AI watermarking schemes force a choice between public verification & private detection keys.
Nethermind Research introduces zkWM by @Cryptoni0x (Antonio Larriba), using SNARKs to prove watermark presence/absence without revealing detection mechanisms.
305-455ms prove+verify.
We're introducing a new benchmark for Ethereum clients.
It replays real mainnet blocks and merged super-blocks to measure real execution throughput.
Initial results show significant performance differences under heavy load, with 𝗡𝗲𝘁𝗵𝗲𝗿𝗺𝗶𝗻𝗱 𝗳𝗮𝘀𝘁𝗲𝘀𝘁 𝗮𝗺𝗼𝗻𝗴 𝗮𝗹𝗹.
🔗 https://t.co/ClMzawGH7H
@alrshirzad@0xAlbertG Hey @alrshirzad ! Thanks for your interest, this is a work in progress with a strong focus on correctness first (and only after the optimization tuning). Not yet recommended for production.
In anticipation of Starknet Version 0.13.2 arriving on mainnet tomorrow, the Voyager team is aligned with the rest of the Starknet ecosystem in closely monitoring the Sepolia stress test results 👀
To recap, in v0.13.2 Starknet introduces 2 main new features:
1⃣Parallel Execution
Now by processing transactions simultaneously, Starknet can execute multiple transactions at the exact same time, without waiting for each one to be completed individually.
2⃣Block Packing
Using the new SNAR tree data structure, each block is continuously merged at various levels of the data structure before being sent through SHARP (Starknet’s shared prover) and submitted to Ethereum for verification.
For a more in-depth recap, check out @Starknet’s post here:
https://t.co/z2U6nFo7rv
https://t.co/OVRrEh4m9a
Voyager team, standing by for Mainnet🫡🚀
https://t.co/IiVgDFxVCM
TEE? ZKP? MPC? FHE?
Everything you need to know about the most important three letter acronyms in crypto
Or, how you win friends and TEE-fluence people 🧵
I just published Liquidation Bot on @zkLend (@Starknet ) Part 3— We're almost at the end of the series.
Join the TG channel for more content (link in the medium post)
https://t.co/cdPoDYlJXB
I have just released the second part of the guide on Performing Liquidations on @StarkNet (@zkLend ). This section focuses on calculating debt and collateral amounts and identifying potential liquidation opportunities.
@starknetjs
https://t.co/AAGif0a3Tg
Based rollups are great, but something is lost when we add preconfirmations. Our latest post explores a based preconfirmation design that piggybacks the L1 PBS pipeline, avoiding many of the negative externalities of preconfs as a result. https://t.co/plJzfclVlo
I can see there's little information online about developing MEV tools on @Starknet. I am putting together a series of guides on this topic, the first release of the liquidation bot on @zkLend is here:
https://t.co/sTdNmYK5oJ