Dynex: The Neuromorphic Quantum Computing Cloud Solving Real-World Problems in AI, Quantum Computing, and Research

People are still trying to build a better blockchain and tailoring their networks to solve more up-to-date computing challenges. One of these is Dynex

Dynex is a blockchain that was launched in 2022. It is aiming to solve “real-world problems” in AI, quantum computing, and research. It is described by its developers as a “distinctive, adaptable blockchain system” and “the world’s only accessible neuromorphic quantum computing cloud.” It harnesses the parallel processing capacity of its GPU-based mining network.

A neuromorphic network, Mapp shares with CoinGeek Backstage, would process information along the same principles as the human brain.

“A neuromorphic network, in the simplest terms, is emulating the same way the human brain works. So when you’re looking at me, you’re seeing me, you’re hearing something around, you’re smelling—that is all parallel processing in your own brain. And we can simulate the same way that works on our chain,” he says.

Dynex processes transactions using a custom algorithm called “DynexSolve,” which combines regular proof-of-work (PoW) and a new concept Mapp calls the “proof of useful work” (PoUW) mechanism. The idea of PoUW is to make sure a portion of the computational resources of Dynex’s mining network are dedicated to solving practical problems. Those would include real-world scenarios in scientific research, AI training, pharmaceuticals, logistics, and financial modeling.

Its native token is also called Dynex or DNX. Miners receive DNX as a block reward for securing the network just as they do on other PoW blockchains, but also receive an additional subsidy for the “meaningful” computation described above. Mapp says that DynexSolve is a way of combining the two into one processing algorithm.

He adds that one pharmaceutical research application Dynex is looking at involves protein folding. A pharmaceutical company noticed they’d previously done RNA folding and RNA sequencing.

“I think we’re up to around 250 amino acid chains. The human body has around 300 in a protein string, so we’re almost fully at human level of protein folding right now. We suspect a couple more months, and we’ll have that fully nailed, and that’s going to open the door to all kinds of new research,” he explains.

LLMs (large language models) are a popular topic in technology, especially with ChatGPT and other similar projects gaining mainstream attention rapidly. Dynex LLM is the project’s home-grown model, and Mapp describes it as a “large behavioral model” based more on how a human mind thinks and learns.

A lot of Dynex’s work is still in the experimental realm, and its neuromorphic quantum computing concept utilizes ion drifting of electrons, which is different from superconducting qubit-based quantum computing in that it uses “memresistive elements that can quickly react to changes, helping the system swiftly find the best solutions.” It’s an alternative way to potentially achieve quantum computing advantages using the movement of ions within memresistors to change a device’s state.

This is just one computer science problem Dynex hopes to solve, and the team hopes for more breakthroughs.