AMD Archives | Small Island Research Notes

In the Age of AI Inference, a Narrative Shift Is Taking Shape

Jane2026-02-02T12:20:29+08:00January 29th, 2026|Categories: Featured Notes, Global Business Dynamics, Strategic Tech and Market Signals|Tags: AI Hardware and Chips, AI Strategy and Ecosystem, AMD, Market Sentiment and Reflexivity, Narrative and Trust, NVIDIA, Platform and Business Model|

Executive Summary The rapid growth of generative AI has led the market, over the past two years, to focus on memory supply and storage capacity. As AI systems move decisively into an inference-driven phase, however, the fundamental bottlenecks facing infrastructure are beginning to shift. In inference environments, system costs are no longer determined primarily by model size or total data volume. Instead, they are shaped by how contextual states persist during computation. When large volumes

The Collective Belief Experiment Behind the OpenAI Boom

Jane2025-11-06T16:52:57+08:00November 6th, 2025|Categories: Global Business Dynamics, Strategic Tech and Market Signals|Tags: AI Hardware and Chips, AI Strategy and Ecosystem, Amazon and AWS, AMD, Broadcom, CoreWeave, Market Sentiment and Reflexivity, Microsoft, Narrative and Trust, NVIDIA, OpenAI, Oracle, Platform and Business Model, Supply Chain and Manufacturing|

Executive Summary Each collaboration OpenAI undertakes is more than a business transaction. It has become a focal point for global capital and industrial belief. Although the company has yet to establish a stable business model, it has already reshaped the rhythm of the global technology supply chain. This article argues that OpenAI is transforming industrial reality through reflexivity. Corporations and investors believe it can define the future, and that very belief is actively shaping the

Why OpenAI Is Choosing Complexity: The Governance Bet Behind Its Multi-Architecture Strategy

Jane2025-10-14T16:04:26+08:00October 14th, 2025|Categories: Featured Notes, Global Business Dynamics, Strategic Tech and Market Signals|Tags: AI Hardware and Chips, AI Strategy and Ecosystem, AMD, Broadcom, Market Sentiment and Reflexivity, Microsoft, NVIDIA, OpenAI, Platform and Business Model|

Executive Summary OpenAI is conducting an unprecedented experiment in governance. Within just two weeks, it announced partnerships with AMD to build a second GPU architecture and with Broadcom to develop custom ASICs, moving from diversifying dependencies to redesigning the very foundations of its computing power. It has deliberately turned complexity into a governance strategy. By maintaining three architectures, including CUDA, ROCm, and ASICs, OpenAI accepts higher integration costs in exchange for the ability to create

Reshaping the AI Chess Game: Why NVIDIA Is Betting on Intel and Teaming Up with OpenAI

Jane2025-09-23T16:03:19+08:00September 23rd, 2025|Categories: Featured Notes, Global Business Dynamics, Strategic Tech and Market Signals|Tags: AI Hardware and Chips, AI Strategy and Ecosystem, Amazon and AWS, AMD, Arm, ASE, Broadcom, Foxconn, Google, Inventec, Market Sentiment and Reflexivity, Meta, Microsoft, Narrative and Trust, NVIDIA, OpenAI, Platform and Business Model, Quanta, Supply Chain and Manufacturing, TSMC, Wistron|

Executive Summary NVIDIA recently announced two major moves: investing in Intel to co-develop custom x86 CPUs with NVLink, and partnering with OpenAI to build AI infrastructure at the scale of a million GPUs. These actions may seem independent, but they reveal the same trend: the bottleneck in AI is shifting from the number of GPUs to the efficiency of CPU–GPU integration. In this transition, NVIDIA is reinforcing cross-platform standards through NVLink, Intel is focusing on

AI Deployment Bottleneck: Observing the Limits of AI Adoption and Market Narratives

Jane2025-08-27T11:22:03+08:00June 3rd, 2025|Categories: Strategic Tech and Market Signals|Tags: AI Hardware and Chips, AI Strategy and Ecosystem, AMD, Asia Vital Components, Auras, Foxconn, Inventec, Market Sentiment and Reflexivity, NVIDIA, Policy and Tariffs, Quanta, Supply Chain and Manufacturing|

Executive Summary: From NVIDIA to the Rack When we talk about artificial intelligence (AI), the spotlight usually stays on models, compute power, and chips. But the most critical phase, which is deployment, is often left out of the conversation. Getting from NVIDIA’s chips to a fully operational rack in a data center takes far more than engineering. It requires navigating manufacturing logistics, capital pressure, thermal limits, geopolitical shifts, and a changing platform landscape. This article

AI Chip Market Evolution Part 2: Edge AI Training, Inference and Market Trends

Jane2025-09-19T11:46:04+08:00February 19th, 2025|Categories: Future Scenarios and Design, Strategic Tech and Market Signals|Tags: AMD, DeepSeek, Edge AI, NVIDIA, Platform and Business Model, Supply Chain and Manufacturing|

Introduction to Part 2 Following our previous discussion on the cloud AI training and inference market, this article will focus on the on-premises AI chip market for training and inference. Compared to the cloud market, on-premises AI solutions offer distinct advantages in low latency and data privacy. As emerging applications such as autonomous vehicles and smart devices grow, on-premises AI training and inference are expected to be key drivers of future market expansion. This article

AI Chip Market Evolution Part 1: Cloud AI Training and Inference

Jane2025-08-30T12:59:50+08:00February 18th, 2025|Categories: Future Scenarios and Design, Strategic Tech and Market Signals|Tags: Amazon and AWS, AMD, Cloud AI, DeepSeek, Google, Meta, NVIDIA, Platform and Business Model, Qualcomm, Supply Chain and Manufacturing|

Executive Summary The AI chip market is undergoing significant transformations, which can be understood through two key dimensions: deployment environments (cloud vs. edge) and market segments (training vs. inference). Cloud-based training currently dominates the market and is expected to maintain strong growth in the future. Training is critical for AI model development, requiring immense computational power to process vast amounts of data, which is why it is primarily concentrated in cloud data centers. NVIDIA is