Machine-Learning(ML), CortexVirtual Machine(CVM)
The location and parameters of the logs interface in the design and test model quantification process
Fix bugs in zkml, and adjust and optimize the code
Implement the interface of image input_data to scale and round separately
After the model is converted to circom, modify input.json and set the input value
Resnet18 resnet34 resnet50 resnet101 resnet152 format converted successfully
Implement the js sdk that interacts with zkx netwrok: zkx.js.
Use handlebars to re-render the solidity code of single verifier and aggregate verifier
Add health check api to monitor the availability of database and web3 connections
Modify the process of price fetcher getting data from third-party api (coingecko, coinmarketcap...), add a validator to verify whether the token can be used for zkx network transaction fees
crypto/secp256k1: define NDEBUG only if not defined #1600
update leveldb metrics collection and track state changes in state db
database put in sync mode
common/lru: add test case for BasicLRU.Peek
core: log message if DeriveFields returns error
send big tx by announce only
make signature of ContractCode hash-independent
add cortex robot
R&D the current progress of ZKML;
R&D the technical progress of the current MPC wallet;
Collaboration with several NFT Artists
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!
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