$ETH has found a new intersection with AI that’s already live: privacy payments.
On October 1, the Ethereum Foundation blog introduced zkAPI and said it has been running on the Ethereum mainnet. It allows users to first deposit usage credits, then authorize API consumption via zero-knowledge proofs—separating the link between payment identity and requests.
In my view, this is more worth tracking than a simple “AI + blockchain” slogan: it corresponds to real needs for paying for services. But going live with the technology is only the starting point. Next, we need to see whether providers integrate it and whether users keep using it.
First, only if the integration footprint expands and repeat usage increases do we have a stronger basis to discuss whether it has truly found a real demand. The attention generated by one release and continued usage are different stages.
Second, if the operation is complex and service coverage is limited, even if the privacy design is valuable, it may be difficult to translate into large-scale applications.
Third, even if the application grows, we need to keep watching how it creates on-chain settlement demand. You can’t directly convert adoption growth into an ETH price increase.
There’s also a boundary: providers can still see the request content and network information such as IP addresses. This isn’t “AI can’t see you at all.”
What I’d really like to see is whether ETH can actually accommodate real service payment demand. With a concrete product now available, the next step lies in the adoption data.
#ETH #AI #以太坊
On October 1, the Ethereum Foundation blog introduced zkAPI and said it has been running on the Ethereum mainnet. It allows users to first deposit usage credits, then authorize API consumption via zero-knowledge proofs—separating the link between payment identity and requests.
In my view, this is more worth tracking than a simple “AI + blockchain” slogan: it corresponds to real needs for paying for services. But going live with the technology is only the starting point. Next, we need to see whether providers integrate it and whether users keep using it.
First, only if the integration footprint expands and repeat usage increases do we have a stronger basis to discuss whether it has truly found a real demand. The attention generated by one release and continued usage are different stages.
Second, if the operation is complex and service coverage is limited, even if the privacy design is valuable, it may be difficult to translate into large-scale applications.
Third, even if the application grows, we need to keep watching how it creates on-chain settlement demand. You can’t directly convert adoption growth into an ETH price increase.
There’s also a boundary: providers can still see the request content and network information such as IP addresses. This isn’t “AI can’t see you at all.”
What I’d really like to see is whether ETH can actually accommodate real service payment demand. With a concrete product now available, the next step lies in the adoption data.
#ETH #AI #以太坊