MediaTek is set to enable ubiquitous AI computing from edge to cloud.
Aiming to mirror its success in mobile devices, MediaTek’s automotive platform is now locked and loaded.
Windows on Arm could be the next battlefield for MediaTek and other mobile players.
AI is changing the way people interact with technology. It allows a more immersive user experience and increased convenience when working with mobile devices. As one of the leading chip vendors for the mobile platform, MediaTek also provides solutions across handset, IoT and automotive segments. This year, MediaTek will work with NVIDIA to extend their partnership into PCs, with the launch of their first AI PC expected in 2025.
MediaTek to enable ubiquitous AI computing from edge to cloud
At Computex 2024, MediaTek announced the extension of its partnership with NVIDIA from automotive to cloud-based GenAI accelerator products. This suggests the potential for hybrid ASIC+GPU designs coming soon.
According to MediaTek CEO Rick Tsai, the total addressable market for customized Arm-based server CPUs will reach $5 billion in size by 2028, with custom AI accelerators leveling up to $40 billion market size. This implies that MediaTek is also set to enable AI computing from edge to cloud.
MediaTek’s automotive platform locked and loaded
Last year, MediaTek announced its partnership with NVIDIA for an automobile platform, Dimensity Auto Cockpit Drive OS. The companies see the platform as an outstanding solution leveraging rich IPs from both sides. MediaTek will embed high-performance computing, communication and connectivity technologies into the smart cockpit combined with NVIDIA’s advantage in AI and GPU to provide a better user experience and lower latency. We can expect the first car carrying the two companies’ leading technologies to be rolled out in 2025.
Source: MediaTek
Windows on Arm next battlefield for MediaTek, other mobile players?
Windows on Arm has been regaining its exposure and gradually seeing higher penetration in the quarters following Microsoft’s release of Windows 11 updates with Qualcomm’s Snapdragon X platform instead of Intel or AMD, which are key vendors for the x86 architecture. PC vendors including Lenovo, HP, Dell, Acer, Asus and Samsung have already introduced new AI laptops. We believe that as the exclusive agreement between Qualcomm and Microsoft expires in 2025, MediaTek will leverage its advantage in mobile platforms and the capability to step into the PC market.
Based on our checks, we expect MediaTek will likely launch a Windows-on-Arm solution in the second half of 2025 with a new brand name in addition to its Kompanio platform used for Chromebooks. Besides, MediaTek will extend its partnership with NVIDIA from the automotive to the PC industry, with the former focusing on CPU and connectivity and the latter providing NPU solutions. To catch up with leaders in the PC industry, the new Windows-on-Arm solution will likely be equipped with at least the same TOPS performance on its NPU as Qualcomm’s Snapdragon X platform (i.e. 45 TOPS), which is also in line with Microsoft’s minimum requirements for Copilot+. Meanwhile, an upgraded version of the Kompanio series is likely to be introduced to support the next-generation AI Chromebook, which is also one of MediaTek’s key product lines.
Commenting on MediaTek and NVIDIA’s partnership for Windows on Arm, Senior Analyst William Lielaborated: “The new PC solution from MediaTek and NVIDIA will likely trigger another wave of Arm PC expansion after Qualcomm’s Snapdragon X platform. If the Snapdragon X platform fares well in the second half of 2024, it would incentivize other players to join the market. Therefore, Windows on Arm could be the next battlefield for MediaTek and other mobile players.”
Unlike Google, Apple avoided creating any grandiose narrative for AI at WWDC. Instead, it focused on specific, practical applications.
Apple AI’s focus is on intuitive features and seamless cross-app integration.
Through the introduction of Apple Intelligence, Apple focuses on harnessing its chip expertise and hardware-software synergy.
The world has been anxiously waiting for Apple’s AI roadmap for over 18 months since the rise of ChatGPT, and it has finally arrived. In this blog, we provide a quick rundown of this year’s WWDC and key analyses of Apple’s AI strategy.
Clear, practical and intuitive AI features
Unlike Google, Apple avoided creating any grandiose narrative for AI. Instead, it focused on specific, practical applications. The company has introduced Apple Intelligence, which it describes as “the personal intelligence system for iPhone, iPad, and Mac that combines the power of generative models with personal context to deliver intelligence that is incredibly useful and relevant”. The focus here is on intuitive features and seamless cross-app integration:
Text: Apple Intelligence has introduced a feature called Priority Notifications. When this feature is enabled, the system sorts notifications based on their importance. The most critical information, such as an email containing the user’s boarding pass, will be displayed at the top.
Another key feature is the Systemwide Writing Tool, which is available across Mail, Notes, Pages and various third-party apps. Users can expand, proofread and summarize text in different applications. Besides, they can adjust the tone of their wording or receive suggestions for smart replies.
Image: Apple Intelligence introduces Genmoji and Image Wand features. Genmoji helps users create original images and emojis, but currently only supports sketch, cartoon and illustration styles. Image Wand can transform users’ rough hand-drawn sketches into more refined images. It can also generate images based solely on text descriptions, just like Stable Diffusion.
New Siri: The highlight of this event was the upgrade to Siri. Driven by Apple Intelligence, Siri is now equipped with a “semantic indexing feature”, promising a somatic understanding of its users’ intentions. This allows Siri to organize a semantic index library based on the user’s photos, calendar, files, emails and more, enabling smarter information search and retrieval.
It is worth noting that Apple has designed a brand-new framework for Apple Intelligence. This framework allows developers to introduce Apple Intelligence into their applications through the App Intents API. This means that Siri will be able to perform complex operations across multiple apps in the future.
Last but not least, Apple has entered a collaboration with OpenAI, linking the recently released GPT-4o model with Siri. Users can access most of the model’s features for free without needing to create an account.
AI strategy analyses
In the arena of large-model innovation and AGI race, Apple’s core technology has been admittedly lagging. However, at this year’s WWDC, the company’s precise tactical approach shone once again.
First and foremost, Apple highlights the existence of its proprietary AI models, marking its entry into the generative model arena. Unlike Google and Microsoft/OpenAI, Apple doesn’t have a frontier LLM. However, it has developed a suite of small and medium generative models, including a 3-billion-parameter on-device language model and a larger server-based model accessible via Private Cloud Compute on Apple silicon servers.
Apple leverages its unique ecosystem, mitigating the impact of its temporary technological lag. Through the introduction of Apple Intelligence, it focuses on harnessing its chip expertise and hardware-software synergy, emphasizing the “on-device” large-model capabilities and addressing common concerns about data security and user privacy in large-model applications. This creates a distinct space for Apple’s AI despite its initial shortcomings.
Apple develops partnerships with leading large-model provider OpenAI, establishing a connection between Siri and GPT-4o. This provides users access to the most advanced models.
However, Apple subtly downplayed the partnership with OpenAI, only announcing it at the end of the event. It emphasized that this collaboration would require user permission for external access rather than being deeply integrated at the OS level, ensuring the advanced model doesn’t overshadow Apple’s own systems.
In fact, Apple is adopting a model agnostic approach. Its partnership with leading LLM providers will not stop at OpenAI. Google’s Gemini and other specialized, fine-tuned large models could be the next in line for integration with the iPhone.
Recognizing that many iPhone users may be new to generative AI, Apple championed “AI for the rest of us” at WWDC. This consumer-friendly approach aims to drive widespread AI adoption on Apple devices. By leveraging its unique hardware, software and private cloud infrastructure, Apple not only differentiates itself from OpenAI but also strengthens user trust and reinforces customer loyalty.
In the fast-paced developments of generative AI, all the leading players, exemplified by OpenAI and Google, are trying to “move fast and break things”. Apple’s WWDC has signaled that the slow and steady can also win the race, especially in its edge AI.
In our upcoming short report on Apple Intelligence, we will further dissect Apple’s AI and its impacts on industry ecosystems and players. Moreover, Apple’s patent applications reveal numerous machine learning-powered innovations across its devices. Securing these patents not only strengthens Apple’s position in the AI devices market but also helps fend off competitors. Based on these insights, we will forecast Apple’s next strategic moves.
Over the next few years, 5G Advanced will provide networks with enhanced capabilities, including improved uplink, lower latency and better coverage resulting in higher network performance and increased reliability. This will enable operators to enhance existing services while generating additional sources of revenues via new services. However, to do this operators will need to maximise their spectrum assets across all bands, particularly their legacy Sub-3GHz spectrum.
Benefits of Sub-3GHz Bands
While higher TDD spectrum bands are being used to provide 5-10Gbps downlink speeds required for premium customer experiences, FDD Sub-3GHz spectrum is also needed to extend high-speed 5G mobile broadband coverage across urban, suburban and rural regions and to provide reliable coverage for IoT services. In particular, Sub-1GHz spectrum is vital for indoor coverage. In addition, FDD spectrum offers lower latency than TDD as different channels are used for the uplink and downlink channels.
Most operators have around 80-120MHz of Sub-3GHz spectrum as this was the primary spectrum used by previous cellular generations and most of this spectrum is becoming available for 5G as operators switch-off legacy 2G and 3G networks. Refarming existing FDD spectrum bands will allow operators to quickly build up their 5G footprint. However, as there is less spectrum available in the Sub-3GHz bands compared to higher bands, operators will need to introduce advanced radio technologies with much improved spectrum efficiencies, throughputs and latencies. In addition, this must be done using compact, cost-efficient radio solutions in order to keep capex and opex costs to a minimum.
FDD Triple-band MIMO and Massive MIMO
Several vendors offer 4T4R and 8T8R ultra-wideband modules for low-band (700MHz, 800MHz and 900MHz) and mid-band (1.8GHz, 2.1GHz, and 2.6GHz) frequencies. As a result, only two multi-antenna, single RAN RF modules are required to cover both spectrum bands – instead of six as with conventional radios. In addition, some vendors offer 32T32R massive MIMO modules which can be deployed in a compact radio/antenna enclosure for the mid-band spectrum bands.
FDD triple-band massive MIMO radios significantly boost capacity and coverage compared to conventional 4T4R radios. This enables operators to improve the spectrum efficiency of their existing Sub-3GHz resources, while at the same time, satisfying higher traffic demands and improving user experience. From an investment viewpoint, FDD massive MIMO radios also reduce operators’ overall capex and opex costs.
Key Radio Technologies
Key technologies at the heart of state-of-the-art FDD RF modules include FDD Beamforming, GigaBand multi-band fusion technology plus innovative energy-saving features enabled primarily by innovations in power amplifier technologies.
FDD Beamforming
To date, beamforming has primarily been used in TDD spectrum as operators initially deployed 5G in TDD bands. However, beamforming can also be used in FDD spectrum which has been supported since 3GPP’s Release 15 specification. As with TDD spectrum bands, the main benefit is increased spectrum efficiency as the directional beams focus the radio signals where they are needed rather than distributing them across the entire cell. This increases radio capacity and coverage while reducing interference. Increasing the number of transmit antenna – and hence the number of beams – means narrower and more focused beams, resulting in even higher capacity and better spectral efficiency.
Multi-Band Power Amplifier Technology
Multi-band technology allows the functionality of several radios to be combined into a single radio unit with a single transceiver accommodating two or three bands. A tri-band radio therefore only requires one power amplifier and one filter rather than three power amplifiers/filters as required in a conventional radio. This significantly increases the level of integration thereby reducing tower footprint. As traffic rarely peaks in all bands simultaneously, a multi-band power amplifier allows power to be dynamically shared between different bands. This means that it is possible to provide full power output for each band but without designing the power amplifier for simultaneous peak power in all bands.
GigaBand Technology
Compared to wide-band TDD spectrum, 700-900MHz low-band FDD spectrum is limited, fragmented and consists of narrow bandwidth channels. The same is true of 1.8-2.1/2.6GHz spectrum. GigaBand technology is a multi-band fusion technology that converts these disparate spectrum assets into a single 100MHz-wide FDD carrier. Using carrier aggregation and Multi-Band Serving Cell (MBSC) technology, six Sub-3GHz spectrum bands can be combined into a single carrier which maximises spectral efficiency.
Energy Saving AI Software
Service requirements are higher with 5G, which means that peak-to-average traffic ratios are also higher. As a result, the requirements for higher energy efficiency at peak hours and low power consumption in idle time are more urgent. AI software solutions are playing a major part to help reduce energy consumption in 5G networks by enabling shutdowns at network, cell and at radio levels coupled with fast wake-up capabilities, with AI/ML being used in real-time to optimise network parameters according to traffic demands.
In the radios, state-of-the-art AI-based software solutions can achieve “deep sleep dormancy” with very low power consumption in an idle state coupled with fast on-demand wake-up. For an operator using multiple frequency bands at a single cell, smart algorithms can progressively shut down different frequency bands depending on traffic loads until only one band is operating, with all other frequencies being in a dormant state.
Huawei FDD MIMO and massive MIMO Radios
In 2022, Huawei launched the industry’s first FDD triple-band MIMO modules supporting GHz-level bandwidths contained in a single radio box. The modules are available in 4T4R, 8T8R and 32T32R configurations.
GigaBand RF Modules – Huawei’s FDD ultra-wideband RF modules have an instantaneous bandwidth (IBW) in excess of 800MHz per module. This is a major advantage for operators with fragmented spectrum as one ultra-wideband radio can replace two or even three narrower band radios. Alternatively, ultra-wideband radios can be used for RAN sharing, which means that two operators can share one radio, again reducing capex and opex costs.
Advanced Power Amplifiers – key to this ultra-wideband capability is Huawei’s advanced power amplifier technology, which leverages breakthroughs in several technologies, including AI-based DPD[1] beamforming algorithms, advanced power amplifier architectures, RF filter materials and improved passive cooling via bionic heat sinks. Huawei claims that its power amplifiers are 10% more efficient than industry rivals and that its innovative filter materials generate 1dB less filter loss compared to industry rivals.
GigaGreen Platform – at the heart of the GigaGreen platform is Huawei’s “0-bit, 0-Watt” and “More-bit, Less-Watt” solutions, which leverage breakthroughs in materials technology, energy saving policy orchestration and smart algorithms. With millisecond level carrier and channel shutdown, Huawei’s “0-bit, 0-Watt” solution can achieve 99% “super deep sleep dormancy” enabling RF modules to consume almost zero power under low load, while its “More-bit, Less Watt” solution continuously minimizes energy consumption under medium and high loads – without compromising user experience. Achieving these low power consumption levels requires independent shutdown of individual power amplifiers and full power sharing across all carriers, frequency bands and Radio Access Technologies (RATs).
FDD sub-3GHz Deployment Example
FDD Sub-3GHz triple band radios are designed from the outset to simplify deployments at cell sites while reducing power consumption. For operators, this translates into capex and opex savings. For example, many operators use four or five FDD frequency bands at a single tower site. Traditionally, this would require four or five radios, i.e. one RF module per frequency band. However, with ultra-wideband 4T4R, 8T8R and 32T32R massive MIMO modules, only two radios are required. In addition, the operator has the option to add one (or two) additional frequency bands.
By combining an active massive MIMO radio/antenna with a six-band passive antenna into a single package, the number of “boxes” per sector can be reduced from seven to two (Exhibit 1). This enables new frequency bands to be added without increasing the number of base stations or power consumption while opex is also reduced.
Exhibit 1: Leveraging Ultra-Wideband Radios To Enable Site Simplification
Analyst Viewpoint
FDD technology at Sub-3GHz frequency bands is set to play a critical role as 5G Advanced is rolled out over the next few years. To fully leverage the opportunities offered by 5G Advanced, Counterpoint Research believes that it is imperative that operators maximise their existing FDD Sub-3GHz spectrum assets in order to ensure seamless coverage across urban, suburban and rural regions. Not only will this provide an enhanced user experience for customers, it will also enable operators to offer a range of new high-data, low-latency services with guaranteed service levels across their entire network footprint.
As less spectrum is available at Sub-3GHz, however, operators will need to boost the spectrum efficiencies of their RAN equipment at these FDD frequencies. In practice, this will involve investing in the latest, advanced massive MIMO radios, which offer significant spectral efficiency gains compared to conventional radios. For example, Huawei claims that its Sub-3GHz 32T32R massive MIMO radio can offer operators up to 10X more capacity, 10X more data downlink throughput, a 10dB increase in coverage and a 30% reduction in power consumption compared to a 4T4R radio.
Counterpoint Research believes that this transition to advanced massive MIMO radios must be done without substantially increasing capex and opex costs for operators, particularly power consumption. RAN operations are typically a trade-off between radio performance and power consumption. Despite their higher throughputs and superior spectrum efficiencies, massive MIMO radios can also help minimise capex and opex costs. As seen in Exhibit 1, replacing multiple single-band radios with a single multi-band radio leads to considerable site simplification and thus a lowering of tower leasing costs. In many cases, using radios with higher spectral efficiencies can also result in a reduction in the number of cell sites required and may even lower operators’ investments in new spectrum bands. In addition, by leveraging state-of-the art radio technologies, including the latest power amplifiers coupled with the latest AI-driven power saving techniques, smart algorithms, etc., massive MIMO radios can also reduce overall power consumption on a cell site basis, thus reducing opex costs for operators, while helping to minimise their carbon footprint.
Since its launch in 2019, 5G has experienced fast adoption surpassing all previous cellular generations. Yet despite this rapid adoption, operators are only beginning to monetise their 5G investments. Over the next few years, 5G Advanced will provide operators with much improved network capabilities that will enable them to offer a raft of innovative new applications as well as enhancing existing consumer and business services.
While 5G essentially provided higher data rates compared to 4G, 5G Advanced will help operators enhance existing 5G networks making them more efficient, with superior uplink and downlink performance, higher throughput and capacity coupled with lower latency and improved network reliability. 5G Advanced will also enable up to 100 billion device connections.
To a large extent, these enhancements will be enabled by the introduction of new 5G base station products such as advanced massive MIMO radios leveraging state-of-the-art multi-antenna and ultra-wideband technologies. 5G Advanced will also introduce new use cases such as passive IoT and Integrated Communications and Sensing (ICAS), two technologies with considerable potential to revolutionize mobile communications. 5G Advanced will also bring deeper integration of AI/ML across the network, including inside radios, devices and across networks, bringing significant gains in network performance as well as improving mobility and coverage.
5G Advanced Will Need More Spectrum
In many cases, operators will need access to new spectrum in order to maximise the full potential of 5G Advanced. The last World Radio Conference (WRC-23) allocated more mid-band spectrum in the 3.5GHz band while the 6GHz band was designated as a mobile band in most regions. The emergence of 6GHz band spectrum will be important as it provides operators with an option to acquire more mid-band spectrum to support higher data transfer rates and increased network capacity, thus helping them to realize new service opportunities. In Europe, much of the 6GHz range is currently used for Wi-Fi, with only a modest amount of the band set aside for cellular use. However, the agreement at WRC-23 will allow more cellular access to the upper portion of this band in Region 1 (Europe, Africa, Middle East). This means that local operators have an opportunity to work with regulators to secure a larger amount of 6GHz spectrum.
Another important band is the millimetre band. Continuously rising data consumption plus 5G Advanced’s demand for more spectrum is reviving operator interest in the millimetre wave bands. However, although more than 140 operators worldwide have acquired millimetre wave spectrum, less than 5% of them have actually deployed any networks, due mainly to the limited coverage of millimetre wave cells. A good example of a millimetre wave network deployment is that of China Unicom Beijing, which has deployed a 5G Advanced network in Beijing’s financial district. The network leverages the latest Extra Large Antenna Array (ELAA) technology with high and low frequency coordination and serves as a benchmark demonstration of the commercial capabilities of millimetre wave spectrum.
Leveraging TDD Multi-Carrier Aggregation
5G Advanced heralds the start of the Multi-Gigabit era. TDD multi-carrier aggregation combines spectrum from different TDD frequency bands and is a proven method for augmenting data throughputs in wireless networks. It allows operators to increase network capacity, providing higher downlink data rates and increased coverage thereby allowing operators to maximise their spectrum assets. TDD multi-carrier aggregation can be used across 2.6GHz, 3.5GHz, C-band, 4.9GHz as well as millimetre bands such as 26GHz and 28GHz. The choice of 3GPP-specified 5G Component Carrier (CC) configurations, for example, 2CC, 3CC, 4CC, etc., continues to expand and enables multi-Gigabit 5G data rates across a wide variety of sub-6GHz and millimetre spectrum allocations globally.
In practice, operators have two primary options at the present time: use 3CC carrier aggregation to aggregate 200MHz of sub-6GHz spectrum or use 3CC in the U6G (6,425-7,125MHz) and millimetre wave bands to aggregate larger bandwidths exceeding 400MHz. With 3CC carrier aggregation in sub-6GHz, it is possible to achieve 5Gbps downlink speeds, i.e. 5 times the capability of current 5G. For example, China Mobile has achieved 5Gbps downlink throughput using 2.6GHz (100MHz & 60MHz) and 4.9GHz (100MHz) spectrum bands. However, millimetre wave spectrum is essential to reach 10Gbps. For example, China Unicom recently achieved a throughput of 10Gbps using 3CC in C-band (100MHz) and millimetre wave (800MHz) bands.
The improved network performance due to 5G Advanced will enable operators to enhance existing services by introducing more immersive mobile broadband offerings and improve connectivity in homes, enterprises and vehicles.
Enhanced mobile broadband – 5G Advanced will enable operators to introduce smarter, more interactive experiences which benefit from low-latency connectivity. For example, New Calling services, which introduce capabilities such as voice/video calls with real-time language translation, speech-to-text translation, screen sharing, interactive visual menus and enterprise ID cards.
UAE operator Du plans to use its 5G Advanced network to accelerate the introduction of 3D Internet-type services as well as offering services such as video calls, live video streaming, games and e-shopping, all of which require high-bandwidth and stable low latency connectivity in both uplink and downlink.
Connecting Homes – FWA-based 5G Advanced provides significantly more bandwidth and reduced latency thus making it possible to offer a range of FWA services across different markets. For example, 5G RedCap CPEs can offer downlink rates of up to 150 Mbps with 50% less power consumption compared to standard 5G CPEs. With RedCap CPEs expected to be priced around $40-$60, this could enable operators to target new markets such as homes without home broadband or served by lower-speed networks.
Operators could introduce a Home Plus type service by leveraging 5G Advanced-based FWA’s high downlink/low latency characteristics and guaranteed service quality offering. This would allow them to earn incremental revenue from existing subscribers by offering new services such as 8K video streaming, large scale cloud-gaming, home security monitoring and VR sports for multiple concurrent users. SMEs could be another new market. 5G Advanced could enable operators to offer “super-uplink” type FWA services with low latencies and guaranteed uplink rates between 50Mbps to 1Gbps.
Connecting Things – 5G Advanced introduces a host of features to improve device connectivity. For example, improvements in RedCap will boost the ability of 5G-Advanced to support lower-performance and more affordable devices, which should open new business opportunities for operators, particularly in IoT. Another promising new use case is passive IoT. Next-generation passive IoT tags will have a range of over 200 metres, far exceeding that of RFID tags, and with a significantly lower cost per tag.
Connecting Enterprises and Vehicles – by leveraging its enhanced uplink characteristics, 5G Advanced will enable fully wireless-connected factories enabling flexible production, a key to digitalization in manufacturing while bringing new capabilities to vehicles, for example, route planning beyond a driver’s line-of-sight, thus making transportation safer.
Operator Deployments
China Mobile has announced that it will launch 5G Advanced in more than 300 cities in China by the end of 2024 and has already launched services in around 100 cities. Full deployment across China is expected by the end of 2026. The operator expects that around 20 million devices and terminals will be shipped by the end of 2024. Key consumer services include New Calling, VIP Gbps, Cloud Phone and glasses-free 3D.
Other operators have also announced commercial 5G Advanced plans, including Beijing Unicom, Zain KSA and Finnish operator DNA. Beijing Unicom has announced that it will deploy 5,000 5G Advanced sites and will use TDD multi-carrier aggregation to provide high-bandwidth services. Zain is developing a 5G Advanced city in Riyadh and will showcase a number of 5G Advanced services, including enhanced FWA services. The operator plans to expand its 5G Advanced coverage to another eight cities by 2026. Meanwhile in Europe, Finnish operator DNA plans to launch a 5G FWA Gbps service.
Analyst Viewpoint
The improved network capabilities enabled by 5G Advanced will enrich the mobile experience for consumers and business users alike, while providing new monetization opportunities and service options for operators. This will allow them to expand existing services and earn incremental revenues through the introduction of new speed or uplink-based tariffs and guaranteed service quality levels. As a result, Counterpoint Research believes that operators should start upgrading their networks to 5G Advanced as soon as possible to ensure they can offer the enhanced user experiences that will be expected by customers, as well as being ready for the accompanying surge in bandwidth demands.
Over the next few years, TDD multi-carrier aggregation will play a key role in the 5G Advanced network upgrade ensuring that operators can offer 5-10Gbps fibre-like downlink speeds, as well as providing improved low-latency and high-data uplink experiences – an acute problem with existing 5G. However, some technical challenges remain in relation to antennas and data processing requirements. For example, 3D or even higher-dimensional computing may be necessary to provide the required user experience. In addition, deploying large-scale commercial 5G Advanced networks will require more cell sites while multi-carrier aggregation will be more challenging if an operator’s spectrum is highly fragmented.
Clearly, the use of millimetre wave spectrum will be crucial to provide the ultimate user experience and maximise the potential of 5G Advanced for operators. However, several problems, such as overcoming high-frequency signal loss and achieving TDD uplink/downlink symmetry, need to be solved first. As a result, Counterpoint Research believes that 3CC carrier aggregation in the sub-6GHz bands will be the preferred choice by many operators as the first wave of 5G Advanced commercial networks are rolled out. However, leading infrastructure vendors are working to overcome the technical challenges associated with TDD multi-carrier aggregation and are confident that they will be able to offer competitive products in due course.
This blog was sponsored by Huawei. To learn about FDD Sub-3GHz Massive MIMO click here.
Marvell reported Q1 FY25 financial results on May 30th with total revenues of $1.16 billion, down 12% Year-on-Year (YoY) and 9% sequentially. As with the previous quarter, the standout business segment was the data centre business, with revenues up 87% YoY and 7% sequentially. However, Marvell posted a $216 million net loss, an increase of 28% YoY.
Data Centre Segment
Data centre revenue reached $814.4 million in Q1 FY25 driven by strong demand for its AI electro-optical products (PAM4 DSPs, TIAs and drivers) as well for its ZR Data Centre Interconnect (DCI) products. The double-digit revenue growth was driven by cloud AI as well as standard cloud infrastructure, which offset a higher than seasonal decline in on-premises enterprise data centre revenues.
In addition, Marvell booked revenues from initial shipments of its custom AI compute programs and announced three new data centre interconnect opportunities: PCIe Gen 6 retimers, AEC PAM4 DSPs and extended range coherent DSP-based DCI modules for use inside and outside data centres.
Optical Interconnects:
100G-lane 800G PAM4 DSPs – are the primary interconnect product for state-of-the-art AI deployments and are shipping in volumes today. Marvell announced that it has started qualifying next-generation 200G/lane 1.6T PAM4 DSP solutions, which will enable next-generation AI accelerators. Volume adoption is expected to start later this year and accelerate during CY 2025.
PCIe Gen 6 retimers – Marvell recently announced its new PCIe Gen 6 retimer product range. PCIe Gen 6 is the first PCI standard to use PAM4 DSPs and these products are designed to help data centre compute fabrics continue to scale inside AI servers. The company is currently sampling its 8-lane and 16-lane PAM4-based PCIe Gen 6 retimer products.
Active Electrical Copper (AEC) PAM4 DSPs – AI demands higher speeds, which is driving the need for active interconnects inside racks. Marvell has started shipping its AEC PAM4 DSPs and has secured design wins with multiple Tier-1 cloud customers.
DCI ZR Modules – Marvell is shipping its 400G ZR products in high volumes and is seeing strong interest in its next-generation 800G ZR/ZR+ pluggable module DCI products. During the quarter, it also demonstrated the industry’s first 3D photonics engine. Marvell’s DCI customer base is expanding with design wins at multiple new data centre customers. However, revenue contribution from the 800G ZR/ZR+ DCI products is not expected to ramp up until next year.
AI clusters today are made up of thousands of GPUs within a single building. As future LLMs increase in size, clusters are expected to comprise hundreds of thousands of GPUs and will be accommodated in multiple buildings on campuses. These buildings will need to be connected so as to look like a single data centre. Marvell recently announced a new coherent DSP for use on campuses, extending the current range from less than two kilometres to 20 kilometres.
Marvell is further expanding its DCI market opportunities by introducing another coherent DSP design based on a new technology called Probabilistic Constellation Shaping (PCS), extending the reach of pluggable DCI modules from 120 kilometres to 1,000 kilometres.
Switches:
In data centre switching, Marvell expects to start production and shipments of its next-generation 51.2T Teralynx 10 switch this summer for lead customer Nvidia.
Custom compute:
Marvell’s custom compute AI programs started to ship in Q1 FY25 with a very substantial ramp-up expected in H2 FY25 followed by a full year of high-volume shipments in FY26. At its recent AI Analyst Day, Marvell revealed that it has custom compute projects with three of the four biggest US hyperscaler operators:
Amazon – AI Trainium training accelerator (ramping up now) and AI Inferentia inference accelerator (expected CY2025 ramp)
Google – ARM Axion custom CPU (ramping up now)
Microsoft – AI Maia accelerator with expected ramp-up in CY2026
Marvell has also developed a custom silicon for chip start-up Groq’s first PetaOPs AI accelerator, a 700mm2 custom ASIC which is in volume production.
Marvell expects its custom silicon business to generate around $200 million by the end of 2024 and the company claims has strong visibility over its 5nm programs over the next two years. In addition, it claims that its 3nm design pipeline and wins have been very strong and is also already engaged on 2nm design work.
Exhibit 1 shows a breakdown of Marvell Q1 FY25 revenues by market segment.
Exhibit 1: Data Centre vs Enterprise, Carrier and Automotive Revenues
5G Infrastructure and Enterprise Networking
As predicted by the company last quarter, the weakness in the 5G infrastructure and enterprise network markets continued with revenues down at both business units:
5G Networks – revenues were $71.8 million in Q1 FY25, down 75% YoY and 58% sequentially. In the previous quarter, Marvell was expecting Q1 FY25 to be the low point with growth resuming in Q2. However, the company now expects Q2 to be flat sequentially with recovery beginning in H2 FY25 driven by the adoption of the next-generation Marvell DPUs at a Tier-1 customer, probably Nokia. Nevertheless, the company expects its 5G market share to increase as customers transition to 5nm Octeon 10 DPUs and baseband processors in H2 FY25. It claims to have won an additional socket with Nokia.
Enterprise Networks – revenue was down 58% YoY and 42% sequentially to $153 million. Although Marvell reported that customers’ excess inventory absorption is progressing, it still expects Q2 revenue to be flat sequentially with recovery starting in H2 FY25.
Automotive/Industrial
The automotive/industrial market is another market experiencing inventory correction. Reported revenues were $78 million, down 13% YoY and 6% sequentially. However, Marvell expects growth to resume in H2 FY25 driven by an increase in Marvell Ethernet content in 2025 model year vehicles.
Analyst Viewpoint
Counterpoint Research believes that Marvell is increasingly well positioned to benefit from the burgeoning growth in AI data centre infrastructure over the next few years. However, many of its new revenues streams will only start towards the end of FY25 but will set up a solid foundation for FY26.
With two hyperscaler customer wins already ramping up, most of the growth in data centre revenue will come from custom silicon over the next two to three years. Marvell had previously pencilled in around $1.5 billion for AI revenue for FY25 (split two-thirds electro-optics, one-third custom compute) – up from $500 million in FY24. However, it now expects to exceed that number and has a target of $2.5 billion in FY26 as the custom silicon programs reach the first full year of volume shipments.
Custom silicon is a business with high barriers to entry and could be very lucrative for Marvell in the medium and long-term. To succeed, vendors need to have R&D scale, technical excellence, cutting edge IP as well as being able to operate on the latest leading-edge process node – attributes which Marvell possesses. In addition, by working closely with the hyperscalers, Marvell will gain a significant advantage as it will acquire unique insights into their next-generation architectural requirements, not only for custom silicon, but also for the connectivity, switching and other products. However, Marvell competes against Broadcom – the 800-pound gorilla of the custom silicon market – and others, including Nvidia, a recent new entrant to the custom silicon market. Over time, there is also a risk that the hyperscalers will develop their own expertise and follow the examples of Apple and Huawei and bring their custom silicon design work in-house.
The other new growth market is data centre interconnects with three new opportunities – AEC interconnects, PCIe Gen 6 retimers and pluggable DCI coherent DSPs – each of which is estimated to be a $1 billion opportunity over the long term. However, in the non-data centre businesses, thinks are not looking quite as rosy, although there are high hopes that both the 5G infrastructure and the enterprise networking businesses have reached the bottom of their respective cycles. 5G capital spending still looks weak and growth might be delayed beyond Q4 FY25. In addition, Marvell is heavily exposed to one vendor, Nokia. Last year, AT&T, one of Nokia’s largest base station customers, switched to rival Ericsson. It will probably take quite some time for these two business units to return to their previous $1 billion per year run rates.
Canada’s 2023 wildfire season surpassed the country’s previous record in terms of the affected area.
Innovative technologies are being deployed to combat this rising trend of wildfires.
AI-equipped sensors have been developed to monitor critical environmental variables.
The Canadian Space Agency is developing the world’s first satellite dedicated to monitoring wildfires.
A less ‘advanced’ technology, but still very important, is practical tools like interactive dashboards and websites.
In 2023, Canada saw an ultimate high of wildfires after a decade of increasing frequency and intensity. The 2023 wildfire season had over 6,500 reported incidents that affected over 18 million hectares of land, surpassing the country’s previous record of 7.6 million hectares. Drivers for this spike were climate change and evolving environmental conditions. To combat this rising trend of wildfires, which devastate air quality and land, innovative technologies are being deployed. They can not only predict such devastating natural events but also prevent and manage them more effectively.
Technologies in development
1. Artificial Intelligence (AI) and sensor technology
Companies like SensaioTech have developed AI-equipped sensors to monitor critical environmental variables, including soil temperature, humidity and luminosity. These sensors provide real-time data, enabling more accurate predictions and quicker responses to potential wildfire threats. This real-time monitoring is a significant improvement over traditional satellite imagery, which often has a delay of several days.
Rogers Communications, in partnership with Pano AI and SpaceX, is in the process of deploying AI-powered cameras that can detect smoke up to 20 km away. Using a 5G network, the cameras provide real-time alerts to first responders to check the spread. This technology focuses more on remote locations where early detection is crucial.
2. Satellite advancements
The Canadian Space Agency is developing WildfireSat, the world’s first satellite dedicated to monitoring wildfires. Unlikely to be launched before 2029, the satellite is being programmed to provide detailed data during peak wildfire instances, which will help emergency services study the trends and triggers for fire activity to better predict and manage wildfires. This initiative aims to bridge the gap in current satellite data, which often misses critical moments of fire activity.
3. Predictive modeling
The province of British Columbia has faced the brunt of wildfire occurrences in Canada, causing it to give wildfire technologies a higher priority than other provinces.
The British Columbia Wildfire Service has been using advanced predictive modeling to forecast wildfire growth and intensity. Much like the AI sensor technology, these models consider various factors, including weather conditions and terrain, to predict the potential spread and impact of wildfires. This allows for more strategic deployment of firefighting resources and better preparation for wildfire seasons.
4. Interactive planning tools for residents
A less ‘advanced’ technology, but still very important, is practical tools like interactive dashboards and websites that provide tools and guidance to residents to prepare comprehensive emergency and evacuation plans, enhancing community resilience against wildfires.
Technology use compared to US
Compared to other countries, Canada experiences a significant number of wildfires annually, but it ranks behind countries like the US and Australia in terms of the total area burned and the number of fires. For instance, the US sees an average of 70,000 wildfires per year, burning over 2.5 million hectares, whereas Canada typically records around 7,300 wildfires, affecting about the same area. This area is considerably lower if we take into account the larger uninhabited land mass that Canada has when compared to other countries.
When it comes to technological integration, Canada is making notable progress but still lags behind some countries. The US, for example, has been quicker to adopt advanced wildfire management technologies, leveraging AI, satellite imagery and drones extensively. However, Canada is catching up with initiatives like WildfireSat and partnerships involving AI-powered detection systems. The slower integration is also due to a restraint on available resources in the more barren landscape, which makes it difficult to get these technologies to cover a larger area in remote places.
Impact of wildfires on Canada
These technological advancements are crucial as Canada faces increasingly severe wildfire seasons. Rising global temperatures and decreasing humidity levels have created conditions that foster more frequent and intense wildfires. The past decade alone has seen some of the worst wildfire seasons on record, with significant economic and environmental impacts.
While wildfires in Canada pose a growing threat, the integration of advanced technologies offers hope for better management and mitigation. From AI and satellite technology to predictive modeling and community planning tools, these innovations are essential in the ongoing battle against wildfires. As traditional wildfire management methods are becoming less dependable, embracing these new technologies will be critical in protecting communities and preserving Canada’s vast forested landscapes. Further, providing effective connectivity across Canada will aid in the quick development of these technologies. This is why we are seeing a rise in telecom player interventions over this issue, like Rogers deploying AI-powered cameras on its already existing towers to detect smoke.
The HP Envy x360 14 is powered by an Intel Core Ultra 7 155U processor with a dedicated NPU for AI tasks.
The laptop also has a dedicated Copilot button for quick access to Microsoft’s AI assistant.
The 2-in-1 laptop features a 2.8K OLED display with a 120Hz refresh rate and IMAX certification.
AI is turning into a ubiquitous phenomenon in the world of technology, especially smartphones and PCs. Intel kick-started the AI PC era with its new Meteor Lake processors in early 2024. HP, along with other PC makers, is one of the first to launch AI PC laptops powered by Intel’s Core Ultra processors. But what exactly is an AI PC and why should one care? What sets them apart from previous PC generations?
Along with the CPU and GPU, AI PCs also have a dedicated Neural Processing Unit (NPU). This NPU helps in offloading some AI tasks from the CPU and GPU, helping save battery life. Since we are still in the early stages of this technology, the definition of AI PC will keep changing as things progress. Microsoft, at Build 2024, announced its Copilot+-powered AI PCs. According to Microsoft, a PC needs at least 40 trillion operations per second (TOPS) of AI performance to qualify as an AI PC.
Based on this, we may have entry-level GenAI basic PCs to the most advanced ones with top-notch configurations.
The HP Envy X360 14 is a 2-in-1 laptop powered by an Intel Core 7 Ultra 155U processor. However, it has a Meteor Lake architecture, which is not as advanced as Intel’s upcoming Lunar Lake architecture, that can deliver up to 120 TOPS AI performance. The HP Envy with Meteor Lake processor qualifies as a basic GenAI PC and, includes AI features that enhance the overall user experience from camera to audio, battery life to display, and much more.
Commenting on the growth momentum of AI PCs, Senior Analyst William Li said, “Microsoft’s announcement at the Build 2024 developer conference reaffirmed AI PC momentum in 2024, especially in the second half. Qualcomm’s first wave of AI laptops will enter the market in the upcoming month, while Intel and AMD are preparing for their next-generation AI solutions for PCs. Intel entered the AI PC market at the beginning of the year and is already working with PC partners to deliver a variety of laptops with the Meteor Lake platform, including the HP Envy x360 14. We believe Intel will continue to dominate the PC market in terms of shipments while Windows on Arm will also be in the spotlight in H2 2024. Overall, we believe three out of four laptops sold in 2027 will be AI laptops with advanced GenAI capabilities.”
We have been testing the HP Envy x360 14 for about three weeks to explore its AI features and see how the 2-in-1 laptop, priced at around $1,550, fits in the hybrid work scenario. Below is our detailed analysis.
WATCH: HP Envy x360 14 Review
2-in-1 form factor with a look and feel that evokes envy
At the launch event, HP mentioned that the Envy x360 14 is designed for creative professionals and freelancers. The laptop features a sleek and slim form factor, weighing just 1.39kgs, making it easier to carry around. The 2-in-1 design with a 360-degree hinge also makes it easier for different use cases. It can be used in the tent mode for watching content or can be folded all the way to be used as a tablet.
On the connectivity front, you get a USB Type-A 3.1 port on the left, an HDMI out, and two USB Type-C Thunderbolt 4 ports. On the right, you get a USB Type-A 3.1 port and a 3.5mm headphone jack. Unfortunately, the laptop misses out on an SD or microSD card slot.
The chiclet keyboard keys have enough travel to offer a good typing experience. The keyboard is backlit, making it easier to work and type in the dark. The keyboard also has a dedicated emoji button among the function keys at the top. The keyboard has a dedicated Microsoft Copilot button, located beside the arrow keys, indicating that the PC also has a dedicated NPU.
Using the dedicated Copilot button, you can quickly invoke the assistant to ask questions, to generate an image or email for you. You can also ask for recipes, travel ideas and itineraries, ask to change wallpaper, turn volume/brightness levels high and low, and much more. You can even use your voice to ask these questions, but unlike Siri on Macs which gets invoked by voice, here you will have to press the mic icon before you ask a question.
Great display with touchscreen functionality and stylus support
The Envy x360 14 features a 14-inch 2.8K resolution (2880 x 1800 pixels) OLED touchscreen display. With 500 nits of peak HDR brightness, the screen supports an adaptive refresh rate of 48Hz to 120Hz, which can automatically be adjusted based on the on-screen content.
The OLED screen is IMAX-certified. It offers great viewing angles, good contrast, vibrant color reproduction and stands out particularly when watching immersive HDR content on Netflix. The touchscreen responsiveness is smooth. We did not experience any issues when scrolling through web pages, performing pinch-to-zoom gestures or playing games like Asphalt 9: Legends.
The screen also supports the HP stylus MPP2.0 Tilt Pen. The stylus is easier to hold and is just like a regular pencil in appearance. There is a small cover at the end of the stylus, sliding which reveals the Type-C charging port.
In terms of usage, the stylus has good input precision, something that creative designers will find handy. We tried sketching using MS Paint, and it worked well. The screen supports palm rejection, but the optimization could have been better.
HP Envy x360 (14-fc0100TU) specifications
Under the hood, the HP Envy x360 14 is powered by Intel’s Core Ultra 7 155U processor. Built on the Intel 4 Node (7nm fabrication), this is our first time testing a Meteor Lake SoC. The processor has 12 cores and 14 threads:
• Two performance cores (P-cores) with a base frequency of 1.7GHz and a max turbo frequency of 4.8GHz.
• Eight efficiency cores (E-cores) with a base frequency of 1.2GHz and a max turbo frequency of 3.8GHz.
• Two low-power efficiency cores (LPE-cores) with a base frequency of 700MHz and a max turbo frequency of 2.1GHz.
The processor has a base power of 15W, which can go up to 57W on turbo mode. On the graphics side, the laptop comes with Intel Graphics with four X-cores and dynamic frequency of up to 1.95GHz. The integrated graphics card supports ray tracing, and a maximum integrated resolution of 3840×2400 pixels with a 120Hz refresh rate.
One factor that differentiates Intel’s Meteor Lake disaggregated SoC architecture from its predecessors is the NPU. Intel has included the Intel AI Boost NPU with a max frequency of up to 1.4GHz. It supports AI software frameworks like OpenVINO, which we will talk about in detail in a bit.
Other specifications include 32GB of LPDDR5 RAM (onboard) and 1TB of PCIe Gen 4 NVMe SSD. Wireless connectivity options include Wi-Fi 6E and Bluetooth 5.3. The laptop comes with a 3-cell, 59Wh battery and a 65W Type-C charging adapter, which can charge the laptop from empty to 50% in about 30 minutes, and a full charge in roughly one hour 30 minutes.
The processor is also Intel Evo-certified, meaning it can offer a battery life of over nine hours, charges over a Type-C port, wakes up from sleep in less than a second, and includes Thunderbolt 4 and Wi-Fi 6E connectivity options.
Dedicated NPU, unlocking new AI PC experiences
We have been hearing and talking a lot about AI PCs, but what are some of their use cases, and how are they different from traditional PCs? Well, the HP Envy x360 14 is loaded with AI features, which we experienced while using the laptop.
Microsoft’s Windows 11 OS, which the laptop runs on, has Windows Studio Effects. This feature allows the user to access various effects on the laptop’s 5MP IR camera such as auto-framing, eye contact, and background effects. The workload of these AI effects is entirely on the NPU (rather than on CPU/GPU), which also helps in conserving battery life. The auto-framing uses AI to detect your face in the frame and keep you in focus.
The eye contact feature ensures that your eyes are looking into the camera, even if you are looking elsewhere, say into your phone. Lastly, the background effects separate the subject from the background while adding blur effects.
The AI also filters unwanted background noise when on voice or video calls. This will be highly beneficial for people who work in hybrid environments, be it offices, café, airports and more. The speakers, tuned by Poly Studio, are good enough for casual media consumption and video calls. The AI does all this work in the background to optimize the laptop’s battery life.
HP has also included a Presence Detection feature which uses the IR sensor and AI to detect when you are around (max distance four feet) and looking into the laptop. Once you look away from the screen for a few seconds, the screen brightness is reduced. It increases again after you start looking at the screen. When you walk away from the screen (for over two minutes), the laptop automatically gets locked. The AI automatically unlocks the laptop when you get back and Windows Hello authenticates your face. However, one thing to note is that to awaken the laptop a few minutes after it goes into sleep mode, you will have to press the power button.
Testing Intel’s OpenVINO AI models
To spread AI everywhere, Intel recently announced over 500 AI models optimized for Core Ultra processors, unlocking new experiences. We tried a couple of these OpenVINO AI effects on the popular open-source audio editing app, Audacity, and the open-source photo editing app, GIMP.
Audacity OpenVINO AI Effects
On the Audacity app, there are four key AI features – music separation, music suppression, music generation, and transcription. All these AI features work on-device and do not need an internet connection. Music separation is great for musicians as it allows editors to separate the vocals, drums and other instruments, and then remix the song. We tried it with a couple of songs, like Hotel California by Eagles, and it worked pretty well.
Music suppression is good for podcasters as it greatly helps to reduce the background noise, like fan noise, AC hum, and wind noise. Using music suppression, we recorded an audio clip with background noise, and the results were impressive.
With the music generation GenAI feature, you can generate original music based on a prompt. While it worked well, the prompt needs to be detailed to get the desired results. You get an option to use NPU as well, and you can see most of the load taken by the NPU, while keeping the CPU and GPU free. In our test, it took two minutes and 11 seconds to generate a track using the NPU.
Lastly, we also tested the audio transcription feature which uses the Whisper model to transcribe audio to text. For a 28-minute podcast audio file, it took around three minutes and 40 seconds to transcribe with decent output.
GIMP OpenVINO AI Effects
We used GIMP for two tasks – text-to-image generation using Stable Diffusion 1.4. The output was decent, and it took around 35 seconds to generate an image using the text.
It also supports semantic segmentation fully using the NPU, which took about seven seconds to separate the background from the subject. The edge detection was not that good, but since these key tasks are handled by the NPU, it unburdens the processor.
(Do note, that installation is not a straightforward process. There is no direct installer, and you will need to download resources from GitHub, install Python, and install the requisites using Command Prompt.)
Filmora AI Effects
Intel and Wondershare have partnered to optimize the processor for the popular video editing app, Filmora. The AI effects allow you to separate the subject (foreground) from the video and add background blur. You can also replace the background while keeping the person in the foreground.
There are other AI effects too, like noise cancellation, video effects like flares, neon lights, and more. All these AI effects make use of the NPU with Intel AI Boost, while also sharing resources with the CPU and GPU. In our test, adding some of these effects to a one-minute video and rendering took about six minutes, which is not bad.
LM Studio
Lastly, we downloaded LM Studio, an app that lets you download small language models (SLMs) and large language models (LLMs), such as Meta’s Llama3, Microsoft’s Phi-3 and Google’s Gemini, to run these AI chatbot models locally. We asked a bunch of questions like the best places for burgers, or top tourist places in different cities, and it offered good results. However, the token generation time taken for the final output was slow as the workload was taken by the GPU. There were no options to shift the workload to CPU or NPU.
Good performance, even better battery life
The Envy x360 is powered by the very competent Intel Core Ultra 7 155U processor and offers reliable performance for a wide range of day-to-day tasks. This includes web browsing, audio/video calls on platforms like Teams and Zoom, checking and responding to emails on Outlook app, and using apps like Word and PowerPoint.
Sure, the 155U is not as powerful as the Core Ultra 7 155H, but it does offer a good balance between performance and efficiency. We were pleasantly surprised by the steady frame rates when playing casual games like Left4Dead2 (hitting even 130fps at times), Rocket League (hitting around 40fps), and Counter-Strike 2 (hitting about 30fps). This is despite not having a discrete graphics card, or the latest Intel Arc graphics solution (as on 155H).
HP has also included the OMEN Gaming Hub, a customization tool for all your games to ensure better all-round gaming performance.
In terms of battery life, we got a little over seven hours of backup with usage that included writing blogs, web browsing and a few audio calls on Teams. With slightly heavy usage, including editing a couple of video reels and watching videos, we still managed to get around five hours of backup. With casual gaming, the laptop still managed close to two hours of backup. (Do note, throughout our heavy usage like gaming, video editing and testing AI tasks, the battery performance settings were set to high mode.)
Final thoughts
The HP Envy x360 14 is a compelling option for users who are looking for a powerful and versatile 2-in-1 laptop. With Intel’s latest Core Ultra 7 processor at the helm, along with a dedicated NPU, it offers innovative AI features thoughtfully designed for everyday use cases. From enhanced video conferencing experiences to handy features like presence detection and a dedicated Copilot button, NPU unlocks a new level of user experience.
All this paired with a great OLED display, good keyboard and long battery life positions the Envy x360 14 as a well-rounded AI PC for professionals, creators and casual users alike.
Apple has unveiled a well-rounded strategy to bring Generative AI capabilities to its ecosystem.
Given the high level of external focus on its AI plans, Apple strategically placed AI at the end of its WWDC24 keynote, branding it ‘Apple Intelligence’, a clever move to gain a greater mind share to start with.
The fact that Apple is positioning it as a capable personalized experience that is based on great architecture, the name Apple intelligence is likely to resonate with users a lot going forward.
The initial use cases announced range from new features for writing, focusing and communication to image creation.
The era of artificial intelligence (or ‘Apple Intelligence’ as the company would like to describe it) beckons Apple users. At its WWDC24 event on Monday, the company unveiled a well-rounded strategy to bring Generative AI capabilities to its ecosystem. Given the high level of external focus on its AI plans, Apple strategically placed AI at the end of its keynote, branding it ‘Apple Intelligence’, a clever move to gain a greater mind share to start with. The fact that Apple is positioning it as a capable personalized experience that is based on great architecture, the name Apple intelligence is likely to resonate with users a lot going forward.
Image Source: Apple
Unlike Google, Apple avoided creating an overly grandiose narrative for AI. Instead, it focused on specific, practical applications. A consumer-friendly approach will truly encourage the mass adoption of AI on its devices. Therefore, Apple has taken a holistic and highly integrated approach to bringing GenAI experiences to its ecosystem.
The initial use cases announced range from new features for writing, focusing and communication to image creation. Apple orchestrated hundreds of actions for end users that make the device experience more personalized. We believe it is an elegant weaving of ‘typical’ AI features like text summary, image creation and contextual info retrieval.
WATCH: Will Apple Intelligence Drive Ecosystem-wide “Super Cycle” for Apple?
Key AI features:
Summarize text
Create original images
Retrieve relevant data when needed
Siri-ChatGPT free access
Transcribe phone calls and voice memos
Solve advanced math equations
Sort through emails
Prioritize notifications
Image Source: Apple
In Siri 2.0, Siri becomes more useful in communicating in a natural conversational and contextual language, the capability being built on top of the App Intent framework, now powered by LLMs. This allows Siri to be more intelligent and take new actions across the apps. Future scenarios for how GenAI, and AImore broadly, can deliver real value to consumers often focus on the evolving role of digital assistants based on software agents.
Despite collaborating with OpenAI, Apple ensured that its capabilities were not overshadowed. For instance, Siri asks for user consent, thus maintaining the strength of its own AI.
At the foundation is Apple Silicon, one of the most powerful and advanced computes available in the market, with the capability to unlock those advanced AI features natively on Apple hardware. Apple also shared the list of devices compatible with Apple Intelligence, starting with the iPhone 15 Pro series in iPhones and iPads.
Image Source: Apple
Built on this are Apple’s ‘Foundation models and Adapters’ trained with underlying privacy-focused “Responsible AI” principles. Adapters are the small neural network modules that fine-tune the models for specific tasks.
Image Source: Apple
Layered on the FM is the ‘App intents’ framework, which is the linchpin here in Apple‘s overall AI strategy. The framework exposes the AI capabilities and drives deeper integration into Apple’s prized application ecosystem. This is the holy grail of Apple’s AI strategy.
OpenAI-ChatGPT-4o partnership adds an extra layer of intelligence for complex queries with universal data across apps.
We believe users and developers will trust Apple’s “privacy-led” narrative both at the edge and in the cloud (Apple’s Private Cloud Compute) to “opt in” with their data to boost the Apple Intelligence strategy.
While it is free for now, at some point Apple will either raise the hardware prices or go with the “hardware-as-a-service” model and start charging for AI.
It can also be a double-sided business model where developers can also earn some (if Apple is generous enough) incentive to integrate App Intents.
Overall, Counterpoint believes that Apple will have more than 250 million fully Apple Intelligence-capable devices by the end of 2025 for developers, Apple and users to start enjoying the scale of Apple Intelligence.
WWDC 2024 – OS Updates
iOS 18 overshadowed, not overlooked
iOS 18 is about customization, productivity and communication. Updates include:
Upgraded home screen, control center
Upgraded messaging:
Finally supporting RCS – green bubbles remain
iOS-Android messaging to support higher-quality images, videos, read receipts, E2E encryption
Scheduling
New text effects
Enhanced Face ID capabilities
Image Source: Apple
iPadOS 18: Redesigned App Experiences
iPadOS 18 brings redesigned experiences across apps, unlocking more capabilities for Apple Pencil.
Customized control center, home screen and an updated photo app from iOS18 coming to iPadOS18 as well.
A floating tab bar makes it easier to navigate between different parts of the app.
Apple brings a native calculator app for iPad.
Math notes and smart script unlock the capabilities of Apple Pencil, leveraging powerful on-device machine learning capabilities.
Messages in iPadOS18 get an update in the form of text formatting, redesigned Tapbacks and the ability to schedule messages at a later time.
Image Source: Apple
macOS Sequoia: Focus on Continuity and Productivity
iPhone Mirroring makes Continuity “More Magical”
Interact with and control iPhone directly from Mac
Safari becomes more productive
‘Highlights’ automatically detects relevant information
from a webpage by using machine learning
Distraction-free video experience
Unified gaming platform
Easier to bring Mac games to iPad and iOS using
Game Porting Toolkit 2
More game titles
Presenter preview and backgrounds for video calls
Image Source: Apple
watchOS18 – Fitness Remains Central to Watch Experience
watchOS18 gets an update on fitness and deeper personalization
Vitals app helps users make more informed decisions about their health on a day-to-day basis.
Watch becomes more personalized with an update to the fitness app, activity rings and Photos watch face.
More intelligent Smart Stack, new widgets, and even suggestions for widgets. The double-tap gesture can now be used to scroll through any app.
Translate app comes to the watch with 20 supported languages.
New APIs for developers to take advantage of the capabilities of Smart Stack and double-tap gesture.
Image Source: Apple
Vision Pro Expands to New Geographies; visionOS2 Uninspiring, but a Step Forward
Apple Vision Pro, exclusively available in the US since February, will now be launched in nine new markets.
visionOS 2 was also previewed with some interesting features:
Can create spatial photos from existing libraries
Navigate using new hand gestures
Watch videos in environments
Developers will have access to new APIs and frameworks to create more immersive experiences
Overall, we believe the WWDC 24 lived up to its expectations and Apple made it look very smooth. But, like watching a duck on the water, we suspect there is a lot of frantic paddling going on inside. At the same time, Apple is best positioned to make AI and GenAI work well for consumers thanks to its Hardware-as-a-Service business model.
eSIM technology is seeing rapid growth. It is being adopted by OEMs in premium smartphones, smartwatches, and tablets, freeing up space for sleeker designs. In our previous podcasts, we spoke about the global eSIM market, innovative business models from various companies, eSIM testing, interoperability, and much more.
In this latest episode of ‘The Counterpoint Podcast’, we look at eSIM opportunities in India, one of the fastest-growing markets in the world. Host Mohit Agrawal is joined by two Kigen officials – VP of Marketing Bee-Hayes Thakore and Regional VP Solutions Mayank Sharma. Kigen is among the companies named as leaders in Counterpoint’s latest eSIM rankings. It is a fast-growing company, renowned across the industry for its eSIM enablement. Kigen also pioneered iSIM technology.
• Over 400 operators globally offer eSIM, and the market is expected to grow 3-4x by 2027.
• With increasing use cases beyond smartphones and automotive (including wearables, smart meters, logistics and telematics), eSIM adoption is on a positive trajectory.
• Customer premises equipment (CPE) supporting fixed wireless access (FWA) is also driving eSIM adoption.
Initiatives in India:
• Kigen has established a fully GSMA-certified SAS-UP data center in India’s Noida for local eSIM manufacturing and procurement.
• Kigen is actively collaborating with Indian manufacturers to leverage eSIM technology.
• It is supporting the government’s ‘Make in India’ initiative by making it possible for local manufacturers to compete globally.
• Kigen is working to make the adoption process simpler for manufacturers by supporting different types of devices.
• It is also streamlining the provisioning process.
• Factory profile provisioning enables manufacturers to select the operator connectivity in the later stages of the production cycle, thus increasing flexibility.
Key challenges:
• Educating consumers about the benefits of eSIM technology is one of the biggest challenges.
• Ensuring the affordability and long-term viability of eSIM-enabled devices for complex devices like smart meters is another challenge.
• There is also a need for shared business models and partnerships to make devices and technology affordable.
• Managing multiple operator profiles while also ensuring compatibility across different regions and circles can be challenging for device makers.
Opportunities:
• In terms of opportunities, secure eSIM technology in infrastructure projects, and smart meters can be beneficial.
• eSIM can offer a secure way to connect devices for banking and mobile payments using companion devices.
• Growth in companion devices can benefit greatly from eSIM technology.
Analyst takeaways
• Kigen is looking at telematics and fixed wireless access (FWA) as the key growth areas for eSIM. FWA is a force multiplier as it enables connectivity in areas that are not covered by fiber. Connectivity, in turn, spurs demand for other consumer and enterprise devices such as point-of-sale (POS) terminals.
• Kigen has made significant investments in India as it views it as a focus market. It has established a SAS-UP certified manufacturing facility in India. India is the fastest-growing IoT market and an early commitment from Kigen will go a long way in establishing it within the Indian manufacturing ecosystem.
• Smart meters represent the biggest cellular IoT opportunity at the moment and for the next few years. India will see over 200 million smart meters installed over the next 4-5 years, offering a big opportunity for Kigen and other players in the ecosystem.
Podcast chapter markers:
1:20 – Mayank and Bee introduce themselves.
4:28 – Bee talks about the global adoption of eSIM.
8:37 – Mayank talks about how eSIM helps Indian operators.
10:23 – Bee talks about how eSIM benefits consumers.
12:45 – Bee sheds light on the impact of eSIM on digital consumption.
15:21 – Mayank highlights some of Kigen’s initiatives in India.
16:26 – Bee talks about the challenges and opportunities in the Indian market.
20:40 – Mayank on how Kigen supports various devices across consumer and enterprise domains.
22:42 – Mayank on how to embed connectivity in factory profile provisioning.
24:59 – Bee and Mayank’s closing remarks on expectations for 2024.
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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.
