{"type":"rich","version":"1.0","provider_name":"Transistor","provider_url":"https://transistor.fm","author_name":"Inside Taiwan","title":"Inside Taiwan 2025: The Year That Changed the Physical Economy and What Comes Next in 2026","html":"","width":"100%","height":180,"duration":767,"description":"Inside Taiwan 2025: The Year That Changed the Physical Economy and What Comes Next in 2026In this New Year special, Inside Taiwan reviews how AI became a physical economy in 2025, shaped by chips, energy, capital, and geopolitics. Based on signals across the supply chain, we examine the defining questions of 2025 and present ten predictions that will shape AI infrastructure, markets, and the global economy in 2026.Q1. Why was 2025 the year AI became physical rather than theoretical?Because demand hit real world limits. In 2025, AI growth was constrained by fabs, power grids, and advanced packaging capacity. The market stopped asking what AI could do and started asking how fast infrastructure could be built.Q2. Was the AI boom in 2025 a bubble or a new industrial revolution?The supply chain suggests an industrial shift. Nvidia reached a roughly five trillion dollar valuation and TSMC capacity was fully utilized. Analysts noted there were no idle GPUs. The risk was not unused infrastructure but overoptimistic timelines for returns.Q3. Why did energy become a defining issue for AI in 2025?AI computing is electricity intensive. OpenAI warned US policymakers that roughly 100 gigawatts of new power per year would be needed to sustain growth. Tech firms began pursuing nuclear and dedicated power deals as grid limits became visible.Q4. Why did geopolitics reshape the semiconductor supply chain in 2025?Supply chains split along strategic lines. The US and allies pushed secure chip ecosystems while China accelerated domestic alternatives. This marked the rise of Sovereign AI where nations seek control over compute, data, and models.Q5. What are the most important trends to watch in 2026?Key signals include the start of 2 nanometer production at TSMC, shortages in high bandwidth memory, wider use of enterprise AI agents, growth of custom AI chips, nuclear powered data centers, packaging capacity as a bottleneck, robotics adoption, an intense talent war, and a clear ROI...","thumbnail_url":"https://img.transistorcdn.com/LqTRKEl1kn18xdK6FQ6pNw-ohLuPiH720A1uYWZ8820/rs:fill:0:0:1/w:400/h:400/q:60/mb:500000/aHR0cHM6Ly9pbWct/dXBsb2FkLXByb2R1/Y3Rpb24udHJhbnNp/c3Rvci5mbS8zMjI4/NmVlMmMyMTI1YjI0/ZmZhOWI3YzRkZDZm/ZDIzZC5wbmc.webp","thumbnail_width":300,"thumbnail_height":300}