Cardano founder Charles Hoskinson is one of the most prominent and influential people in the crypto community, as well as one of the wealthiest. Hoskinson took to Twitter to announce a whopping $20 million donation to establish a private research university in his name.
Located in Pittsburgh, Pennsylvania, the university is being named ‘Hoskinson Center for Formal Mathematics’ at Carnegie Mellon University. Hoskinson, who also happens to be the CEO of Input Output Global [IOG], is also a famous mathematician and has been in educating the masses about the nuances of the cryptocurrency industry and how it has the potential to transform the financial system globally. The exec hopes that the latest center at one of the world’s top 30 universities, will “rewrite the language of math.”
His tweet announcing the same read,
“The cats out of the bag. Today I got to announce the Hoskinson Center for Formal Mathematics at Carnegie Mellon University I donated 20 million dollars to create a permanent center to rewrite the language of math.”
Cardano’s Alonzo upgrade and beyond
The latest news comes on the heels of a successful Alonzo update on the third-largest blockchain platform in the world. The update paves the way for much anticipated and highly debated smart contract functionality, offering developers the ability to build apps that can employ the advanced capabilities of its blockchain. Hoskinson had previously stated that “decentralized finance [DeFi] is up for grabs” after the Alonzo hard fork earlier this month.
The Cardano ecosystem also aims to become Ethereum Virtual Machine-backwards-compatible in a bid to draw decentralized finance developers by providing lower transaction fees and a more efficient platform.
Following the Alonzo hard fork on the Cardano network, IOHK recently revealed the development of a layer-2 scaling solution for the network known as Hydra. It also introduces the concept of isomorphic state channels. The main objective of the scalability solution is to address all of the concerns about maximizing throughput, minimizing latency, incurring low to no costs, and significantly reducing storage requirements.