Machine-Learning(ML), CortexVirtual Machine(CVM) & Model RepresentationTool(MRT) R&D
MRT/CVM
MRT updated the accuracy test code, adjusted and tested the model output results of the sampling data
Adjust the parameter setting of Calibrate Pass: absmax, fix the problem of FuseBatchnorm
Refactored the Quantiza Pass code and fixed the Infer Precision issue
Fixed the FixPoint Infer Type problem and added subgraph verification function
The model parameters are adjusted to Int8, which reduces the model size
CVM encapsulates the operator interface code and completes the test code
ZkRollup
Fixed the error that ZK for ETHF could not submit proofs to the chain, Chain ID Error
Zion reference implements the Rust version to speed up transaction execution
Implemented Poseidon hash, babyjubjub, benchmark and pubkey compression algorithms
Cortex Full Node
core: reset txpool on sethead
implement resettable freezer
fix tracer crash due to balance nil
return proper error from debug_TraceTransaction
Cortex Wallet (NFT Gallery) test;
Cortex Christmas NFT Giveaway;
NFT community point system planning & research;
Continue to monitor popular market ventures and examine project logic and Web3, NFT & GameFi 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
| Block Explorer — Cerebro| Mining Pool | Remix Editor | Software | ZkMatrix
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