Optimum, a decentralized, performance-enhancing reminiscence layer for any blockchain, raised an $11 million seed spherical, inviting its creators from establishments like Harvard and MIT to leap from the world of academia into the business crypto enviornment.
The seed spherical was led by 1kx with participation from Robotic Ventures, Finality Capital, Spartan, CMT Digital, SNZ, Triton Capital, Large Mind, CMS, Longhash, NGC, Animoca, GSR, Caladan, Reforge and others.
Optimum is constructing what it calls the lacking reminiscence layer of blockchains, making the way in which information is saved, accessed and propagated, sooner, cheaper and really decentralized, in line with a press launch.
On the core of Optimum’s innovation is a technique of decentralized coding for distributed techniques, generally known as Random Linear Community Coding (RLNC), developed by Muriel Médard, an MIT professor who’s talking at Consensus Toronto 2025.
“In case you consider Web3 as a decentralized world laptop, folks have carried out an incredible job on the compute half; for example, the working system,” Médard stated in an interview. “However anyone who’s put collectively a pc is aware of that you simply additionally want a bus, which is the info propagation, and also you want a reminiscence, which we name the random entry reminiscence, versus extra static reminiscence like a disk or the cloud.”
And not using a scalable reminiscence layer, blockchains face systemic inefficiencies, in line with Médard, reminiscent of outdated gossip networks that redundantly propagate information, congested memepools that trigger unpredictable delays and bloated nodes that make retrieval expensive and complicated.
Optimum’s reminiscence infrastructure tackles inefficient information propagation, redundant storage and sluggish entry, utilizing Médard’s RLNC coding scheme.
Optimum is now dwell on a non-public testnet and is inviting L1s, L2s, validators and node operators to expertise its decentralized reminiscence layer in motion.
