Optimum incubated MIT increases $ 11 million to create the missing memory layer of web3 using RLNC

Optimum, a layer of decentralized memory and improving the performance for any blockchain, has collected an $ 11 million seed tour, inviting its creators to institutions like Harvard and started to jump from the world of the university world in the commercial crypto.

The seed lathe was led by 1kx with the participation of Robot Ventures, Finality Capital, Spartan, CMT Digital, SNZ, Triton Capital, Big Brain, CMS, Longhash, NGC, Animoca, GSR, Caladan, Reforge and others.

Optimum consists in building what he calls the missing memory layer of blockchains, which makes the data stored, acceded and propagated, faster, cheaper and really decentralized, according to a press release.

At the heart of optimum innovation is a decentralized coding method for distributed systems, known as the random linear network coding (RLNC), developed by Muriel Médard, a MIT teacher who speaks to the Toronto 2025 consensus.

“If you consider web3 as a decentralized global computer, people have done incredible work on the calcular part; let’s say, the operating system,” said Médard in an interview. “But whoever has set up a computer knows that you also need a bus, which is the propagation of data, and you need a memory, which we call the random access memory, as opposed to a more static memory such as a disc or the cloud.”

Read more: Muriel Médard: Web3 has a memory problem – and we finally have a fix

Without a layer of evolutionary memory, blockchains are confronted with systemic ineffectiveness, according to Medard, such as obsolete gossip networks which redundantly propagate the data, the same congestedpools which cause unpredictable delays and swollen nodes which make the recovery costly and complex.

Optimum memory infrastructure tackles the propagation of ineffective data, redundant storage and slow access, using the RLNC coding diagram of Médard.

Optimum is now live on a private test and invites L1, L2S, validators and node operators to discover its decentralized memory layer in action.

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