읽기

편집

역사

알림

공유

Jacob Robert Steeves

Jacob Robert Steeves is a Peru-based Co-founder of , an open-source protocol that powers a decentralized, -based machine-learning network. [1][2][3]

Education

Jacob Robert Steeves attended Simon Fraser University where he studied for a Bachelor of Applied Science (BASc), Mathematics and Computer Science in 2011-2015. [2]

Career

Jacob Steeves started out as a Machine Learning Researcher at Knowm Inc. from 2015 to 2016. Afterward, he worked at Google as a Software Engineer from December 2016 to April 2018. [2]

Bittensor

In 2016, Jacob Steeves co-founded , a  network, similar to  that offers censorship-resistant access to a decentralized network of machine learning models. Bittensor presents a strategy for the development and distribution of  technology through the utilization of a distributed ledger. This involves aspects such as open access/ownership, decentralized governance, and the utilization of globally distributed computing resources within an incentivized framework. [1][3]

"Bittensor leverages the same innovation that brought us consensus on things like Bitcoin but brings it to what we're deeming the most important thing in this fourth Industrial Age that we're going through which is machine intelligence, machine knowledge" - Jacob Reeves explaining Bittensor[4]

utilizes the TAO token, its native  to incentivize AI technology development and distribution. TAO also grants external access, allowing users to extract information from the network while tuning its activities to their needs. It is used for governance, , and as a means of payment for accessing AI services and applications built on the Bittensor TAO network. [3][5][6]

"We're building a massive decentralized neural network that's aimed at better understanding the information in the world around us" - Jacob Reeves[4]

See something wrong? Report to us.

Jacob Robert Steeves

커밋 정보

편집자

편집 날짜

January 2, 2024

피드백

평균 평점

No ratings yet, be the first to rate!

경험은 어땠나요?

빠른 평가를 해서 우리에게 알려주세요!

트위터 타임라인

Loading...

로딩 중

미디어

참고 문헌.