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The AI revolution isn’t slowing down because of a lack of ideas or software innovation. It’s being constrained by something far more physical and far less visible: advanced semiconductor packaging. At the center of this crisis is Chip-on-Wafer-on-Substrate (CoWoS)—a technology that has quietly become the most important bottleneck in the entire global AI supply chain. In this video, we take a deep dive into why CoWoS is now the gatekeeper of AI scale, why TSMC controls the overwhelming majority of CoWoS capacity, and why even record-breaking investments in fabs and packaging plants are failing to solve the shortage. While headlines focus on GPU launches and trillion-parameter models, the real battle is happening inside packaging facilities in Taiwan, where supply is rationed years in advance. We explain how AI accelerators from NVIDIA, AMD, Google, Microsoft, Amazon, Meta, and OpenAI all depend on CoWoS to connect massive compute dies with high-bandwidth memory. Without CoWoS, modern AI GPUs simply cannot function at the bandwidth, latency, and power efficiency levels required for large-scale training and inference. That dependency has turned CoWoS from a manufacturing step into a strategic asset. You’ll see how NVIDIA secured more than half of global CoWoS output, effectively locking in its dominance across AI data centers. We also explore how Broadcom, AMD, and hyperscalers compete for the remaining capacity, and why over 85% of all CoWoS production is already reserved years in advance, leaving little room for new entrants or startups. This allocation system has created a two-tier AI market: companies that control the supply chain, and everyone else who pays higher prices or waits in line. The video also breaks down why the problem goes far beyond packaging alone. High-Bandwidth Memory (HBM) is sold out through 2026, advanced logic nodes at 3nm and 2nm are fully allocated to AI workloads, and critical components like silicon interposers and ABF substrates face long lead times and yield challenges. Even if one bottleneck eases, the others immediately take its place, creating a persistent, multi-layered constraint. We examine the alternatives being developed to escape the CoWoS squeeze. Intel’s EMIB and Foveros packaging platforms promise lower-cost and more flexible approaches, while major OSATs like ASE, SPIL, and Amkor are racing to expand CoWoS-like capacity. These solutions offer partial relief, but none yet match the scale, yield, and integration depth of TSMC’s advanced packaging ecosystem. Looking forward, we explore CoPoS (Chip-on-Panel-on-Substrate)—TSMC’s next-generation platform that replaces round silicon wafers with large glass or sapphire panels. CoPoS promises larger AI chips, lower cost per die, and better thermal performance, but it won’t reach meaningful volume until 2028 or later, and early capacity will once again be limited to the biggest players. The geopolitical implications are impossible to ignore. With roughly 80% of global CoWoS capacity concentrated in Taiwan, any disruption—from trade restrictions to regional conflict—would instantly ripple across the global AI economy. Governments and companies are investing heavily in onshore and near-shore production, but advanced packaging outside Taiwan faces higher costs, slower learning curves, and years-long delays before reaching parity. Ultimately, this video explains why the AI chip shortage is not temporary, why prices remain high, and why access to compute is increasingly determined by capital and geopolitics rather than innovation alone. CoWoS has become the invisible infrastructure layer deciding who can build the next generation of AI—and who can’t. If you want to understand why AI hardware scaling is so hard, why NVIDIA’s margins remain elevated, why hyperscalers are building custom chips, and why the AI supply chain is more fragile than it appears, this video gives you the full picture. #cowos #tsmc #nvidia #aichips #copos #amd #intel #broadcom #taiwan #taiwan #hbm #highbandwithmemory #ai #semiconductor #semiconductorindustry