Quick take:
- Optimum offers a chain-agnostic a decentralised, performance-enhancing memory layer.
- The platform ensures that the way blockchain data is stored, accessed and propagated is faster, cheaper and truly decentralised.
- Optimum leverages an innovative method of decentralised coding dubbed Random Linear Network Coding (RLNC), developed by MIT professor Muriel Médard.
Optimum, a chain-agnostic memory layer incubated by MIT, has raised $11 million in a seed round led by 1kx. The fundraising also attracted participation from Robot Ventures, Finality Capital, Spartan, CMT Digital, SNZ, Triton Capital, Big Brain, CMS, Longhash, NGC, Animoca, GSR, Caladan, Reforge and others.
Optimum offers a decentralised, performance-enhancing memory layer for all blockchains. According to the announcement, the layer ensures that the way blockchain data is stored, accessed and propagated is faster, cheaper and truly decentralised.
The platform leverages an innovative method of decentralised coding dubbed Random Linear Network Coding (RLNC), developed by MIT professor Muriel Médard.
Explaining the important role Optimm plays in the crypto ecosystem, Médard said in an interview: “If you think of Web3 as a decentralised world computer, people have done an amazing job on the compute part; let’s say, the operating system. But anybody who’s put together a computer knows that you also need a bus, which is the data propagation, and you need a memory, which we call the random access memory, as opposed to more static memory like a disk or the cloud.”
According to Médard, some of the systemic inefficiencies that Optimim seeks to address with the RLNC coding scheme include outdated gossip networks that redundantly propagate data, congested memepools that cause unpredictable delays and bloated nodes that make retrieval costly and complex.
The platform is now live on private testnet and is inviting Layer-1s, Layer-2s, validators and node operators for the testing phase of its decentralised memory layer.
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