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RE: LeoThread 2025-10-16 23-29

in LeoFinance6 days ago

Part 4/11:

  • Achieving the desired location (market fit)

  • Staying within budget

Only two are achievable at once. Similarly, AI projects often face compromises:

  • Rapid deployment on cloud platforms like AWS, GCP, or Azure can lead to unexpectedly high costs due to cloud service pricing models—such as Nvidia H100 GPU prices, which can be four times the market rate.

  • On the other hand, buying in-house infrastructure reduces ongoing costs but sacrifices agility, scalability, and speed—moving backwards in the trilemma.

The Cost of Cloud-Based AI Development