Zero-knowledge proofs are basically a way to trust code execution without re-running it yourself.
Compile C# to a minimal RISC-V runtime. You run the program once, and instead of shipping all the outputs and logs, you generate a zk proof—a tiny math receipt that says "this execution was correct." Anyone can verify that receipt in milliseconds.
It's a bit like TEEs (Intel SGX, AMD SEV) where you outsource compute to someone else and rely on hardware to prove they ran it faithfully. The difference is zk proofs don’t depend on trusting special chips or vendors - it's just math.
Implications:
* Offload heavy workloads to untrusted machines but still verify correctness
* Lightweight sync and validation in distributed systems
* New trust models for cloud and datacenter compute
Im not familiar with how these zk proofs work, but for a PoW scheme I was working with the binary proofs were over 60kb - and they were sample based to decrease probability of cheating - not an absolute proof without full replay.
Do you have some info/resource to describe how these proofs work and can be so small?
There's different proof constructions, but many are depending on recursive SNARKs. You basically have an execution harness prover (proves that the block of VM instructions and inputs were correct in producing the output), and then a folding circuit prover (that proves the execution harness behaved correctly), recursively folding over the outer circuit to a smaller size. In Ethereum world, a lot of the SNARKs use a trusted setup — the assumption is that for as long as one contributor to the ceremony was honest (and that there wasn't a flaw in the ceremony itself), then the trusted setup can be trusted. The outsized benefit of the trusted setup approach is that it allows you to shift the computational hardness assumption over to the statistical improbability of being able to forge proof outputs for desired inputs. This of course, assumes that the trusted setup was safe, and that quantum computers aren't able to break dlog any time soon
Compile C# to a minimal RISC-V runtime. You run the program once, and instead of shipping all the outputs and logs, you generate a zk proof—a tiny math receipt that says "this execution was correct." Anyone can verify that receipt in milliseconds.
It's a bit like TEEs (Intel SGX, AMD SEV) where you outsource compute to someone else and rely on hardware to prove they ran it faithfully. The difference is zk proofs don’t depend on trusting special chips or vendors - it's just math.
Implications:
* Offload heavy workloads to untrusted machines but still verify correctness
* Lightweight sync and validation in distributed systems
* New trust models for cloud and datacenter compute