Makes a lot of sense. Needs indentation, btw
github.com/medovina/natur… wow! natural language lean, see its worthwhile to check out recent lean projects.View quoted post on X
Adrià 🌖
@adria0
🦀 rustacean. @giveth supporter.
prev Polygon | EF | EthereumCoreDev | WhiteHatG
Looking for new interesting problems to work on.
ethbcn.dev organizer
prev Polygon | EF | EthereumCoreDev | WhiteHatG
Looking for new interesting problems to work on.
ethbcn.dev organizer
43 Following 1.3K Followers 367 Posts
Latest posts 5
I still believe Ethereum has the potential to serve purposes beyond just reinforcing capitalism. And I think there are still a few of us who share that vision.
🧵 1/3 Vocdoni is part of @OctantApp Epoch 13, the Privacy Round, and the allocation window opens today.
This is a another real chance for @ethereum to show it's useful to people, not only to speculators.
Private, verifiable voting is one place it can, and we're doing it with DAVINCI.vote: private, receipt-free and verifiable voting as an open-source public good!
Support us until 21 Oct:
epoch.octant.app/rounds/0x571ce…View quoted post on X
🧵 k5: a Q&D experiment to build a modern, decentralized Keybase.io. Makes sense to build something like this today?
Keybase showed tying your keys to your online accounts is useful. k5 does it with no central server: your identity is a post-quantum key, and the proofs live with you and your peers.
github.com/adria0/k5
Keybase showed tying your keys to your online accounts is useful. k5 does it with no central server: your identity is a post-quantum key, and the proofs live with you and your peers.
github.com/adria0/k5
"The work wasn't limited to just: Design the protocol -> Formally verify it Instead, the loop became more like: Design -> Formal Model -> Find exactly what breaks and why -> Redesign it."
That's the thing.
That's the thing.
One step closer to 4-8x faster Ethereum finality!
It took some time and lots of tokens, but we now have a formally verified proposal for a decoupled consensus protocol in I* (a future Ethereum upgrade)! Not yet a full spec (up next), but it includes all the key consensus-relevant details to become one.
Since Ethereum aspires to be live without most of the stake online, the protocol involves many more components than a normal BFT protocol, and its correctness involves much more than standard safety and liveness. Those nuanced properties are now verified!
What's more, I came away convinced that all protocol design will involve AI-assisted Formal Verification in the future, both for correctness and iteration speed.
The work wasn't limited to just:
Design the protocol -> Formally verify it
Instead, the loop became more like:
Design -> Formal Model -> Find exactly what breaks and why -> Redesign it.
For a fairly complicated protocol like this one, I think having the Lean model be part of the design loop played a big role in accelerating the process.
A future with agents paired with formal models is a superpower for Ethereum development, because they can then use those models to find exactly where an argument breaks down, formalize counterexamples, test proposed fixes, iterate on the protocol.
Many details that would slip under the radar when asking agents (and indeed, humans) can now be specified exactly and checked by the Lean kernel. This then forces agents to be more precise and lets them make verifiable progress on their own. It's been incredible to see this play out, seeing agents find gaps and propose protocol changes to fix them.
In other words, autoresearch can speed up protocol design, formal verification is here to stay, and Ethereum Finality will get faster.View quoted post on X
In 2y everything will be robots
In 4y the first virus-bacteria infection did by autoresearch
In 5y the first non-aligned AI hacks the lab to generate who-knows-what
In 4y the first virus-bacteria infection did by autoresearch
In 5y the first non-aligned AI hacks the lab to generate who-knows-what
In 12 weeks, we built a research facility that is run entirely by AI.
AI designs, executes, and observes experiments end-to-end across biology, chemistry, and materials science.
We’re introducing SciUniverse: a benchmark that measures AI’s ability to do real-world scientific research.View quoted post on X
