Cortex Develops New AI Network for Decentralized Apps

According to an official post made on June 26, the Cortex company has released a network for decentralized apps which is based on artificial intelligence (AI).

“Decentralized AI world computer, Cortex has announced the successful launch of its technology platform. The network, designed for AI-powered dApps, brings deep learning models as artificial intelligence support to the blockchain ecosystem. The Cortex mainnet, which launched on June 26th following 15 months of intense development, marks the first time that AI has been introduced to a crypto network at scale.”-read the press release.

The company has stated that this is the largest AI implementation on a crypto network to date. The technology is expected to be used for generating credit reports, facilitating anti-fraud reports for decentralized exchanges, P2P financing platforms, insurance, and cryptocurrency lending. Other use cases would be applied to gaming, esports, and AI governance structures.

The CEO of Cortex, Ziqi Chen explained how AI  can impact crypto networks:

“In the near future, we expect to see stablecoins based on machine learning, decentralized decision making, malicious behavior detection, smart resource allocation, and much more. These are challenges that all intersect with crypto networks, where having trained AI models that are accessible on-chain will prove to be extremely valuable.”

In the near future, Cortex says has plans for implementing AI dApps on its network, and to extend its on-chain machine learning feature to other networks than Ethereum.

“On-chain machine learning is an extremely complex endeavor due to the computational demands, and the need to create a virtual machine that is Ethereum Virtual Machine compatible. With the Cortex Virtual Machine, we’ve achieved a breakthrough that brings the benefits of artificial intelligence to a wider audience.

Although dApp developers will be among the first beneficiaries of the Cortex mainnet, this is only the beginning. In time, we expect to develop a diverse range of use cases, all delivered on-chain,” said Ziqi Chen.