Machine-Learning(ML), CortexVirtual Machine(CVM)
ZKML adds TVM Runtime Inference reasoning simulation test quantized accuracy, and debugs the loss of accuracy;
ZKML adjusts the data set mount interface and output result analysis class;
ZKML adjusts the restore logic of the quantitative model output results;
Fix the problem of input_data not passing mrt transformer in model2circom;
ZKML adjusts the data set mount, and increases the data set input in the calibrated pass to improve the quantization accuracy;
Requantize bit digit adjustment, binary operators such as add/sub/mul/div are adjusted to 30/31, 16/16;
Implement zkx-crypto (signature, verification, hash, etc.) related functions to wasm through Binaryen and wasm-pack;
Add batch tx, including processing it in mempool, statekeeper;
Realize batch fee calculation, add batch tx-related api interface and fix fee calculation problem;
The tx submitted in the Forced exit request is changed to batch tx to ensure success or failure at the same time;
Create the schema of the entire database and create the corresponding index (sqlx migration);
NFT Gallery Powered by Cortex is now available
Collaboration with several NFT Artists
Continue to monitor popular market ventures and examine project logic and Web3, NFT & Defi Tokenomic models
Working with Ledger integrations
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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