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AI compute costs a lot.
Google pays SpaceX 920 million dollars a month. Large models need thousands of GPUs. Startups struggle to pay these bills.
Token economics offer a solution. New projects issue tokens for compute access. These tokens provide governance rights. They offer a share of future revenue.
This creates a decentralized network. It lowers costs for small teams.
Check these examples:
- Akash Network
- Render Token
These networks link spare GPU owners to users. Some users earn tokens by giving data or compute power.
Challenges exist:
- Laws are unclear.
- Token prices fluctuate.
- Performance lags behind cloud giants.
The future is a mix. Big companies keep their own hardware. Small teams use token networks. You must understand both to secure resources.
Source: https://dev.to/vjswamy/the-rising-cost-of-ai-how-token-economics-are-reshaping-startup-funding-19lc Optional learning community: https://t.me/GyaanSetuAi