On August 27, AI server giant Supermicro was accused of accounting violations, inadequate disclosure of related party transactions, and evading sanctions by selling products to Russia by short-seller Hindenburg Research.

In addition, Supermicro announced on August 28 that it would delay the release of its annual report, potentially facing order withdrawals. Industry sources also believe this news presents a chance for Supermicro’s competitor Dell to gain market share.

Besides Dell, a report from Commercial Times also points out that Hewlett Packard Enterprise (HPE) could benefit from the shift in orders, potentially boosting shipments for its Taiwanese supply chain partners such as Wistron, Inventec, Quanta, and Foxconn.

The report from Commercial Times also cite sources, suggesting that this shift could provide Gigabyte, which is actively promoting its liquid-cooled products for NVIDIA’s H200 series, with  opportunities in the second half of the year.

Wistron, as a key supplier of motherboard and GPU accelerator cards for NVIDIA’s Hopper and Blackwell GPU, is not only a major supplier for Supermicro’s server motherboards but also for Dell. Its clients include HPE and Lenovo as well, which makes the company one of the primary beneficiaries.

Similarly, Inventec, one of the server motherboard suppliers, is also expected to benefit if the shift in orders boosts Dell, HPE, and Lenovo.

Moreover, one of Supermicro’s largest clients, CoreWeave, is transitioning to become a cloud computing service provider specializing in GPU-accelerated computing.

This shift has increased demand for GPU-accelerated computing and liquid cooling solutions. Reportedly, it’s believed that Gigabyte, which holds orders from CoreWeave, could be one of the biggest beneficiaries of the upcoming order shift.

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(Photo credit: Supermicro)

In late March, NVIDIA CEO Jensen Huang personally delivered the first high-end DGX H200 AI server to customer OpenAI. According to a report from Commercial Times, following this, the upstream chips for the H200 AI-GPU entered mass production in late Q2, with large-scale deliveries expected from Q3 onwards.

Downstream companies, including Inventec, Quanta (QCT), Hewlett Packard Enterprise (HPE), Supermicro, and Lenovo, have reportedly listed the H200 products as ready for shipment, with deliveries anticipated to begin in the second half of the year.

The same report, citing sources, indicates that current pending orders are still largely focused on the H100 in the HGX architecture, with the H200’s share remaining limited. The H200 shipments expected in Q3 will primarily be NVIDIA’s DGX H200. As for the B100, there is already some visibility, with shipments expected in the first half of next year.

Despite the CoWoS production capacity catching up and a significant easing in the supply of AI GPUs, due to the allocation system, the delivery time for the main H100 GPU shipments from various end-system partners can still reach up to 20 weeks.

However, major Taiwanese manufacturers such as Quanta, Inventec, Wistron, Gigabyte, and ASUS have seen a substantial boost in their overall server operations, driven by AI server business in the first half of the year. They are reportedly optimistic about AI server shipments in the second half of the year, expecting strong demand to continue, making the server business effectively free from any off-season throughout the year.

Among them, Wistron holds a significant advantage in the production and supply of H100 series substrates and the subsequent B100 series GPU modules and substrates. Starting from the second quarter, Wistron’s AI server-related business has shown high visibility, providing strong support for its overall operations.

On the other hand, the H20 series, an AI chip tailored for China due to U.S. chip restrictions, has also seen demand in the Chinese market. As NVIDIA recently secured a rush order for the H20 series, Taiwanese companies, including Wistron and Inventec, are expected to benefit.

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(Photo credit: NVIDIA)

In the dynamic wave of generative AI, AI PCs emerge as a focal point in the industry’s development. Technological upgrades across the industry chain and the distinctive features of on-device AI, such as security, low latency, and high reliability, drive their rapid evolution. AI PCs are poised to become a mainstream category within the PC market, converging with the PC replacement trend, reported by Jiwei.

On-Device AI, driven by technologies like lightweighting language large models (LLMs), signifies the next stage in AI development. PC makers aim to propel innovative upgrades in AI PC products by seamlessly integrating resources both upstream and downstream. The pivotal upgrade lies in the chip, with challenges in hardware-software coordination, data storage, and application development being inevitable. Nevertheless, AI PCs are on track to evolve at an unprecedented pace, transforming into a “hybrid” encompassing terminals, edge computing, and cloud technology.

Is AI PC Industry Savior?

In the face of consecutive quarters of global PC shipment decline, signs of a gradual easing in the downward trend are emerging. The industry cautiously anticipates a potential recovery, considering challenges such as structural demand cooling and supply imbalances.

Traditionally viewed as a mature industry grappling with long-term growth challenges, the PC industry is witnessing a shift due to the evolution of generative AI technology and the extension of the cloud to the edge. This combination of AI technology with terminal devices like PCs is seen as a trendsetter, with the ascent of AI PCs considered an “industry savior” that could open new avenues for growth in the PC market.

Yuanqing Yang, Chairman and CEO of Lenovo, elaborates on the stimulation of iterative computation and upgrades in AI-enabled terminals by AIGC. Recognizing the desire to enjoy the benefits of AIGC while safeguarding privacy, personal devices or home servers are deemed the safest. Lenovo is poised to invest approximately 7 billion RMB in the AI field over the next three years.

Analysis from Orient Securities, also known as DFZQ, reveals that the surge in consumer demand from the second half of 2020 to 2021 is expected to trigger a substantial PC replacement cycle from the second half of 2024 to 2025, initiating a new wave of PC upgrades.

Undoubtedly, AI PCs are set to usher in a transformative wave and accelerate development against the backdrop of the PC replacement trend. Guotai Junan Securities said that AI PCs feature processors with enhanced computing capabilities and incorporating multi-modal algorithms. This integration is anticipated to fundamentally reshape the PC experience, positioning AI PCs as a hybrid terminals, edge computing, and cloud technology to meet the new demands of generative AI workloads.

PC Ecosystem Players Strategically Positioning for Dominance

The AI PC field is experiencing vibrant development, with major PC ecosystem companies actively entering the scene. Companies such as Lenovo, Intel, Qualcomm, and Microsoft have introduced corresponding innovative initiatives. Lenovo showcased the industry’s first AI PC at the 2023 TechConnect World Innovation, Intel launched the AI PC Acceleration Program at its Innovation 2023, and Qualcomm introduced the Snapdragon X Elite processor specifically designed for AI at the Snapdragon Summit. Meanwhile, Microsoft is accelerating the optimization of office software, integrating Bing and ChatGPT into the Windows.

While current promotions of AI PC products may exceed actual user experiences, terminals displayed by Lenovo, Intel’s AI PC acceleration program, and the collaboration ecosystem deeply integrated with numerous independent software vendors (ISVs) indicate that the upgrade of on-device AI offers incomparable advantages compared to the cloud. This includes integrating the work habits of individual users, providing a personalized and differentiated user experience.

Ablikim Ablimiti, Vice President of Lenovo, highlighted five core features of AI PCs: possessing personal large models, natural language interaction, intelligent hybrid computing, open ecosystems, and ensuring real privacy and security. He stated that the encounter of AI large models with PCs is naturally harmonious, and terminal makers are leading this innovation by integrating upstream and downstream resources to provide a complete intelligent service for AI PCs.

In terms of chips, Intel Core Ultra is considered a significant processor architecture change in 40 years. It adopts the advanced Meteor Lake architecture, fully integrating chipset functions into the processor, incorporating NPU into the PC processor for the first time, and also integrating the dazzling series core graphics card. This signifies a significant milestone in the practical commercial application of AI PCs.

TrendForce: AI PC Demand to Expand from High-End Enterprises           

TrendForce believes that due to the high costs of upgrading both software and hardware associated with AI PCs, early development will be focused on high-end business users and content creators. This group has a strong demand for leveraging AI processing capabilities to improve productivity efficiency and can also benefit immediately from related applications, making them the primary users of the first generation. The emergence of AI PCs is not expected to necessarily stimulate additional PC purchase demand. Instead, most upgrades to AI PC devices will occur naturally as part of the business equipment replacement cycle projected for 2024.

(Image: Qualcomm)

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• [News] AI PCs and Smartphones on the Rise as Generative AI Expands to the Edge

The fusion of AIGC with end-user devices is highlighting the importance of personalized user experiences, cost efficiency, and faster response times in generative AI applications. Major companies like Lenovo and Xiaomi are ramping up their efforts in the development of edge AI, extending the generative AI wave from the cloud to the edge and end-user devices.

On October 24th, Lenovo hosted its 9th Lenovo Tech World 2023, announcing deepening collaborations with companies like Microsoft, NVIDIA, Intel, AMD, and Qualcomm in the areas of smart devices, infrastructure, and solutions. At the event, Lenovo also unveiled its first AI-powered PC. This compact AI model, designed for end-user applications, offers features such as photo editing, intelligent video editing, document editing, and auto task-solving based on user thought patterns. 

Smartphone manufacturers are also significantly extending their efforts into edge AI. Xiaomi recently announced their first use of Qualcomm Snapdragon 8 Gen 3, significantly enhancing their ability to handle LLMs at the end-user level. Xiaomi has also embedded AI LLMs into their HyperOS system to enhance user experiences.

During the 2023 vivo Developer Conference on November 1st, vivo introduced their self-developed Blue Heart model, offering five products with parameters ranging from billions to trillions, covering various core scenarios. Major smartphone manufacturers like Huawei, OPPO, and Honor are also actively engaged in developing LLMs.

Speeding up Practical Use of AI Models in Business

While integrating AI models into end-user devices enhances user experiences and boosts the consumer electronics market, it is equally significant for advancing the practical use of AI models. As reported by Jiwei, Jian Luan, the head of the AI Lab Big Model Team from Xiaomi, explains that large AI models have gain attention because they effectively drive the production of large-scale informational content. This is made possible through users’ extensive data, tasks, and parameter of AI model training. The next step in achieving lightweight models, to ensure effective operation on end-user devices, will be the main focus of industry development.

In fact, generative AI’s combination with smart terminal has several advantages:

1. Personal data will not be uploaded to the cloud, reducing privacy and data security risks.
2. AI models can connect to end-user databases and personal information, potentially transforming general AI LLMs into personalized small models, offering personalized services to individual users.
3. By compressing AI LLMs and optimizing end-user hardware and software, edge AI can reduce operating costs, enhance response times, and increase service efficiency.

Users often used to complain about the lack of intelligence in AI devices, stating that AI systems would reset to a blank state after each interaction. This is a common issue with cloud-based LLMs. Handling such concerns at the end-user device level can simplify the process.

In other words, the expansion of generative AI from the cloud to the edge integrates AI technology with hardware devices like PCs and smartphones. This is becoming a major trend in the commercial application and development of large AI models. It has the potential to enhance or resolve challenges in AI development related to personalization, security and privacy risks, high computing costs, subpar performance, and limited interactivity, thereby accelerating the commercial use of AI models.

Integrated Chips for End-User Devices: CPU+GPU+NPU

The lightweight transformation and localization of AI LLMs rely on advancements in chip technology. Leading manufacturers like Qualcomm, Intel, NVIDIA, AMD, and others have been introducing products in this direction. Qualcomm’s Snapdragon X Elite, the first processor in the Snapdragon X series designed for PCs, integrates a dedicated Neural Processing Unit (NPU) capable of supporting large-scale language models with billions of parameters.

The Snapdragon 8 Gen 3 platform supports over 20 AI LLMs from companies like Microsoft, Meta, OpenAI, Baidu, and others. Intel’s latest Meteor Lake processor integrates an NPU in PC processors for the first time, combining NPU with the processor’s AI capabilities to improve the efficiency of AI functions in PCs. NVIDIA and AMD also plan to launch PC chips based on Arm architecture in 2025 to enter the edge AI market.

Kedar Kondap, Senior Vice President and General Manager of Compute and Gaming Business at Qualcomm, emphasizes the advantages of LLM localization. He envisions highly intelligent PCs that actively understand user thoughts, provide privacy protection, and offer immediate responses. He highlights that addressing these needs at the end-user level provides several advantages compared to solving them in the cloud, such as simplifying complex processes and offering enhanced user experiences.

To meet the increased demand for AI computing when extending LLMs from the cloud to the edge and end-user devices, the integration of CPU+GPU+NPU is expected to be the future of processor development. This underscores the significance of Chiplet technology.

Feng Wu, Chief Engineer of Signal Integrity and Power Integrity at Sanechips/ZTE, explains that by employing Die to Die and Fabric interconnects, it is possible to densely and efficiently connect more computing units, achieving large-scale chip-level hyperscale computing.

Additionally, by connecting the CPU, GPU, and NPU at high speeds in the same system, chip-level heterogeneity enhances data transfer rates, reduces data access power, increases data processing speed, and lowers storage access power to meet the parameter requirements of LLMs.

(Image: Qualcomm)

At Global Tech World Event on October 24th, Lenovo Group’s Chairman and CEO, Yuanqing Yang, has presented AI-powered PCs and enterprise-level “AI Twins”(AI assistant) to a global audience, heralding a new dawn for personal computers. He revealed that AI PCs are slated to hit the market no sooner than September of the following year.

Yang said that the journey of AI PCs involves a maturation process. Historically, they start with a 10% market share but are destined to become the norm, envisioning a future where every computer is an AI PC.

Regarding foundation models, Yang pointed out that some companies are hastily jumping on the bandwagon. However, he emphasized Lenovo’s commitment to not rush into trends and noted the drawbacks and vulnerabilities in China’s existing public foundation models, including concerns about personal privacy and data security. Lenovo’s focus is on establishing hybrid foundation models.

Given the need to compress models for device deployment, Lenovo is currently concentrating on research related to domain-adaptive model fine-tuning, lightweight model compression, and privacy protection techniques.

Moreover, Yang highlighted Lenovo’s prior announcement of a US$1 billion investment in the AI Innovation over the next three years. However, he clarified that this amount falls short of the financial demands since virtually all of Lenovo’s business domains involve AI and fundamental services, requiring substantial financial backing.

Lenovo’s Q1 earnings report from mid-August had unveiled the company’s plan to allocate an additional $1 billion over the next three years for expediting AI technology and applications. This encompasses the development of AI devices, AI infrastructure, and the integration of generative AI technologies like AIGC into industry vertical solutions.

Besides, chip manufacturers like Intel is joining forces to expedite the development of the AI PC ecosystem. Their objective is to realize AI applications on over 100 million personal computers by 2025. This endeavor has piqued the interest of well-known international brands like Acer, Asus, HP, and Dell, all of which have a positive outlook on the potential of AI-powered PCs. It is anticipated that AI PCs will be a pivotal factor in revitalizing the PC industry’s annual growth by 2024.

Currently, there are no brands selling AI PCs in the true sense, but leading manufacturers have already revealed their plans for related products. The industry anticipates a substantial release of AI PCs in 2024.

(Image: Lenovo)