Global Insight Notes

 LPDDR used to be seen simply as a “mobile DRAM.” But in 2025, it is becoming a foundational component of the global AI hardware boom , powering everything from edge devices to autonomous systems and lightweight AI compute. The next memory supercycle may not be driven by server DRAM alone — LPDDR is taking center stage. 🚀 1. LPDDR Is Now the Core of Edge AI AI workloads are shifting from centralized cloud GPUs toward: on-device inference low-power AI accelerators IoT-embedded compute robotics and autonomous mobility LPDDR’s high bandwidth + low power + compact design fits perfectly into this shift. This emerging demand is structurally different from older smartphone-only cycles. 📈 2. 2025 Will Be a Supply-Demand Inflection Point Global research houses expect: LPDDR5/5X production tightening through mid-2025 Mobile, VR/AR, wearable, and auto-LiDAR systems expanding rapidly AI PCs beginning mass adoption Edge TPU/GPU units requiring LPDDR as st...

  The proposed U.S.–Korea Strategic Investment Corporation (SKIC) is emerging as one of the most significant policy concepts of 2025. More than a bilateral investment platform, SKIC signals a shift toward joint industrial planning, shared capital deployment, and coordinated supply-chain strategy between the two countries. If implemented, SKIC could redefine how both nations allocate resources across critical sectors like semiconductors, EVs, batteries, defense tech, and AI infrastructure. 🔍 1. SKIC as a New Industrial Policy Framework Unlike traditional cross-border funds, SKIC aligns public policy goals with private-sector capital , creating a system in which: Washington’s reshoring agenda meets Seoul’s scaling agenda Joint investment can support fabrication, research, and deployment Capital allocation becomes a policy tool, not just a market function This makes SKIC far more strategic than a typical bilateral finance vehicle. 🔋 2. Supply Chain Security Is th...

  Executive Summary The November FOMC meeting revealed the clearest hints yet of a potential Fed pivot in early 2025 . With inflation cooling, labor-market pressure easing, and forward guidance subtly shifting, global markets are pricing in an accelerated rate-cut timeline . This shift could reshape U.S. liquidity, global capital flows, and emerging-market risk premiums. 1. Key Insights The Fed’s tone shifted from “higher for longer” → “data-dependent easing.” Core PCE inflation is now moving firmly toward the 2% target. Bond markets are pricing 2–3 cuts in 2025 , earlier than previously expected. Financial conditions have tightened enough to substitute for further hikes. Global EM currencies may stabilize as U.S. rate-cut expectations strengthen. 2. What Changed After the November FOMC? 2.1 A Softer Tone from Powell For the first time in months, Powell emphasized that “the risks of doing too much and too little are becoming more balanced.” This is the cla...

  U.S. immigration policy is more than a political storyline — it is one of the fastest ways to read upcoming shifts in labor supply, technology competitiveness, wages, and sector-level investment flows. As Trump’s 2025 policy direction takes shape, three areas stand out: border control, high-skilled visas, and industry-specific labor policy. This changing landscape also aligns with insights from one of my earlier WordPress analyses, which explored how labor scarcity shapes tech-sector valuations. (Internal link: Insert your WP URL here and I will apply it naturally ) 1) The Core of Trump’s 2025 Immigration Approach 1. Border Enforcement Tightening Stronger surveillance and detention policy Expansion of border security budgets Stricter long-term stay eligibility Impact: Decreased labor supply in low-wage and seasonal sectors, raising structural wage pressure. 2. Skilled Visa Restructuring (H-1B, OPT, STEM) Prioritization of U.S.-critical industries Potentia...

The AI world is entering a new phase. Training chips — especially TPU-class accelerators — will determine which countries and companies lead the next wave of AI innovation. 1. Why TPU Demand Is Surging in 2025 AI models are doubling in size every few months. GPU-based training has become too expensive, too slow, and too power-hungry. Meanwhile: TPUs deliver higher FLOPS per watt, lower cost per training run, and more stable scaling across large clusters. This shift explains why major cloud regions (U.S., UAE, Korea, India) are adopting TPU-like accelerators in sovereign AI strategies. 2. TPU vs GPU — The Real Difference Category GPU TPU Flexibility Excellent Medium Training Throughput Good Superior Cost Efficiency Moderate High Best Use Case Inference + general compute Large-scale training The more parameters a model has, the more likely TPUs outperform GPUs in both speed and cost. 3. Who Will Dominate TPU Infrastructure in 2025? 🇺🇸 United States Still leads TPU architecture, com...