A proof-of-work puzzle can be hard to solve, or it can reward work that is actually useful, but not both. RIBO resolves this with Bounded-Composition Useful Proof-of-Work (BC-UPoW). Security comes from sequential time. Useful work buys a bounded discount — and the protocol is currently in active development.
Whether you'll be running a prover farm, submitting open research problems, or auditing the protocol, the Ribosome Network is being designed to turn your compute into a bounded, verifiable claim on chain — once it ships.

Run the canonical RNA verifier, generate a knowledge-sound zkVM execution proof, submit it bound to a fresh epoch beacon. The protocol's security is sequential; the useful part earns a bounded discount — once the network launches.

Open research problems in multi-state RNA inverse design can be submitted to the network. Verified solutions are immutably anchored on-chain — timestamped proof of discovery. The ceiling on coupling means the reward never silently erodes security.

RIBO is being developed in the open. The BC-UPoW framework, the VDF construction, the zkVM verification relation, and the RNA verifier are all specified in the whitepaper. Contribute to a reference implementation, audit the security argument, or build tooling.
A Verifiable Delay Function (VDF) evaluates repeated squarings in a class group of unknown order. This establishes a baseline cost that requires inherently sequential time and cannot be meaningfully accelerated by parallel hardware.
Solvers tackle multi-state RNA inverse design — finding a single sequence that satisfies a set of target secondary structures under varying physical conditions while avoiding anti-target configurations. An adversary could use a free, instant oracle for this; the protocol's security does not depend on the biological problem's hardness.
Solvers generate a knowledge-sound succinct proof that a deterministic RNA verifier ran for at least c_min cycles and accepted the candidate. The proof is bound to a fresh epoch beacon, and the cryptographic hash of the discovered sequence is exposed as a public input to enforce Data Availability.
Valid zkVM proofs are counted per epoch. The biological work earns a discount off the sequential cost, but this discount is mathematically capped by δ_max. The discount function δ(k) = α·√k is monotone concave in the number of independently-keyed submissions k.
The combination of the VDF evaluation and the zkVM proofs determines block validity. Even with a perfect biological algorithm, attack cost never drops below (1 − δ_max) · C_h. The plaintext RNA sequence is permanently recorded on the public ledger as a scientific commons.
"For any useful problem U and for any computational strategy or optimization algorithm developed for it (including a theoretical possibility of an oracle that outputs a solution for free instantly), the attack cost is bounded: Cattack ≥ (1 − δmax) · Ch."
R = { (pid, x, y, c_min, h_w) |
∃ w : Exec(pid, x, w) = y
∧ consumed ≥ c_min
∧ H(w) = h_w
}Every accepted solution is broadcast to the network as a single signed message. The plaintext RNA sequence (discovered_seq) is mandatory — submissions with missing, hidden, or mismatched sequences are entirely rejected, enforcing strict Data Availability.
Guarantees that 85% of block cost is always pure sequential work.
Calibrates the discount curve relative to submission volume.
Number of unique solutions to reach the max discount.
Prevents a single participant from providing more than 1% of the epoch's count.
10 to 300 ms per RNA structure
10³ to 10⁴ cycle multiplier
5 to 30 min on general-purpose solver hardware
< 5 ms per submission (recursive proof pipelining)
The Zuker-Stiegler recurrence and McCaskill's algorithm are the decades-old deterministic backbone of our verifier. We use zkVMs in the most conservative way: prove a fixed program ran, on a fixed input, for at least a fixed number of cycles. The zero-knowledge privacy property is intentionally bypassed — the discovered sequence must be published on-chain.
Zuker-Stiegler recurrence (1981). The deterministic backbone that checks if the sequence folds into the target structure σ_i under physical conditions P_i.
McCaskill's algorithm (1990). Computes the equilibrium probability of the target structure to ensure P(σ_i | s, P_i) ≥ 0.5.
For each physical condition P_i, the MFE structure for sequence s must never equal any anti-target configuration τ_i. Avoids off-target therapeutic behaviour.
Finding a sequence s ∈ Σ that satisfies all targets while avoiding anti-targets. Solvers use ML or heuristics, but consensus only checks the zkVM proof.
RIBO HAS NO INSTITUTIONAL USERS YET — THE PROJECT IS IN ACTIVE DEVELOPMENT
We do not use the zero-knowledge property for anything security-critical. The real value of zkVMs is succinctness and knowledge soundness. A solver takes minutes to generate a proof; any full node verifies it instantly via recursive proof pipelining. This is why the network evaluates useful work on an epoch scale rather than per-block.
RIBO is being developed conservatively. The whitepaper explicitly recommends launching with the discount parameter set to zero (δmax = 0) — solutions can still be submitted, verified inside the zkVM, and stored on-chain, but the discount to the sequential baseline is zero, preserving full ledger security while behaviour is observed across multiple epochs.
RIBO is still in development. Join the mailing list to receive protocol updates, spec revisions, and an early heads-up when the zero-discount testnet opens. No tokens, no sales — just research and engineering progress.
RIBO IS NOT YET DEPLOYED. ANYONE OFFERING TO SELL $RIBO OR CLAIMING INSTITUTIONAL PARTNERSHIPS IS NOT AFFILIATED WITH THIS PROJECT.