TPU

TPU is an AI-specific chip designed by Google itself. It is attracting attention as a rival to NVIDIA GPUs.

TPU (Tensor Processing Unit) is a dedicated semiconductor designed by Google to optimize AI calculations. Instead of using commercially available all-purpose cooking utensils (GPUs), Google has made its own kitchen equipment tailored to the menu of its restaurants. Google operates much of its AI infrastructure, including search, translation, and Gemini model training, with TPUs.

As the price of NVIDIA GPUs soared due to the AI boom and competition to secure supplies intensified, the trend of developing in-house chips to reduce dependence on specific companies grew, and TPUs became a representative example. It is also provided to external companies through Google Cloud, and is attracting attention in the market as an alternative to NVIDIA's proprietary system.

However, since TPU is optimized for the Google ecosystem, a limitation is that there are conversion costs involved in moving the development environment familiar with NVIDIA's software ecosystem (CUDA).

✅ Why it matters

• Specialized in AI calculations and efficient for large-scale learning and service operation
• Promotes market competition as an alternative to reducing dependence on NVIDIA GPUs
• This is a representative example of understanding the competitive landscape of the AI semiconductor industry

⚠️ Limits and debates

• It is provided mainly on Google Cloud, so the usage environment is limited
• The conversion cost of moving from the NVIDIA software ecosystem is high
• It is not a product that general consumers can directly purchase and use.