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)

According to Bloomberg, Apple is quietly catching up with its competitors in the AI field. Observing Apple’s layout for the AI field, in addition to acquiring AI-related companies to gain relevant technology quickly, Apple is now developing its large language model (LLM).

TrendForce’s insights:

1. Apple’s Low-Profile Approach to AI: Seizing the Next Growth Opportunity

As the smartphone market matures, brands are not only focusing on hardware upgrades, particularly in camera modules, to stimulate device replacements, but they are also observing the emergence of numerous brands keen on introducing new AI functionalities in smartphones. This move is aimed at reigniting the growth potential of smartphones. Some Chinese brands have achieved notable progress in the AI field, especially in large language models.

For instance, Xiaomi introduced its large language model MiLM-6B, ranking tenth in the C-Eval list (a comprehensive evaluation benchmark for Chinese language models developed in collaboration with Tsinghua University, Shanghai Jiao Tong University, and the University of Edinburgh) and topping the list in its category in terms of parameters. Meanwhile, Vivo has launched the large model VivoLM, with its VivoLM-7B model securing the second position on the C-Eval ranking.

As for Apple, while it may appear to be in a mostly observatory role as other Silicon Valley companies like OpenAI release ChatGPT, and Google and Microsoft introduce AI versions of search engines, the reality is that since 2018, Apple has quietly acquired over 20 companies related to AI technology from the market. Apple’s approach is characterized by its extreme discretion, with only a few of these transactions publicly disclosing their final acquisition prices.

On another front, Apple has been discreetly developing its own large language model called Ajax. It commits daily expenditures of millions of dollars for training this model with the aim of making its performance even more robust compared to OpenAI’s ChatGPT 3.5 and Meta’s LLaMA.

2. Apple’s Advantage in Developing a Paid Subscription Model for Large Language Models Compared to Other Brands

Analyzing the current most common usage scenarios for smartphones among general consumers, these typically revolve around activities like taking photos, communication, and information retrieval. While there is potential to enhance user experiences with AI in some functionalities, these usage scenarios currently do not fall under the category of “essential AI features.”

However, if a killer application involving large language models were to emerge on smartphones in the future, Apple is poised to have an exclusive advantage in establishing such a service as a subscription-based model. This advantage is due to recent shifts in Apple’s revenue composition, notably the increasing contribution of “Service” revenue.

In August 2023, Apple CEO Tim Cook highlighted in Apple’s third-quarter financial report that Apple’s subscription services, which include Apple Arcade, Apple Music, iCloud, AppleCare, and others, had achieved record-breaking revenue and amassed over 1 billion paying subscribers.

In other words, compared to other smartphone brands, Apple is better positioned to monetize a large language model service through subscription due to its already substantial base of paying subscription users. Other smartphone brands may find it challenging to gain consumer favor for a paid subscription service involving large language models, as they lack a similarly extensive base of subscription users.

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