PIR with preprocessing can remove the 1-of-2 trust requirement by having the client precompute many random-query XOR sums after an upfront full-database download, effectively acting as one of the two servers.
Plinko reduces both client communication and server compute from O(N) to O(sqrt(N)) while using preprocessing to eliminate the trust assumption.
For an Ethereum-like dataset of 10 billion 32-byte values arranged as a 100000x100000 grid, Plinko would require storing about 100000*128 hints (approximately 390 MB), plus additional backup hints.
Why-Gkr-Is-Fast (Commitment Avoidance And Sumcheck Reductions)
A key efficiency mechanism of GKR is that it avoids committing to intermediate-layer values and requires commitments only to inputs and outputs.
For Poseidon-style cubing layers, the GKR reduction can be implemented via a degree-4 sumcheck that relates a next-layer evaluation to a sum over previous-layer values transformed by cubing and round constants.
A demo cost model described suggests GKR proves Poseidon hashes with about 15× theoretical overhead versus roughly 100× for STARK approaches that commit to all intermediate trace values.
Investing Culture Trust And Information Edges
West Coast investors can outperform when a visceral product leap precedes obvious numerical proof because they are more willing to translate qualitative experience into future market expansion.
The alien-founder view over-attributes success to innate genius because it ignores the compounding training effect of years of operating and learning while building a company.
A key unresolved question for crypto is whether today’s projects resemble early-internet dead ends or eventual winners.