AI Is Challenging Silicon Valley’s Two-Decade Belief in Being Asset-Light: How Tech Giants Are Deepening Their Bets on Hardware and Infrastructure

2025-11-04T16:03:38+08:00November 4th, 2025|Categories: Featured Notes, Global Business Dynamics, Strategic Tech and Market Signals|Tags: , , , , , , , , |

Executive Summary Over the past two decades, Silicon Valley’s formula for success has been built on the belief in staying asset-light. The scalability of software and the power of network effects became the most efficient levers for growth, driving companies to pursue speed, scale, and operational lightness. Generative AI, however, is disrupting this model. From Microsoft and Amazon to Google, Meta, Apple, and Tesla, the world’s largest tech companies are collectively returning to a world

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

2025-09-23T16:03:19+08:00September 23rd, 2025|Categories: Featured Notes, Global Business Dynamics, Strategic Tech and Market Signals|Tags: , , , , , , , , , , , , , , , , , , , , |

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 Strategy Shifts Among the Big Six: Four Core Trends from Compute Scale to Efficiency Competition

2026-01-25T11:42:27+08:00August 6th, 2025|Categories: Featured Notes, Global Business Dynamics, Strategic Tech and Market Signals|Tags: , , , , , , , , |

Executive Summary In less than three years, the focus of the AI race has shifted three times. It began with a contest to build the largest and most capable models, moved into a rush to secure computing power, and has now arrived at a phase defined by efficiency, the rise of AI agents, and the first real tests of commercial viability. Based on insights from the most recent earnings calls of six leading technology companies

Apple AI Governance

2025-08-27T10:15:05+08:00July 31st, 2025|Categories: Featured Notes, Global Business Dynamics, Strategic Tech and Market Signals|Tags: , , , , , , , |

Executive Summary Apple’s measured approach to AI is often explained as a matter of philosophy, with a commitment to user control, privacy, and thoughtful design.But this may miss the deeper story. Unlike peers such as Meta, Microsoft, and Google, which are reshaping their platforms for an AI‑first era, Apple still operates within a governance and product rhythm built for hardware dominance. As AI shifts the rules of competition toward openness, rapid iteration, and cross‑platform integration,

Adobe Is Not Just an AI Company: Rebuilding the Digital Content Supply Chain

2025-09-02T17:31:59+08:00April 9th, 2025|Categories: Global Business Dynamics|Tags: , , , , , , , |

Executive Summary In the generative AI race, Adobe isn’t the fastest player but it may be the most strategic and well-rounded. While most companies focus on breakthroughs and market expansion, Adobe has taken the lead in content governance, regulatory engagement, and education. It’s not just building AI tools. It’s laying the foundation for a trusted, commercial-grade digital content ecosystem. From Firefly’s licensed training data and content credentials to GenStudio’s end-to-end content pipeline and Adobe’s proactive

OpenAI’s AI Ecosystem Strategy: Insights from the Stratechery Interview

2025-08-28T16:28:15+08:00March 24th, 2025|Categories: Featured Notes, Global Business Dynamics|Tags: , , , , , , |

Executive Summary OpenAI is actively strengthening its global leadership by accelerating the adoption and application of AI through a diverse range of strategies. The company is focused on enhancing ChatGPT’s user experience and capabilities while expanding its footprint in the consumer market. To achieve this, OpenAI has reinforced its subscription model, deepened enterprise collaborations, and explored multiple revenue streams, including new subscriptions, corporate partnerships, and advertising. On the technological front, OpenAI is committed to advancing

Exploring Weak Signals: Broadcom ASICs

2025-08-27T17:02:18+08:00March 14th, 2025|Categories: Global Business Dynamics, Strategic Tech and Market Signals|Tags: , , , , , , , , , |

Executive Summary In the rapidly evolving AI hardware space, discussions often center around the competition between different chip architectures, particularly GPUs and ASICs. While NVIDIA’s GPU has traditionally dominated AI training, ASICs have generally been seen as more suitable for the AI inference stage. However, Broadcom’s recent commentary during its earnings call on AI training-specific ASICs has caught our attention, potentially signaling a subtle shift in the industry’s understanding of AI workloads and the role

Microsoft Strategic Shift: 2025 AI Market and Fungible Data Center

2025-08-30T13:10:58+08:00March 1st, 2025|Categories: Featured Notes, Global Business Dynamics, Strategic Tech and Market Signals|Tags: , , , , , , , , |

Executive Summary Microsoft’s recent capital expenditure adjustments underscore a pivotal shift in the AI market, as the primary focus transitions from model training to inference. Distributed inference is emerging as a significant yet underappreciated demand driver. The company’s decision to delay certain data center construction projects signals a strategic recalibration in response to evolving market structures, a trend mirrored by Google, Amazon, and Meta. However, Microsoft’s fungible data center concept stands out as a key

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

2025-08-30T12:59:50+08:00February 18th, 2025|Categories: Future Scenarios and Design, Strategic Tech and Market Signals|Tags: , , , , , , , , , |

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

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