2025-12-29 07:20:32

Recently, I have been paying attention to the developments of projects combining AI and encryption, and I have looked into many new innovative technical solutions. One project has come up with a new approach in the field of zero-knowledge machine learning — jumping directly from theoretical verification to practical application, which shows real capability.

The most eye-catching aspect on the technical level is the combination of two components. One is DSperse slicing technology, which simply means breaking down those massive ML computation tasks into smaller parts that can be processed in parallel, with each part capable of generating a zero-knowledge proof independently. The other is the JSTprove engine used to run these proofs, which is significantly faster than previous solutions.

What does the improvement in zk verification speed mean for the entire ecosystem? It means that ML models can run on-chain without being painfully slow, and complex AI computations can be verified within an acceptable timeframe. From concept to implementation, many projects have been stuck for a long time, so seeing someone truly pushing it to production level is definitely worth paying attention to.

View Original

This page may contain third-party content, which is provided for information purposes only (not representations/warranties) and should not be considered as an endorsement of its views by Gate, nor as financial or professional advice. See Disclaimer for details.

18 Likes

Reward
18
6
Repost
Share

Comment

0/400

digital_archaeologist

· 01-01 05:13

Wow, the combination of DSperse with JSTprove is really impressive. Finally, someone has brought zk machine learning out of the PPTs. Is it finally not slow? If this really turns out to be reliable, that would be a game-changer. The on-paper data looks good, but what really counts is whether it can run on-chain. Let's see how it performs later. Both zero-knowledge and machine learning—this complexity is giving me a bit of a headache, but it definitely sounds different. Finally, someone is pushing forward with on-chain AI computation, much better than those who just talk big.

View OriginalReply0

FOMOSapien

· 2025-12-30 23:39

Wow, someone finally actually made zk-ML happen. All those projects that were hyped up before were really just air. What does it mean to be faster by a notch? There are more projects that can run now. The DSperse solution seems pretty solid—parallel processing plus independent proofs. Why didn't I think of that earlier? Can it really be used in production? I need to pull it in and check the code audit report first. If it's truly stable, on-chain ML might really take off.

View OriginalReply0

StablecoinGuardian

· 2025-12-29 07:36

The idea of zk-ML is indeed interesting. Previously, those projects hyped up loudly but proved to be extremely slow in validation. Now finally someone has made progress. However, can DSperse's slicing scheme truly run stably at production level, or is it just another wave of conceptual hype? If on-chain AI computing power can really break through, it depends on the actual use case implementation. It's still too early to tell. This parallel proof optimization approach is good; if it can also reduce costs, it would truly be a game changer. JSTprove is fast, but what about the gas fees? Still feel like something is missing.

View OriginalReply0

BlockchainNewbie

· 2025-12-29 07:34

Wow, does DSperse really break the speed barrier of AI proofing? I have to try it out. Finally, someone has turned zk-ML from a theoretical concept into a real product, gotta give them props. JSTprove is much faster, but what about the on-chain gas fees? That's the real key. The turtle-speed era might really be over; I'm a bit looking forward to the subsequent application implementations. Just talking about technology being awesome isn't enough; the key is what kind of ecosystem can be built. How does this parallel processing solution ensure security? It’s not that simple, right?

View OriginalReply0

APY追逐者

· 2025-12-29 07:33

Wow, finally someone has brought zk-ML to production level? It was all just theoretical before, now it can really run? Something's not right. How does DSperse ensure the proof quality of each slice... It's both ZK and AI, this trend is pretty intense, need to think it through carefully. By the way, how much has this efficiency improved? Can we see some data? Feels like we're about to step into another pit haha

View OriginalReply0

DoomCanister

· 2025-12-29 07:24

This is exactly what I wanted to see. Finally, someone has brought zk-ML from PPT to reality, no longer just theoretical discussions. The combination of DSperse+JSTprove is indeed powerful, doubling efficiency—pretty interesting. Running ML on-chain should no longer be stuck for ages; production-level tools are truly different. But I just want to ask, can this speed improvement really support real business scenarios... Only real-world validation with actual funds counts. I'm optimistic about this direction. zk definitely needs a new breakthrough.

View OriginalReply0