Recently, I have been diving deep into the GAIB project, and the more I look at it, the more I feel it could be one of the most noteworthy directions in the next wave of Alx DeFi narratives—"Financialization of Computing Power". Currently, discussions about AI in the market mostly revolve around macro aspects like supply and demand of computing power, GPU shortages, and the explosion of AI models, but there are actually very few projects that can organize these values through blockchain.
GAIB's approach is quite unique; it is not simply creating a computing power market but is attempting to build an "AI Computing Economic Layer" that allows the output of computing power to be split, priced, and circulated, and through the AID asset model, maps the returns of computing power into a divisible digital asset on the chain.
What does this mean? It means that in the past, only large institutions could participate in GPU computing returns; in the future, ordinary users will also be able to participate through on-chain methods, and even combine RWA, lending, and staking to form new yield curves.
More importantly, GAIB is not about "selling computing power" but about "turning computing power into combinable financial assets".
If this model proves successful, the flow of value in AI training and inference will undergo significant changes:
1. Resources will be more transparent
2. Returns will be more traceable
3. Computing power can be freely combined
4. The participation threshold in the AI ecosystem will be greatly reduced
Currently, the trend of AI x RWA x DeFi is becoming stronger, and projects like GAIB that focus on the "Computing Power Economic Layer" will have greater growth potential than those that simply supply computing power.
I will continue to follow this track and welcome everyone to share your thoughts. #gaib @GAIB AI
GAIB's approach is quite unique; it is not simply creating a computing power market but is attempting to build an "AI Computing Economic Layer" that allows the output of computing power to be split, priced, and circulated, and through the AID asset model, maps the returns of computing power into a divisible digital asset on the chain.
What does this mean? It means that in the past, only large institutions could participate in GPU computing returns; in the future, ordinary users will also be able to participate through on-chain methods, and even combine RWA, lending, and staking to form new yield curves.
More importantly, GAIB is not about "selling computing power" but about "turning computing power into combinable financial assets".
If this model proves successful, the flow of value in AI training and inference will undergo significant changes:
1. Resources will be more transparent
2. Returns will be more traceable
3. Computing power can be freely combined
4. The participation threshold in the AI ecosystem will be greatly reduced
Currently, the trend of AI x RWA x DeFi is becoming stronger, and projects like GAIB that focus on the "Computing Power Economic Layer" will have greater growth potential than those that simply supply computing power.
I will continue to follow this track and welcome everyone to share your thoughts. #gaib @GAIB AI