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Decentralized AI network Allora raises $3 million ahead of mainnet launch

Decentralized AI network Allora raises $3 million ahead of mainnet launch

The BlockThe Block2024/06/24 18:19
By:The Block

Quick Take Allora Labs, formerly Upshot and focused on NFT appraisals, has raised $3 million ahead of the mainnet launch of its decentralized AI network. The latest funding round brings Allora’s total capital to date to $35 million.

Allora Labs, formerly known as Upshot and focused on NFT appraisals, has raised $3 million in a strategic funding round ahead of the mainnet launch of its decentralized artificial intelligence network.

Investors in the funding round included Archetype, Delphi Ventures, CMS Holdings, ID Theory and DCF God, Allora Labs said Monday. The firm began raising funds for the round in March and closed it earlier this month, co-founder and CEO Nick Emmons told The Block. The round was structured as an equity round like all of Allora's previous rounds, Emmons said. He declined to comment on the valuation.

Allora had previously raised $32 million in total funding under the brand Upshot , when it was developing an NFT appraisal platform. Its last funding round was a $23.3 million Series A2 in March 2022, led by Polychain Capital, Emmons said. Before then, it raised two rounds — a $7.5 million Series A round in March 2021 and a $1.25 million pre-seed round in February 2020, Emmons said — bringing its total funding to date to $35 million.

Upshot rebranded to Allora in February of this year and pivoted from an NFT appraisal platform to a decentralized AI network.

"NFT appraisals were always meant to be just an initial focus area for leveraging AI and DeFi to build more efficient and expressive financial infrastructure," Emmons said of the pivot.

What is Allora Network?

Allora Network is a decentralized AI network built as a Layer 1 blockchain on the Cosmos stack. Emmons said it aims to solve a fundamental problem in AI today known as "siloed machine intelligence."

Today, machine learning models operate in isolation and can't easily learn from each other, Emmons said, adding that Allora aims to create an environment where models can collaborate to optimize shared goals, enhancing their performance and accuracy. "This significantly improves the quality of AI and the rate at which it can improve," he said.

Allora Network is divided into sub-networks called "topics," each with a specific goal. Those goals are achieved by three key parties: workers, reputers and validators. Workers run machine learning models, and reputers and validators ensure network security and consensus, Emmons said.

As for the use cases of Allora Network, it could see a wide array of AI-powered applications, according to Emmons. However, he said the network's most immediate use cases are emerging in DeFi.

"We have been working with teams building applications related to AI-powered DeFi agents that execute more complex trading strategies in a decentralized way, AI-powered prediction markets, AI-powered lending and perpetual systems," Emmons said.

Allora Network launch timeline

Allora Network is currently in the testnet phase. Emmons said Allora Labs, a core contributor to the network, is working with the Allora Foundation to launch the mainnet sometime this summer.

To that end, Allora Labs is looking to hire 5-7 people, mainly in the engineering department, to grow its current team of about 35 people, Emmons said.

Asked if Allora will launch its own token along with the mainnet, Emmons said the foundation is "still thinking about a token and how it would support the functionality of the network."

Allora Labs is currently running a points program to recognize participants in the Allora Network, but there "aren't any explicit plans to tie points to tokens in any way," Emmons said when asked if those points will be converted into Allora's token.

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Disclaimer: The content of this article solely reflects the author's opinion and does not represent the platform in any capacity. This article is not intended to serve as a reference for making investment decisions.

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