Wolfram Alpha teams up with Cardano to build ‘avant-garde oracles’
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Wolfram Alpha teams up with Cardano to build ‘avant-garde oracles’

Wolfram Alpha teams up with Cardano to build ‘avant-garde oracles’

Cardano is the next blockchain to integrate with the world’s largest answer engine in 2021.

Wolfram Alpha, a major computational knowledge engine providing technology for major services like Apple’s Siri assistant, is integrating data from Cardano blockchain.

According to a Dec. 17 announcement, Wolfram Blockchain Labs, or WBL, a subsidiary of Wolfram Research, has partnered with Charles Hoskinson-founded tech company, IOHK.

As part of the partnership, WBL will integrate Cardano’s blockchain data into Wolfram Alpha, allowing developers to integrate external data into Cardano’s smart contracts. The new partnership will specifically address work on the so-called “avant-garde oracles,” which the companies believe are a necessary component to build advanced smart contracts.

According to the announcement, WBL and IOHK will be rolling out the functionality in 2021, planning to release the integration later in the year.

Wolfram’s computational technology and knowledge base were previously integrated with major blockchain platforms including the Bitcoin blockchain and the Ethereum network. Other integrated platforms include ARK blockchain framework and Bloxberg, a major blockchain initiative led by the Max Planck Society.

Additionally, IOHK will be working closely with WBL to develop smart contract-based applications as part of a wider mission of enabling blockchain-based commerce and business model transformation. Following the partnership, WBL also plans to include some Cardano-specific content in its course material, allowing developers to learn how best to use Wolfram tools and oracles for Cardano.

Wolfram Alpha is a natural language processing tool and a provider to Apple’s Siri and Alexa intelligent assistants. Developed by Wolfram Research, Wolfram Alpha acts as the so-called “answer-engine,” providing answers to factual queries directly by computing the answer from structured data.

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