Vitalik Buterin pfp
Vitalik Buterin
@vitalik.eth
A fun math aside, on the idea of splitting a large zk proving workload between multiple provers. Suppose you have N provers, and you have a proving workload that you split into N parts (so, one part per prover). You require provers to pre-register, but registration is open-access. Suppose you have a constant fault rate (eg. 1/5 of registered provers fail). Provers expect to complete in one round (eg. 3s). If one prover fails, other provers have to come in and re-prove that load. How many rounds does it take for the entire workload to get proven? Answer: log*(N) (yes, that's the iterated-log function) Why: In the first round, you go from N unproven workloads to N/5 unproven workloads In the second round, each remaining workload gets assigned 5 provers, so per-workload failure rate becomes 1 in 5^5. So you go to N / 5 / 5^5 unproven workloads In the third round, each remaining workload gets assigned ~5^5 provers, so failure rate is 1 in 5^(5^5). So you go to N / 5 / 5^5 / 5^(5^5) unproven workloads
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polymutex pfp
polymutex
@polymutex.eth
This seems to assume that provers would unconditionally accept redundant workloads. My sense is that in practice, economically-motivated provers would reject workloads when they know that a sufficient number of other provers are already working on the same workload. This saves on bandwidth/power costs.
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Nicki Sanders pfp
Nicki Sanders
@nicki
👀
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Zico 🐱👾 pfp
Zico 🐱👾
@hazzanzico
I wish I understood all what you're saying.
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Qomrade pfp
Qomrade
@qomrade
Sounds like beboundless.xyz
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Ashish 🎩 pfp
Ashish 🎩
@ashish-007
I love that everytime you post, I hook my bot to dumb it down so that I learn something cool and new everyday. That knowledge is very beautiful my guy!
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Dakota Roberson Lost Many Coins. pfp
Dakota Roberson Lost Many Coins.
@anarchybob6
ELIF? 😸
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G4zer19r pfp
G4zer19r
@g4zer19r
This is a fascinating insight into how fault tolerance can scale logarithmically in a decentralized proving system. The iterated logarithm growth truly demonstrates the efficiency gains from redundancy and parallel processing in zk-SNARKs.
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Peter Arogundade pfp
Peter Arogundade
@noblepeter2000
Lots are bringing in lots of variables not inputted in the already stated variable and that how things get complicated. 1+1 =2, except other faction or function are permitted to be added which they aren't, then let 1+1=2 simple. Its For fun, why complicate it again with unintended variables 😂. The homo of sapiens will always piens 😂
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Charlie Simms pfp
Charlie Simms
@validdiktorian
The open registration assumption is doing heavy lifting. What if registration required a stake that's slashed on failure? The failure rate becomes endogenous: stake/reward ratio determines participation quality. You could (theoretically) achieve O(1) rounds by making the stake curve superlinear in round number.
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Mind Attic pfp
Mind Attic
@mindattic
Help us with education 🤗 https://warpcast.com/mindattic/0x4d46c874
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SuperAI pfp
SuperAI
@superai
May you stay optimistic and strong through challenges! Wishing you success! #Optimistic #Strong
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Coin Space pfp
Coin Space
@coinspace
Hope you find peace and joy in every moment! Life is beautiful! #Peace #Happiness
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Lewis pfp
Lewis
@8999
Eth is King
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Fer pfp
Fer
@ferdj
F or normal humans Give N workers N tasks (one each). ~20 % screw up. The few leftover tasks get a lot more helpers next round. That “pile-on” halves the problem so brutally that the whole job wraps up in about log*(N) rounds—think “take log, then log of the log, repeat until 1.” Even if N is a billion, log*(N) ≈ 5. So you’re done in a handful of rounds. Fast.
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IamCharis.base.eth pfp
IamCharis.base.eth
@iamcharis
+1 to this. (Even if I have no idea what you’re talking about🫠)
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Hugo Montenegro pfp
Hugo Montenegro
@hm
that's so neat So its never gonna go above like 4 rounds. Wow!
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Fairman(Ø,G) pfp
Fairman(Ø,G)
@fairman
I don’t understand a damn thing
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Fractal Visions pfp
Fractal Visions
@fractalvisions.eth
There needs to be some sort of AI integration here to help summarize all of this…
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