My first art piece for the @DlicomApp project is officially live
Meet the superhero of the decentralized world floating through the chaos with style
Loved bringing this
cosmic caped character to life for the community
The journey is just beginning
@joyhasanx10@timcrypt
1/7
Gmum
Blockchain scaling is usually framed as an execution problem
But there is a less obvious constraint underneath it
How fast can the network move the data required to keep everything in sync
@get_optimum@cryptooflashh@blockchainjeff
6/7
It is also about making the networks underlying information flow more efficient
That is why data propagation deserves to be treated as infrastructure rather than merely networking plumbing
7/7
Optimums bet is essentially that the next step in blockchain performance may come from moving less data more intelligently
And if that layer improves everything built above it gets more room to scale
6/7
Fermah says Froben has already generated 2.8M+ proofs with 99.7% reliability with ZKsync among its paying customers
The bigger idea isn't simply making proofs cheaper or faster
7/7
It's making proving a commodity layer that applications can consume without owning the machinery behind it
When that happens, ZK stops feeling like specialized infrastructure
It starts looking like compute
4/7
And Fermah Kernel is designed to stay neutral across proving systems rather than making applications depend on a single proving stack
That distinction matters
5/7
If proving infrastructure becomes an abstraction developers don't need to build and operate their own specialized proving fleets every time they want to use ZK
Proof generation starts becoming something applications can simply request
1/7
gFermah
Most people think ZK proving is mainly a compute problem
But as proving demand scales another bottleneck becomes harder to ignore: coordination
Who handles each workload?
Which machine should run it?
At what price?
@fermah_xyz@7wealthh
3/7
Froben turns proof generation into a two sided market: compute providers supply GPU/CPU capacity while ZK applications create demand
Its Matchmaker sits between them routing workloads based on the economics and performance requirements of each job
2/7
How do you balance latency reliability and cost across heterogeneous compute?
At that point proving starts to look less like buy more GPUs and more like a marketplace + scheduling problem
That’s the part of @fermah_xyz I find particularly interesting
gFermah
The UI is clean and easy to use but what interests me is what's underneath: proof requests workflows and settlement all running through one engine
Most people will judge it by the dashboard
I'm more curious how the system behaves under real load
@fermah_xyz@7wealthh
gDlic
DILI just floated out into space
A golden star trail swirls around him and his suit's coiled hose drifts along
Drew this one for @DlicomApp a little messy on purpose
Still can't tell if he's dancing or just lost up there
Maybe both
@timcrypto@retreeq_@MichaelWin3129
1/3
gFluton
Onchain privacy isn’t just about hiding the final transaction
If your intent route or strategy is exposed before execution the leak has already happened
That’s why @FlutonIO approach is interesting
@cryptoperseus_@thisislexer
2/3
Its encrypted intents are designed to stay private across the full lifecycle:
intent → routing → execution → settlement
FHE allows execution on encrypted data so the network can process an intent without exposing its plaintext