(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.
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 fromQ1 2020 to Q2 2023. We have also included aone-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 atsales(at)www.arena-ruc.com. If you are a member of the press, please contact us atpress(at)www.arena-ruc.comfor any media enquiries.
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’, hostMaurice Klaehneis joined by Counterpoint Associate DirectorMohit Agrawaland Senior AnalystAkshara Bassito 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.
最近的兴趣激增生成AI高lights 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.
5GAdvanced 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 of5G Advancedand will play a critical role in the end-to-end (E2E) design and optimization ofwireless系统。在6克的情况下,无线AI会变得e native and all-pervasive, operating autonomously between devices and networks and across all protocols and network layers.
E2E Systems Optimization
AIhas 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 thenetwork. 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 foroperatorsand 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 enablesAImodel 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 thecloud. 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-nativeprocessorsare being developed to implement on-device AI and other AI-based applications. A good example isQualcomm’snew 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 of5G 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 in6G. 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 ofMLto 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).
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.
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 moreAIinnovation 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.
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
增殖5 g + Wi-Fi 7 A Massive Opportunity
5G+Wi-Fi 7 Takes Wireless Performance to the Next Level
5 g + wi - fi 7共存带来的射频的复杂性
5G+Wi-Fi 7 Solutions for Potential Challenges to Performance Enhancement
MySmartPrice Tech in Focusconcluded 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:
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Murlikrishnan B
President
Xiaomi India
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[one_fourth]
Sachin Kalantri
Senior Director
Qualcomm
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[one_fourth]
Tarun Pathak
Research Director
Counterpoint Research
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Sohail Khan
Marketing Head
MySmartPrice
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Check out the highlights from MySmartPrice Tech in Focus 2023:
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.
The audience will have the opportunity to engage with the speakers, ask questions, and gain a deeper understanding of thedynamic smartphone ecosystemin India.
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Registration: Please register to participate in this insightful event.Space is limited, so we encourage you to secure your spot asap.
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
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 ofAIin 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 willacceleratethe 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 forAI 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
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 onPCs, 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首席执行官雷内·哈斯强调数据的关键作用centers, automotive technology and AI in driving the compute demand powered by ARM designs.
According to Counterpoint Research,Arm-based notebookswill gain over Intel and AMD, almost doubling their shipment share to 25% by 2027 from 14% today.
Laptop Shipment Share by CPU/SoC 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,COMPUTEXwas back in its on-site mode this year in Taipei with solid and eye-catching AI solutions. We are stepping into a newcomputingera, 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.
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 thesmartphoneare the SoC, display and camera subsystem. Due to excess inventory and supply, components related to theRF sub-systemand memory were subjected to a cost decrease.
Qualcomm and Samsung’s design wins
TheS23 Ultrafurther builds upon Qualcomm’s design, showcasing a customized version of the Snapdragon 8 Gen 2 chipset, manufactured onTSMC’s 4nm process node. Samsung has chosenQualcomm chipsetsdue 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,RFpower amplifiers, Wi-Fi + Bluetooth, GPS and Sub-6GHz transceiver.
Samsung is the second largest beneficiary. It is an exclusive supplier of the 256GBNAND flashand the 6.8-inch AMOLED display for the S23 Ultra. Thedisplaycan 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 thecamera 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.
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,STMhas 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 fromNXP而从Conveni 15 w无线充电ICent Power.
Samsung’ssourcing strategyand 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, contactinfo@www.arena-ruc.com
The transition of the Radio Access Network (RAN) from a standalone, integrated network into a disaggregated, virtualized solution is well underway. However, all open RAN deployments to date rely on Intel’s x86-based COTS servers, with most deployments also using Intel’s proprietary FlexRANsoftwarearchitecture. Recently, various silicon vendors have announced that they are developing alternatives to Intel’s x86 platform based on ASICs, GPUs as well RISC-V architectures. Several of these vendors are currently testing their new PCIe-based Layer-1 accelerator cards with CSPs and commercial versions of these products are expected to become widely available during the next three years.
Thisreportprovides an overview of the emerging open RAN PCIe-based Layer-1 accelerator cardmarketbased on new merchant silicon and highlights the opportunities and technical challenges facing the open RAN chip community as they strive to develop alternativechipsolutions capable of efficiently processing real-time, latency-sensitive Layer-1 workloads.
Key Takeaway No. 1: Too much diversity?
The launch of new L1 accelerator cards from various vendors, large and small, should be welcomed by CSPs calling fordiversityand will go some way to quell criticism that the openRANmarket is too Intel-based. However, CSPs may now be faced with another dilemma – too much choice! They must now face the difficult challenge of testing and comparing multiple accelerator cards, inevitably involving complicated technical and commercial trade-offs.
Key Takeaway No. 2: Look-Aside or In-Line Accelerators?
At present, the choice ofacceleratorarchitecture is binary: either look-aside or inline. Both types have their advantages and drawbacks. Depending on use cases and applications, Counterpoint Research believes thatoperators可能需要使用两种类型的加速器。但仍r, only one vendor currently offers a software/silicon platform with the capability to do this.
Key Takeaway No. 3: Interoperability and Vendor Lock-In
Developing commercial-grade Layer 1 software suitable for massive MIMO networks is an expensive process requiring very specific skills and a lot of experience – but with no guarantee of commercial success. Although openRANis designed to promote interoperability and vendor diversity, all L1 stacks are currently tied to the underlying silicon architectures and hence are not portable between hardware platforms. This introduces a new form of vendor lock-in for CSPs. Clearly, there is an urgent need for an universal software abstraction layer between the L1 stack and the various hardware platforms to enable stack portability.
The complete versions of these Key Takeaways, including the full set of Takeaways is published in the following report, available to clients of Counterpoint Research’s5G Network Infrastructure (5GNI) Service.
Smartwatches, AR/VR and smart glasses were everywhere at MWC.
An unconventional attempt from Huawei stands out for smartwatch. OEMs seem to have begun to consider a new form factor beyond functionality.
Qualcomm’s Snapdragon Spaces, XR developer platform will help expand the XR market by enabling more diverse content development.
Wearable devices are evolving and their future market prospects appear to be bright. Innovations in this sphere are getting more intriguing not only for device manufacturers, component suppliers, application developers and platform companies, but also for potential consumers. DuringMWC Barcelona, 2023, various new products and technologieswere showcased that attracted a lot of attention. Here is a summary of some of the key wearable innovations announced during the event:
Notable Devices
Smartwatch: Smartwatches have become the new battleground for smartphone OEMs. To differentiate their products amid intensifying competition, OEMs are emphasizing on conventional watch designs or on experimental form factors.
Xiaomi S1 Pro: During Xiaomi’sMi 13 seriessmartphone launch event, the company emphasized on its latest smartwatch the S1 Pro’s traditional design and connectivity with other devices. The long battery life of up to 14 days is one of the device’s key strengths. Through this launch event, Xiaomi attempted to solidify its ecosystem by establishing connectivity between smartphones and wearables, such as their smartwatches and earbuds.
Huawei Watch Buds and Watch GT Cyber: Huawei presented two experimental smartwatches at MWC 2023. The Watch Buds is a combination of a smartwatch and a set of earbuds. The device is designed to store earphones inside the watch display. Meanwhile, the GT Cyber’s design allows the bezel and strap to be separated. This indicated the possibility of the device evolving into a modular smartwatch like LG’s G smartphone series in the past.
Smart Glasses: Many Chinese consumer IT vendors who were absent during CES participated in MWC 2023, exhibiting their latest smart glasses. As smart glasses equipped with AR functions become mainstream, light and comfortable-to-wear glasses-type smart wearables are emerging as a form factor that can provide optimal user experiences for both consumers and businesses in the future.
OPPO Air Glass 2: OPPO’s smart glasses, the Air Glass 2, was unveiled atOPPO INNO Day2023年1月。公司集中在超light design of the glasses, which can be worn for a long time, as it weighs only about 38g. The device is equipped with the world’s first diffractive waveguide lens developed in-house. A voice-to-text conversion function has been added for the hearing impaired, in addition to the basic functions of AR glasses, such as making a phone call, translating and navigating. This is still only a concept product as mass production of the mounted Micro LED display has not yet been achieved. It is highly likely that it will take a long time to commercialize the glasses or for them to be sold only in China on a small scale.
ZTE Nubia Neovision Glass: ZTE unveiled its first AR smart glasses as the company pursues versatility to meet users’ needs not only in daily life but also in work environments, sports and entertainment. It has a Micro OLED display and will be released in China soon at a price of RMB2,999.
TCL NXTWEAR S: These smart XR glasses from TCL won the Best Connected Consumer Device Award at GLOMO 2023. The TCL NXTWEAR S is tethered with other devices such as smartphones and PCs. As its marketing concept, TCL emphasizes that the glasses appear like a 130-inch screen in front of the user’s eyes. In addition to the Micro OLED display, the glasses are equipped with an accelerometer, gyroscope and proximity sensor to focus more on gaming use cases. After TCL’s previous smart glasses, the NXTWEAR AIR, won the Most Innovative Award of The Year at CES 2022, the latest award at MWC proves that TCL has advanced the technology in this field.
New Innovations
eSIM
Mymanu Titan: Mymanu, a UK-based audio technology company founded in 2014, showcased the world’s first voice-controlledeSIM-enabled earbuds, called Titan, which allows a standalone connected “phone-free” experience. The earbuds also have built-in live voice translation. The eSIM feature allows Titan to connect to a 4G network with which a user can perform some basic tasks that do not require a smartphone, such as playing music, making calls and sending texts.
Googlefinally announced its eSIM plans allowing Android to streamline the eSIM transfer experience while switching phones. Deutsche Telekom will be one of the first to adopt eSIM transfer on Android smartphones.
Human Augmentation
Docomo’s Motion Sharing Platform: Human augmentation platforms facilitate remote sharing of feelings and sensations using special wearables. This will be a possible use case when 6G is commercialized. The connected robot moves according to the movements of the user, who is equipped with motion sensors. This is expected to be highly useful in dangerous work environments or in remote medical care and healthcare.
(Demonstration of Docomo’s Motion Sharing platform using 6G at MWC)
Mudra Air-Touch: Israel-based Wearable Devices exhibited the Mudra Air-Touch feature, a neural input technology, and the Mudra Band for Apple Watch. These are the company’s solutions to integrate its technology into consumer products. The Mudra Air-Touch feature seamlessly switches control from devices such as iPhones, iPads, Mac computers and Apple TV devices, as well as other connected devices, including smart glasses, using subtle finger and wrist movements from hands-free and touchless devices.
Rollable Display: Lenovo attracted a lot of attention with its concept devices, the rollable Motorola smartphone and the rollable notebook. These devices are equipped with a rollable display developed by BOE. The rollable display was first introduced by LG Display at CES in 2018. Since then, major display panel makers such as Samsung Display, BOE, Visionox and CSOT have disclosed that they have rollable technology. The rollable display technology fits very well with the requirements of wearable devices to be worn on parts of the body. Therefore, this will be an important part of the expansion of the wearable market, but before that, the excessively high price issue needs to be resolved.
Platform
Google Keep for Wear OS: Through Google Keep for Wear OS, Google has added a function that allows smartwatch users to make notes or to-do lists by simply tapping the clock screen. Wear OS 3+ also has a new sound mode, display mode and gray scale to improve the clock’s accessibility.
(Google Keep for Wear OS / Image source: Androidpolice.com)
Qualcomm Snapdragon Spaces: Qualcomm’s most impressive announcement was its collaboration with seven carriers (Vodafone, Deutsche Telecom, Telefonica, KDDI, DoCoMo, T-Mobile and China Mobile) for the XR expansion ecosystem. Based on Qualcomm’s Snapdragon Spaces’ XR developer platform, helping these carriers support and commercialize developers in their respective countries will generate more diverse content keys to expand the XR market. It is expected to grow into an XR platform that can compete with Apple’s ARKit.
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This data is based on the smartphone AP/SoC shipments
