Jakarta, Pintu News – Ethereum (ETH) founder Vitalik Buterin introduced the GKR protocol, which consists of various innovations to enable ultra-fast proof systems. He called this solution a set of protocols that form the basis of the high speed of many proof systems currently in use.
In his explanation, Buterin highlighted the implementation of GKR to prove Poseidon’s hash.
Buterin opened his piece by acknowledging the existence of a very fast ZK-prover. This is the ZK-EVM prover that can represent Ethereum Layer-1 in real-time using just 50 consumer GPUs.
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“It took only a consumer laptop to prove 2 million Poseidon hashes per second, and the ever-increasing speed of the zk-ML system to prove LLM inference,” Buterin said.
This is where the GKR protocol comes into play. It is the main foundation for these provers. GKR is designed to enable fast ZK-EVM and zk-ML proofs. It is optimized for computations that have many low-degree layers and repeated functions, such as hashing and neural networks.
All GKR needs is a commitment to inputs and outputs – not to layers of intermediaries. In the long run, this approach improves efficiency significantly.
What Buterin means by “commitment” is putting data into a cryptographic data structure, which can be done through KZG or Merkle trees, as long as it allows users to prove certain claims over the data.
However, it is important not to misunderstand: GKR is not a zero-knowledge protocol as it only handles the succinctness, not the privacy. Even so, the zero-knowledge aspect can still be achieved with GKR, simply by wrapping the proof into ZK-SNARK or ZK-STARK.
In recent times, Vitalik Buterin, co-founder of Ethereum, has also started discussing various issues related to artificial intelligence models.
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Two months ago, he criticized the AI industry for focusing too much on agentic models, which are autonomous systems that act on their own without much human intervention. According to him, there are already too many such systems and this is not a good thing.
Buterin argues that systems that allow more human input produce better and safer results. His view is in line with that of Andrej Karpathy, Tesla’s former AI director, who also advocates a similar approach.
He also stated that he is more interested in open-weight AI models, as they have more powerful and flexible editing capabilities.
In September, Buterin again emphasized that over-reliance on AI, especially forgovernance, could be very dangerous.
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