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## What is Cortex?
Cortex represents a groundbreaking development in blockchain technology, positioning itself as the first public blockchain capable of executing AI algorithms and [AI DApps](https://coinrotator.app/coin/fetch-ai) directly on the blockchain. By providing an AI platform for developers to seamlessly upload their models into smart contracts, Cortex moves beyond the limitations of traditional off-chain inference, ensuring a decentralized, immutable, and transparent execution of AI models. Launched in June 2019, Cortex's MainNet has since facilitated the integration of AI into smart contracts through its innovative approach.

Cortex At a Glance:
- Cortex Virtual Machine (CVM): EVM-compatible with added GPU support for on-chain AI inference.
- AI Inference Engine - Synapse: A deterministic inference engine ensuring consistent results across diverse computing environments.
- AI Smart Contract and AI DApp: Cortex integrates machine learning into smart contracts and DApps, allowing developers to use Solidity and off-the-shelf AI models for enhanced applications.
- Decentralizing AI Research: Cortex fosters an open-source ecosystem, incentivizing AI researchers and developers to share their models, promoting collaboration and innovation.

## How does Cortex Enable On-Chain AI?
The execution of AI models on the blockchain was a formidable challenge until Cortex devised its innovative solutions. By developing a blockchain with a virtual machine utilizing GPU and implementing a quantization scheme for deterministic execution, Cortex successfully overcame the obstacles that hindered AI inference on traditional blockchains. Simulated quantization and integer-only inference not only eliminated nondeterministic behaviors of deep learning models but also accelerated their inference, making the execution of non-trivial AI models on the blockchain feasible.

## Cost Effective
Contrary to expectations, Cortex, with its Cortex Virtual Machine (CVM) and quantization method, has made running AI on the blockchain both cost-effective and practical. The transaction fees remain extremely low, especially during less congested network periods, demonstrating the efficiency and affordability of the Cortex platform.

## Comparisons to Ethereum
Cortex's approach stands out by introducing a virtual machine that runs on the GPU, a significant departure from conventional blockchains like Ethereum, which rely on CPU-based virtual machines. This fundamental difference allows Cortex to execute non-trivial AI models directly on the blockchain, achieving true AI smart contracts. Moreover, the Cortex Virtual Machine (CVM) is backward-compatible with the Ethereum Virtual Machine (EVM), facilitating a seamless migration for Ethereum developers to incorporate AI models into their applications on the Cortex blockchain.

## Launching ZkMatrix - Layer2 ZkRollup Solution
ZkMatrix, a Layer2 Solution on the Cortex Blockchain, leverages zkRollup technology to aggregate batch transitions on the side chain into a single transaction on the main chain. This innovation aims to enhance transaction per second (TPS) and significantly reduce the Endorphin fee associated with each transaction. ZkMatrix inherits security and consensus features from the main chain while focusing on optimizing transaction performance, providing a promising solution for scaling the Cortex ecosystem.

## AI on Blockchain Ecosystem
Cortex's open-source, decentralized blockchain democratizes AI by offering a platform where AI models can be easily integrated into smart contracts, fostering an environment where individual developers contribute to a diverse and competitive ecosystem. This approach stands in stark contrast to the inefficiencies of traditional blockchains in running nontrivial machine learning models.

## Partners
Cortex's Technical & Academic Partners: CRRC, CMET, Amazon, MXNet, Poseidon Network, Tsinghua University, and Leland Stanford Junior University.

## Project Development

In recent technical updates for Cortex, the MRT (Model Runtime) and CVM (Cortex Virtual Machine) components have seen significant enhancements. MRT now supports detection models, implementing quantization for models like Yolo and SSD. The addition of an automatic Spliter/Merger algorithm addresses duplicate issues in segmented subgraphs, with constant pass fusion for operators like oneslike and zeroslike. 

Furthermore, operators such as shape of, reverse, maximum, and minimum have gained adaptation and quantization logic. Circom has been adapted for the detection model, incorporating operators like slice_like, repeat, and tile. Ongoing research on OPML technology explores additional possibilities for on-chain AI inference. In the ZkRollup domain, efforts include bytecode compression for reduced on-chain data consumption, the introduction of StorageProcessor for PostgreSQL database access, and the implementation of a persistent storage layer based on the database, utilizing RocksDB for enhanced execution speed. 

Various improvements, such as abstracting StorageView and addressing issues in Metric exporter and job processor, contribute to a more efficient and robust Cortex ecosystem. The Cortex Full Node also undergoes updates, incorporating linter adjustments, liveness checks, and consensus test enhancements for improved performance.






## {{name}} Price Analysis

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