Technical Updates 🤖

Machine-Learning(ML), CortexVirtual Machine(CVM)

1. ZKML optimizes ResNet model accuracy, improving accuracy by 14%

2. ZKML adjusts the Trace API and adds interfaces for data set binding, preprocessing, and postprocessing information.

3. ZKML completes the data set ImageNet, coco and other interfaces, and downloads more data sets

4. ZKML investigates ezkl, runs through the process and compares ZKML Circom benchmark performance

ZkRollup

1. Implementing the opcode of zkcvm

2. Try to implement the execution layer of zkcvm (modify consensus, block generation, smt, etc.)

3. Investigate and run through the new poseidon hash implementation and poseidon-hash circuit in halo2

4. Research and follow up on the latest zkevm development (cariovm, fuelvm, syncvm, midenvm)

5. OPCode that implements zkcvm

Cortex Full Node

1. core/rawdb: allocate database keys with explicit size to avoid slice

2. core: ensure txindex will be triggered at least once (#27847)

3. ignore genesis block on importChain

4. trie: reduce allocs in recHash (#27770)

5. all: update golang/x/ext and fix slice sorting fallout (#27909)

Community Updates👨‍👩‍👦‍👦

1. R&D on cross-chain bridge ecosystem;

2. Compiling the current ZKML project R&D report;

3. Collaboration with several NFT Artists;

4. Continue to monitor popular market ventures and examine project logic and Web3, NFT & Defi Tokenomic models

About Cortex 😇

Cortex’s main mission is to provide state-of-the-art machine-learning models on the blockchain in which users can infer using smart contracts on the Cortex blockchain. One of Cortex’s goals also includes implementing a machine-learning platform that allows users to post tasks on the platform, and submit AI DApps (Artificial Intelligence Decentralized Applications).

Cortex is the only public blockchain that allows the execution of nontrivial AI algorithms on the blockchain. MainNet has launched. Go build!

TestNet

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