biggest names in the smartphone industry.

When: June 21 | 3:30 PM to 5:00 PM GMT+5:30 | Where: Virtual Event

Panellists:

Murlikrishnan B 

President

Xiaomi India

Sachin Kalantri 

Senior Director

Qualcomm

Tarun Pathak 

Research Director

Counterpoint Research

Sohail Khan 

Marketing Head

MySmartPrice


Who should attend?

  • ​CXOs of Tech brands
  • ​Brand and product heads
  • ​Media and PR professionals reporting on Tech
  • ​Anyone researching the Tech Ecosystem

​The audience will have the opportunity to engage with the speakers, ask questions, and gain a deeper understanding of the dynamic smartphone ecosystem in India.


Registration: Please register to participate in this insightful event. Space is limited, so we encourage you to secure your spot asap.


​About MySmartPrice:

​MySmartPrice is the largest shopping discovery platform for tech in India. Every month, 20mn+ shoppers visit MySmartPrice to research and know more about what they should buy and which tech is better

Related Posts

COMPUTEX 2023: AI Solutions, Capabilities in Focus

Tech giants showcased their most advanced solutions in AI and computing at the COMPUTEX 2023 show in Taipei in the first week of June. If NVIDIA CEO Jensen Huang’s keynote address focused on the company’s game-changing innovations around AI, Arm CEO Rene Haas’ keynote had compelling demonstrations showcasing Arm’s capabilities in AI. Qualcomm focused on on-device intelligence enhancement and Hybrid AI as the mainstream format of AI in the future. With meaningful upgrades in computing capability, we expect to see the beginning of a new chapter in the coming years. In the following sections, we summarize the key takeaways from COMPUTEX 2023.

NVIDIA: Grace Hopper Superchip to boost AI revolution 

The world’s first-of-its-kind Grace Hopper Superchip, which is manufactured by the TSMC 4nm process node, is likely to level up NVIDIA’s determination on AI. In addition, more GPUs will be used for generative AI training and inference models, which will accelerate the transformative technology in the near term, highlighted Mr. Huang.

Our Associate Director, Brady Wang, shared his ideas and insights at the influential event.

NVIDIA also introduced the Spectrum-X platform, a fusion of the Spectrum-4 switch and Bluefield-3 DPUs, which boasts a record 51Tb/sec Ethernet speed and is tailor-made for AI networks. Combined with BlueField-3 DPUs and NVIDIA LinkX optics, it forms an end-to-end 400GbE network optimized for AI clouds. This innovation not only fits NVIDIA’s target but also consumes a great amount of foundry capacity, especially TSMC.

NVIDIA ACE Framework

Counterpoint Research - Nvidia ACE_Dark
Source: Nvidia

NVIDIA: Avatar Cloud Engine (ACE) for Games

NVIDIA did not forget its loyal gamers. This time, it introduced the Avatar Cloud Engine (ACE) for Games, a groundbreaking custom AI model service. ACE empowers non-playable characters (NPCs) in games with AI-driven natural language interactions, revolutionizing the gaming experience. With ACE, gamers can enjoy more immersive and intelligent gameplay.

Notes from analyst Q&A with NVIDIA founder and CEO Jensen Huang

  • If most of the workload involves training AI models, the data center operates as an AI factory. An optimal computer is capable of handling both training and inference tasks, although the selection of processors is contingent upon the specific inference type. 
  • In the foreseeable future, AI is poised to become the predominant force within the realm of NPCs in video games. These NPCs will possess a distinctive narrative and contextual background, effortlessly engaging with one another in a harmonious manner. Their movements will be fluid and their comprehension of instructions will be exceptional.
  • AI revolutionizes the user experience on PCs, propelling the advancement of personalized recommender systems. Furthermore, even on compact smartphones, it taps into extensive personalized internet data. As a result, future interactions generate real-time, customized content, transitioning towards generative processing to accommodate the escalating demand for personalized information. This groundbreaking development signifies the dawning of a new era characterized by the proliferation of generated and augmented information, thereby departing from the previously dominant retrieval-centric paradigm.
  • InfiniBand excels in high-performance computing, offering superior throughput for single computers and AI factories. It dominates in supercomputers and AI systems, while Ethernet is prevalent in cloud environments.
  • China leads the way in cloud services, consumer internet and digital payments. It has swiftly advanced in electric and autonomous vehicles, showcasing local innovation through numerous GPU start-ups. This underscores China’s technological dominance and promising future growth.
  • Omniverse streamlines computer setup with cloud integration and partnerships, enabling effortless information streaming through browser-based access. It optimizes factory design and simulation, minimizing work, errors and expenses.

Arm: Everything now is a computer; AI runs on Arm

Citing the remarkable 260% increase in data center workloads from 2015 to 2021, Arm CEO Rene Haas emphasized the pivotal role of data centers, automotive technology and AI in driving the compute demand powered by ARM designs.

According to Counterpoint Research, Arm-based notebooks will gain over Intel and AMD, almost doubling their shipment share to 25% by 2027 from 14% today.

Laptop Shipment Share by CPU/SoC Type %

Counterpoint Research - laptop shipment by CPU type

source: Counterpoint Research

AI emerged as a focal point during Haas’ keynote, where he captivated the audience with compelling demonstrations showcasing Arm’s capabilities. That said, Arm is poised to support an even broader range of applications in the future.

We also echo Arm’s view and believe that generative AI, digital twins and edge computing will emerge as top technology trends in 2023 and affect the whole tech industry.

Qualcomm: Focus on on-device intelligence enhancement, Hybrid AI

Qualcomm’s “AI” Hexagon processor offers 3-5 times better computing performance compared to existing CPU/GPU solutions. The company aims to expand the application of its Snapdragon 8cx Gen 3 processor to the laptop industry with thorough support from Microsoft.

For AI, Qualcomm believes there are limitations to the efficiency improvements of Edge AI or Cloud AI. However, leveraging Qualcomm’s connectivity solutions and combining edge AI with cloud AI can provide incremental benefits in terms of cost/energy savings, privacy and security enhancements, reliability, and latency. Therefore, the company guides that Hybrid AI (Edge AI + Cloud AI) will be the mainstream format of AI in the future.

Conclusion

With the COVID-19 pandemic loosening its grip, COMPUTEX was back in its on-site mode this year in Taipei with solid and eye-catching AI solutions. We are stepping into a new computing era, with generative AI set to transform our lives. Not only server vendors and data center hyper-scalers, but mobile and PC vendors are also working together to facilitate technology improvements with AI support.

Counterpoint’s analysts continue to work closely with the tech product market to monitor all changes and trends.

Related Posts

BoM Analysis: Samsung Galaxy S23 Ultra Costs $469 to Make

  • Qualcomm takes the top spot in terms of cost contribution, accounting for over 34% of the model’s BoM cost.
  • Qualcomm and Samsung combined contribute more than 65% of the component cost in the Galaxy S23 Ultra.
  • Featuring Qualcomm’s custom Snapdragon chipset, Samsung’s Galaxy S23 Ultra makes a considerable leap in computing performance with its shift to TSMC’s 4nm process node.

Producing an 8GB+256GB Galaxy S23 Ultra (Sub-6GHz) variant costs Samsung around $469, according to the latest bill of materials (BoM) analysis by Counterpoint’s component research service. The major components driving cost in the smartphone are the SoC, display and camera subsystem. Due to excess inventory and supply, components related to the RF sub-system and memory were subjected to a cost decrease.

Samsung Galaxy S23 Ultra BoM share (%)

Qualcomm and Samsung’s design wins

The S23 Ultra further builds upon Qualcomm’s design, showcasing a customized version of the Snapdragon 8 Gen 2 chipset, manufactured on TSMC’s 4nm process node. Samsung has chosen Qualcomm chipsets due to enhanced cellular support, increased performance gain from both the CPU and GPU, and better battery life. The GPU also has support for raytracing and has gained a slight uplift of 39MHz clock speed.

Qualcomm’s share in the S23 Ultra has increased to an all-time high after attaining design wins for the fingerprint sensor IC, key power management ICs, audio codec, RF power amplifiers, Wi-Fi + Bluetooth, GPS and Sub-6GHz transceiver.

Samsung is the second largest beneficiary. It is an exclusive supplier of the 256GB NAND flash and the 6.8-inch AMOLED display for the S23 Ultra. The display can sustain 1750 nits of peak brightness and has a resolution of 1440 x 3088 pixels that allows the users to view pictures and videos in sharp detail. The 120Hz LTPO panel also supports adaptive refresh rate.

In the camera sub-system, the design wins are shared between Samsung (SEMCO) and Sony. Samsung provides the 200MP wide-angle camera (S5KHP2) and the 12MP selfie camera (S5K3LU), while Sony offers the 12MP Ultrawide (IMX564), 10MP Telephoto and Periscope Telephoto (IMX754) sensors.

Samsung Galaxy S23 Ultra Design wins

Other component suppliers

Silicon Mitus and Maxim are the providers of power management ICs that support the regulation of power for display and other key components.

For sensing components, STM has registered design wins related to the laser autofocus module, accelerometer, gyroscope, barometer, and touch panel controller. The battery is packaged by Samsung and the cell is provided by ATL. The quick charging IC, which charges up to 45W, is sourced from NXP while the 15W wireless charging IC is from Convenient Power.

Samsung’s sourcing strategy and choice of components are enabling the brand to have a competitive edge in terms of cost efficiency.

For detailed component and pricing analyses, queries, or for acquiring this research, contact info@counterpointresearch.com

Related Posts

Term of Use and Privacy Policy

Counterpoint Technology Market Research Limited

Registration

In order to access Counterpoint Technology Market Research Limited (Company or We hereafter) Web sites, you may be asked to complete a registration form. You are required to provide contact information which is used to enhance the user experience and determine whether you are a paid subscriber or not.
Personal Information When you register on we ask you for personal information. We use this information to provide you with the best advice and highest-quality service as well as with offers that we think are relevant to you. We may also contact you regarding a Web site problem or other customer service-related issues. We do not sell, share or rent personal information about you collected on Company Web sites.

How to unsubscribe and Termination

You may request to terminate your account or unsubscribe to any email subscriptions or mailing lists at any time. In accessing and using this Website, User agrees to comply with all applicable laws and agrees not to take any action that would compromise the security or viability of this Website. The Company may terminate User’s access to this Website at any time for any reason. The terms hereunder regarding Accuracy of Information and Third Party Rights shall survive termination.

Website Content and Copyright

This Website is the property of Counterpoint and is protected by international copyright law and conventions. We grant users the right to access and use the Website, so long as such use is for internal information purposes, and User does not alter, copy, disseminate, redistribute or republish any content or feature of this Website. User acknowledges that access to and use of this Website is subject to these TERMS OF USE and any expanded access or use must be approved in writing by the Company.
– Passwords are for user’s individual use
– Passwords may not be shared with others
– Users may not store documents in shared folders.
– Users may not redistribute documents to non-users unless otherwise stated in their contract terms.

Changes or Updates to the Website

The Company reserves the right to change, update or discontinue any aspect of this Website at any time without notice. Your continued use of the Website after any such change constitutes your agreement to these TERMS OF USE, as modified.
Accuracy of Information: While the information contained on this Website has been obtained from sources believed to be reliable, We disclaims all warranties as to the accuracy, completeness or adequacy of such information. User assumes sole responsibility for the use it makes of this Website to achieve his/her intended results.

Third Party Links: This Website may contain links to other third party websites, which are provided as additional resources for the convenience of Users. We do not endorse, sponsor or accept any responsibility for these third party websites, User agrees to direct any concerns relating to these third party websites to the relevant website administrator.

Cookies and Tracking

We may monitor how you use our Web sites. It is used solely for purposes of enabling us to provide you with a personalized Web site experience.
This data may also be used in the aggregate, to identify appropriate product offerings and subscription plans.
Cookies may be set in order to identify you and determine your access privileges. Cookies are simply identifiers. You have the ability to delete cookie files from your hard disk drive.