Ala Shaabana is a Canada-based Co-founder of Bittensor, an open-source protocol that powers a decentralized, blockchain-based machine-learning network. ^[1][2]

Education

In 2006, Ala Shaabana enrolled at the University of Windsor. There he studied for a Bachelor of Science degree in Computer Science with a Software Engineering Specialization earned in 2011. From 2013 to 2017, he studied for his Ph.D. in Computer Science at the McMaster University. ^[1]

Career

Ala Shaabana started his career as a Software Developer at firmChannel from 2018 to 2013. In 2016, he served as an MTS Intern - Application Cloud Services at VMware, then moved to the role of a Software Engineer (R&D) in 2017. In August 2019, Ala became a Senior Software Engineer at Instacart and worked there until September 2020. ^[1]

From 2020, he was an Assistant Professor at the University of Toronto and a Postdoctoral Fellow at the University of Waterloo until December 2021. ^[1]

Bittensor

Ala Shaabana joined Bittensor as a Co-founder in December 2019 where he worked alongside Jacob Robert Steeves. Bittensor is a mining network, similar to Bitcoin that offers censorship-resistant access to a decentralized network of machine learning models. the protocol presents a strategy for the development and distribution of artificial intelligence 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]

The TAO token is Bittensor's native cryptocurrency, incentivizing AI technology development and distribution. It also grants external access, allowing users to extract information from the network while tuning its activities to their needs. It is used for governance, staking, and as a means of payment for accessing AI services and applications built on the Bittensor TAO network. ^[4][5]

"Bittensor's goal is to leverage blockchain technology to decentralize AI research and create a system where contributors are rewarded for building valuable models. The focus is on shifting away from the traditional emphasis on paper publication and fostering a decentralized approach to address challenges in the AI field" - Ala Shaabana in an interview with Towards Data Science^[6][7]