Overview
The AI ASIC market is rapidly expanding, with TPUs shifting from internal use to external commercialization due to their energy efficiency and customization. Leading cloud and tech firms actively develop in-house ASICs to reduce costs and supply risks, driving AI hardware toward high performance, low power, and diverse applications, becoming the main accelerator after GPUs.
Key Highlights:
- The AI ASIC market is experiencing rapid growth, driven by increasing cloud service demand and AI model scale.
- TPUs have advantages in energy efficiency and vertical integration, offering better cost structure and customization than high-end GPUs.
- Major US cloud providers and leading tech firms (Tesla, OpenAI, Apple) actively develop in-house ASICs tailored to specific AI applications.
- In-house ASIC development reduces long-term compute costs and supply chain risks, enhancing competitiveness.
- AI ASIC applications are expanding from training and inference to voice generation, real-time translation, recommendation systems, and edge AI, enabling wider commercialization and vertical market penetration.
- Chip design service providers support industry growth, positioning AI ASICs as the second major AI acceleration hardware after GPUs.