Blockchain and AI, two major technological waves, are sweeping in. One pursues openness and consensus, the other relies on data and computing power. They may seem parallel, yet they collide head-on at one point: privacy.
AI needs massive amounts of data, but how can sensitive information be safely put on-chain? Blockchain needs agents to execute strategies, but with code being open and transparent, wouldn’t the strategies be completely exposed? This contradiction severely limits the imagination for their integration.
The emergence of @zama, however, seems to point toward a new possibility. Leveraging fully homomorphic encryption, they are attempting to create an on-chain environment that is “computable yet invisible.” This not only adds privacy options, but more so quietly prepares the soil for a possible new species in the future.
Take their collaboration with @TheoriqAI on a “privacy AI agent,” for example. Imagine a DeFi fund management robot operating 24/7—on traditional chains, every step of its logic and every portfolio adjustment is fully visible, making it easy to track or copy. But under Zama’s FHE technology, the AI’s entire decision process happens in an encrypted state. It’s like a trader operating in dense fog; outsiders can only see the results of fund flows, but have no insight into the underlying strategies or logic. This may be the Achilles’ heel of DeFi automation: seeking automation while fearing exposure.
But this could be just the beginning. Such a “privacy computation layer” could nurture new ecosystems: 🔹 Confidential Machine Learning as a Service: Provide AI models on-chain, allowing enterprises to obtain encrypted predictions using encrypted data, with raw data never being exposed. 🔹 Collaborative Confidential Computing: Competitors can jointly train stronger models or conduct risk control on-chain without exposing their core data. 🔹 True Personal Data Sovereignty: Users can store encrypted medical and financial data on-chain, independently granting access to specific applications and maintaining full control.
@zama’s vision is to become the “privacy engine” of the Web3 world. Rather than making hit applications directly, it supports all apps that need privacy. When data can remain safe and “alive” on open blockchains, what we gain may not be a more closed system, but a new ecosystem that achieves more complex and intelligent collaboration based on protecting individual secrets.
This might also be a key step for blockchain to reach a broader world. #ZamaCreatorProgram
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Blockchain and AI, two major technological waves, are sweeping in. One pursues openness and consensus, the other relies on data and computing power. They may seem parallel, yet they collide head-on at one point: privacy.
AI needs massive amounts of data, but how can sensitive information be safely put on-chain? Blockchain needs agents to execute strategies, but with code being open and transparent, wouldn’t the strategies be completely exposed? This contradiction severely limits the imagination for their integration.
The emergence of @zama, however, seems to point toward a new possibility. Leveraging fully homomorphic encryption, they are attempting to create an on-chain environment that is “computable yet invisible.” This not only adds privacy options, but more so quietly prepares the soil for a possible new species in the future.
Take their collaboration with @TheoriqAI on a “privacy AI agent,” for example. Imagine a DeFi fund management robot operating 24/7—on traditional chains, every step of its logic and every portfolio adjustment is fully visible, making it easy to track or copy. But under Zama’s FHE technology, the AI’s entire decision process happens in an encrypted state. It’s like a trader operating in dense fog; outsiders can only see the results of fund flows, but have no insight into the underlying strategies or logic. This may be the Achilles’ heel of DeFi automation: seeking automation while fearing exposure.
But this could be just the beginning. Such a “privacy computation layer” could nurture new ecosystems:
🔹 Confidential Machine Learning as a Service: Provide AI models on-chain, allowing enterprises to obtain encrypted predictions using encrypted data, with raw data never being exposed.
🔹 Collaborative Confidential Computing: Competitors can jointly train stronger models or conduct risk control on-chain without exposing their core data.
🔹 True Personal Data Sovereignty: Users can store encrypted medical and financial data on-chain, independently granting access to specific applications and maintaining full control.
@zama’s vision is to become the “privacy engine” of the Web3 world. Rather than making hit applications directly, it supports all apps that need privacy. When data can remain safe and “alive” on open blockchains, what we gain may not be a more closed system, but a new ecosystem that achieves more complex and intelligent collaboration based on protecting individual secrets.
This might also be a key step for blockchain to reach a broader world.
#ZamaCreatorProgram