Gensyn AI raises $43M for decentralized machine learning led by a16z

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Gensyn AI, a UK-based decentralized machine learning compute protocol, has raised $43 million in Series A funding led by a16z crypto. The funding will be used to expand the Gensyn AI team and production costs, including a test network launch later this year. Gensyn AI aims to empower developers to create AI tools on a pay-as-you-go model. The idea is to connect all of the machine learning capable compute hardware in the world that is capable of doing machine learning training work — including GPUs and CPUs — and make it accessible to engineers, researchers, and academics. Gensyn is a layer one proof-of-stake blockchain based on the Substripe protocol, which is unlimited in scale and super low cost in terms of verification overhead.

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Frequently Asked Questions (FAQs) Related to the Above News

What is Gensyn AI?

Gensyn AI is a decentralized machine learning compute protocol that aims to connect all machine learning capable compute hardware in the world and make it accessible to developers on a pay-as-you-go model.

How much funding has Gensyn AI raised in Series A funding?

Gensyn AI has raised $43 million in Series A funding led by a16z crypto.

What will Gensyn AI use the funding for?

Gensyn AI will use the funding to expand its team and production costs, including a test network launch later in the year.

What kind of blockchain is Gensyn AI based on?

Gensyn AI is based on a layer one proof-of-stake blockchain called the Substripe protocol, which is unlimited in scale and super low cost in terms of verification overhead.

Who will benefit from Gensyn AI?

Engineers, researchers, and academics who want to create AI tools on a pay-as-you-go model will benefit from Gensyn AI.

Please note that the FAQs provided on this page are based on the news article published. While we strive to provide accurate and up-to-date information, it is always recommended to consult relevant authorities or professionals before making any decisions or taking action based on the FAQs or the news article.

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