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Only the performance of Gemini is discussed, but when incorporating language-based generative AI into business, it is useless unless a mechanism for fine tuning or search expansion generation is incorporated.

When GCP uses VartexAI search and conversation, it is possible to incorporate a search expansion generation mechanism without the need for special development, and operation costs are only a few thousand yen per month.

If an equivalent mechanism is realized with AWS, development costs are high and it costs a fixed monthly fee of 3000 dollars or more, so Google is superior when focusing on introducing generative AI into business.

Also, as is the case with Microsoft's ChatGPT, as can be seen from the fact that all language generation AI in recent years has been developed from technology in papers published by Google Deepmind, when services are released on the cloud, there is an advantage that when services are released on the cloud, a path up to business integration that goes one step further compared to the other two companies is released as a set.

If a society that really utilizes generative AI comes in the future, GCP will definitely grow.

Microsoft, which has introduced AI to Windows and Microsoft Office, will grow mainly in government offices and non-IT companies.

AWS is lagging behind with generative AI, and it hasn't reached the point where it is possible to build products that comprehensively launch use cases, and to be honest, I don't know the future, but it's strong in Japan, where information engineering education is immature