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@m7x2020

Pharmacist | Crypto enthusiast | Educator & Community Growth Advocate |

Egypt Katılım Nisan 2022
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Mesrega
Mesrega@m7x2020·
Most blockchain upgrades require major changes like new protocols, clients, or hard forks which slow adoption. @get_optimum takes a different approach. It works as a plug-in layer that enhances existing systems instead of replacing them. Using mump2p, it can be integrated without changing the consensus client. CC: @blockchainjeff @tgogayi @cryptooflashh
Mesrega@m7x2020

Most blockchains focus on processing speed, but ignore how data actually moves across the network. The real problem is that blocks and transactions propagate slowly, redundantly, and inconsistently between nodes, leading to delayed confirmations, higher fork probability, and reduced overall efficiency. @get_optimum solves this at the root by focusing on data propagation itself. Through its networking layer mump2p, powered by RLNC, it replaces repetitive transmissions with smarter, encoded data exchange. The result is faster propagation, lower latency, and better synchronization across nodes. Optimum doesn’t just make blockchains faster it makes them coordinated, which is what truly keeps decentralized systems working. CC: @blockchainjeff @tgogayi @cryptooflashh

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Mesrega
Mesrega@m7x2020·
gMum I also agree that too much of the current conversation focuses only on reinforcing the lock (KEMs/signatures) while ignoring scalability and deployability across real world systems. That said, I think the quantum attacker punching through anywhere in the door analogy may overstate the current threat model a bit. Quantum advantage today is still tied to specific mathematical structures rather than arbitrary non-deterministic access to encrypted payloads. McEliece absolutely deserves more respect than it currently gets though. Its longevity under cryptanalysis is hard to ignore. The HUNCC direction is interesting because it shifts the discussion from how do we replace classical crypto primitives? to how do we distribute protection efficiently across data systems without unbearable overhead? Coming from the pharmaceutical manufacturing and quality field, the analogy actually reminds me a lot of contamination control and process robustness. In pharma, strengthening only one checkpoint is never enough. You can have a perfect final inspection, but if the process itself is fragile, contamination or variability can still appear anywhere across the production chain. That’s why robust systems are built around layered protection, redundancy, monitoring, and process-wide resilience rather than trusting a single control point. @get_optimum particularly interesting to me. Because the use of RLNC and network coding is not just about speed, but about building infrastructure that is more resilient and efficient at the network level itself, especially across large-scale decentralized environments.
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Muriel Medard@MurielMedard

Many people talk about quantum (PQ) computing like it's mystical. It isn't. It's math. The way we will secure data against it is also math, specifically, coding theory. Let me explain what that means, because much of the current PQ conversation is missing some important context. ​ Quantum computers work on qubits rather than bits. A bit is 0 or 1. A qubit can be described as something that can be 0, 1, or a distribution between them. That extra room is where the power comes from: a quantum computer is probabilistic, not deterministic, and it can solve specific problems that today's machines cannot. ​ The challenge is that as you compute, the qubits degrade. The state doesn't stay constant. Without robust, efficient error correction, a quantum computer can't scale. Error correction is a coding problem. So coding is one of the largest open obstacles to making quantum computing real at all, which is why so much of the heavy investment in this space is, at its core, an investment in better codes. ​ That same math is what protects us on the other side. To see why, the analogy I keep coming back to is a door and a lock. Every cryptosystem you use today protects a large surface (say a megabit of data) with a tiny key, say 128 or 256 bits. The lock is a small fraction of the door. That arrangement works against a classical attacker because they have to break the lock; there's no other way in. ​ A quantum attacker doesn't have that constraint. They can probe non-deterministically; they don't need to break the lock at all. They can look for a weak point anywhere on the surface of the door and punch a hole through it. You may not even know which part of your data they saw, maybe nothing important, maybe exactly what you wanted to hide. ​ Almost the entire PQ conversation today is about reinforcing the lock. Replace ECDSA, replace the key-exchange primitive, swap in a lattice-based KEM. That work matters and it should continue. But it is still a small reinforced patch on a very large door. ​ The real question is how you reinforce the whole door. The math for that has existed since the 1970s: the McEliece cryptosystem, the granddaddy of post-quantum schemes, and the main one I personally trust. It has withstood half a century of attacks by cryptographers without a fundamental break—a track record little else in this space comes close to. ​ The problem with McEliece is not security. It is pain. Applying it to a full payload is, if you forgive the grim comparison, like chemo: it kills the tumor and almost kills the patient. That is why nobody deploys it broadly. The lock is small enough to absorb the cost; the door is not. ​ This is where coding solves the second half of the problem. The construction my collaborators and I developed, HUNCC (Hybrid Universal Network Coding Cryptosystem), splits the data into coded pieces and applies the expensive PQ encryption to only a small fraction of them, maybe a few percent, or less. An attacker who breaks in sees a system of equations with one unknown they cannot recover. One unknown in a coded system is a hyper-strong key, and the protection lives everywhere on the data, not just at the lock. ​ The point is not that this replaces ML-KEM or any other PQ KEM. It doesn't, and I wouldn't claim it does. The point is that coding is what makes post-quantum security something you can actually deploy at speed, across the whole door, without paying the chemo cost everywhere. ​ Coding is what is currently blocking quantum computing from becoming real, and coding is what will make quantum safety real. The math has been here for fifty years. What we have been missing is the path from correct-but-unusable to correct-and-fast. ​ More to come.

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Alola (∇, ∇) ♦️(real-time oracle)
Built for the Onchain Future The internet is entering a fully onchain era. Stablecoins are evolving into the default settlement infrastructure. Tokenized assets are transforming markets into programmable financial systems. Autonomous agents are beginning to transact, coordinate, and execute value onchain in real time. But none of this can truly scale if the underlying network layer remains slow. That’s where projects like @get_optimum come in focusing on the overlooked infrastructure layer: high-performance decentralized networking built for fast data propagation, ultra-low latency, and scalable coordination across onchain ecosystems. Because when billions of transactions, AI-driven interactions, and tokenized assets move simultaneously, the network itself becomes the bottleneck. The future demands: → Faster propagation → Lower latency → Stronger decentralized coordination → Infrastructure designed for massive onchain scale Speed is no longer just an advantage. It becomes infrastructure. And infrastructure becomes power.
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Mesrega
Mesrega@m7x2020·
@ada_pegasus Check this 👀
Mesrega@m7x2020

gMum I also agree that too much of the current conversation focuses only on reinforcing the lock (KEMs/signatures) while ignoring scalability and deployability across real world systems. That said, I think the quantum attacker punching through anywhere in the door analogy may overstate the current threat model a bit. Quantum advantage today is still tied to specific mathematical structures rather than arbitrary non-deterministic access to encrypted payloads. McEliece absolutely deserves more respect than it currently gets though. Its longevity under cryptanalysis is hard to ignore. The HUNCC direction is interesting because it shifts the discussion from how do we replace classical crypto primitives? to how do we distribute protection efficiently across data systems without unbearable overhead? Coming from the pharmaceutical manufacturing and quality field, the analogy actually reminds me a lot of contamination control and process robustness. In pharma, strengthening only one checkpoint is never enough. You can have a perfect final inspection, but if the process itself is fragile, contamination or variability can still appear anywhere across the production chain. That’s why robust systems are built around layered protection, redundancy, monitoring, and process-wide resilience rather than trusting a single control point. @get_optimum particularly interesting to me. Because the use of RLNC and network coding is not just about speed, but about building infrastructure that is more resilient and efficient at the network level itself, especially across large-scale decentralized environments.

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Pegasus
Pegasus@ada_pegasus·
🖥️The quantum threat in crypto is like worrying about an asteroid impact: the danger is real and would be catastrophic, but the timeline and mechanics are heavily overhyped. 🌊Looking at the current state of hardware development, the short answer is simple: ❌Short term: No need to panic ✅Long-term: Preparation is non-negotiable. ----- 🤔Let’s be realistic about incentives. The crypto market is not where a nation-state or an entity with a multi-billion-dollar quantum computer will strike first. There are far bigger fish to fry. 📍Legacy banking infrastructure 📍National defense systems 📍Global intelligence grids ... hold vastly higher strategic value and rewards than cracking private keys. ----- ❓How do we prepare? By understanding that quantum security isn’t magic - it’s pure mathematics and coding theory. As Professor @MurielMedard pointed out, coding is both the bottleneck holding quantum computers back (quantum error correction) and the shield protecting us from them. ♾ This is exactly why @get_optimum is ahead of the curve. By leveraging Random Linear Network Coding (RLNC), we aren't just solving data propagation and scaling bottlenecks for today's decentralized webs, we are fundamentally mastering the exact domain - coding theory - that defines post-quantum resilience. ----- The future of blockchain security isn't about running away from quantum, it's about building on superior coding architecture from day one.
Muriel Medard@MurielMedard

Many people talk about quantum (PQ) computing like it's mystical. It isn't. It's math. The way we will secure data against it is also math, specifically, coding theory. Let me explain what that means, because much of the current PQ conversation is missing some important context. ​ Quantum computers work on qubits rather than bits. A bit is 0 or 1. A qubit can be described as something that can be 0, 1, or a distribution between them. That extra room is where the power comes from: a quantum computer is probabilistic, not deterministic, and it can solve specific problems that today's machines cannot. ​ The challenge is that as you compute, the qubits degrade. The state doesn't stay constant. Without robust, efficient error correction, a quantum computer can't scale. Error correction is a coding problem. So coding is one of the largest open obstacles to making quantum computing real at all, which is why so much of the heavy investment in this space is, at its core, an investment in better codes. ​ That same math is what protects us on the other side. To see why, the analogy I keep coming back to is a door and a lock. Every cryptosystem you use today protects a large surface (say a megabit of data) with a tiny key, say 128 or 256 bits. The lock is a small fraction of the door. That arrangement works against a classical attacker because they have to break the lock; there's no other way in. ​ A quantum attacker doesn't have that constraint. They can probe non-deterministically; they don't need to break the lock at all. They can look for a weak point anywhere on the surface of the door and punch a hole through it. You may not even know which part of your data they saw, maybe nothing important, maybe exactly what you wanted to hide. ​ Almost the entire PQ conversation today is about reinforcing the lock. Replace ECDSA, replace the key-exchange primitive, swap in a lattice-based KEM. That work matters and it should continue. But it is still a small reinforced patch on a very large door. ​ The real question is how you reinforce the whole door. The math for that has existed since the 1970s: the McEliece cryptosystem, the granddaddy of post-quantum schemes, and the main one I personally trust. It has withstood half a century of attacks by cryptographers without a fundamental break—a track record little else in this space comes close to. ​ The problem with McEliece is not security. It is pain. Applying it to a full payload is, if you forgive the grim comparison, like chemo: it kills the tumor and almost kills the patient. That is why nobody deploys it broadly. The lock is small enough to absorb the cost; the door is not. ​ This is where coding solves the second half of the problem. The construction my collaborators and I developed, HUNCC (Hybrid Universal Network Coding Cryptosystem), splits the data into coded pieces and applies the expensive PQ encryption to only a small fraction of them, maybe a few percent, or less. An attacker who breaks in sees a system of equations with one unknown they cannot recover. One unknown in a coded system is a hyper-strong key, and the protection lives everywhere on the data, not just at the lock. ​ The point is not that this replaces ML-KEM or any other PQ KEM. It doesn't, and I wouldn't claim it does. The point is that coding is what makes post-quantum security something you can actually deploy at speed, across the whole door, without paying the chemo cost everywhere. ​ Coding is what is currently blocking quantum computing from becoming real, and coding is what will make quantum safety real. The math has been here for fifty years. What we have been missing is the path from correct-but-unusable to correct-and-fast. ​ More to come.

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TheBlockBoy
TheBlockBoy@TheBl0ckBoy·
Do I need to write anything about this shit?
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Mesrega
Mesrega@m7x2020·
Optimum and the Future of Modular Networking Web3 is becoming modular. Execution, storage, and networking are separating into specialized layers. This evolution changes how infrastructure is designed. @get_optimum fits directly into the networking layer. Its role is not execution. Its role is not consensus. Its role is movement. Specifically: moving data faster, more efficiently, and more reliably across distributed systems. And this specialization matters. Because execution layers are only as strong as the communication layer beneath them. Optimum strengthens that layer. This improves the performance of everything built above it. In a modular future, networking becomes critical infrastructure. And Optimum is positioning itself at the center of that shift. CC: @blockchainjeff @tgogayi @@aqccapital
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Mesrega@m7x2020

Why RLNC Outperforms Traditional Erasure Codes Not all coding systems are equal. Many networks already use erasure coding methods like Reed–Solomon. But RLNC introduces something more powerful: recoding. A node can generate entirely new coded shards from the shards it already has without waiting for full reconstruction. This enables continuous propagation. And continuous propagation reduces latency dramatically. @get_optimum argues that RLNC outperforms traditional approaches in large distributed systems because it combines: • flexibility • resilience • propagation efficiency This is why RLNC is at the center of Optimum’s architecture. Not as a marketing term. But as the actual mechanism driving performance gains. Cc: @blockchainjeff @tgogayi

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Mesrega
Mesrega@m7x2020·
gMum💥 Back then, whenever a project said we’re decentralized, it usually meant one thing: the network would be slower. @get_optimum flipped that idea completely. Instead of more nodes creating congestion and delays, mump2p + RLNC turn every new node into an advantage for the network itself. In simple terms: An independent node operator running from home in Asia or Africa can achieve propagation speeds close to large enterprise operators with expensive infrastructure in Europe or North America. And that’s a massive shift. Because traditional networks mostly depend on: - Server location - Hardware strength - Proximity to data centers But here? Every node actively helps distribute, recode, and reconstruct data more efficiently. So the result becomes: - Global distribution turns into an advantage - More nodes actually improve speed - Decentralization strengthens performance instead of hurting it That’s why Optimum feels different from typical networking projects. They’re not just optimizing propagation. They’re redefining how propagation works. @blockchainjeff @tgogayi @cryptooflashh
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Optimum@get_optimum

Everyone thinks decentralized = slow. We're proving them wrong. Powered by Random Linear Network Coding, Optimum's mump2p improves network decentralization. When every node has access to low latency data propagation, it matters much less where that node is located or what hardware it runs on. By simply running mump2p, an independent node operator in Asia or South America can close the performance gap with enterprise operators in Western Europe or North America. Decentralization innately supports network resilience, censorship resistance, and attack resistance. When a network communicates using RLNC that 𝐝𝐞𝐜𝐞𝐧𝐭𝐫𝐚𝐥𝐢𝐳𝐚𝐭𝐢𝐨𝐧 𝐚𝐜𝐭𝐮𝐚𝐥𝐥𝐲 𝐡𝐞𝐥𝐩𝐬 𝐬𝐩𝐞𝐞𝐝 𝐮𝐩 𝐭𝐡𝐞 𝐧𝐞𝐭𝐰𝐨𝐫𝐤 too. Because of RLNC’s fundamental properties: - Recoding - Early forwarding - Decoding with any combination of coded shards it thrives in massive globally distributed networks, whereas other propagation methods slow down. Every new node adds more coded shards to the network, so decoding gets faster. More nodes in more diverse regions shortens the hops between them, so latency drops. This is how Optimum lets chains decentralize to scale.

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NOMAN
NOMAN@Nomiie143·
GM One thing I really like about @get_optimum is how they challenge the old idea that decentralization has to be slow Most projects talk about scaling Optimum is actually exploring ways to make globally distributed networks faster and more efficient through RLNC and better data propagation More nodes should strengthen a network not slow it down 🩶
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Optimum@get_optimum

Everyone thinks decentralized = slow. We're proving them wrong. Powered by Random Linear Network Coding, Optimum's mump2p improves network decentralization. When every node has access to low latency data propagation, it matters much less where that node is located or what hardware it runs on. By simply running mump2p, an independent node operator in Asia or South America can close the performance gap with enterprise operators in Western Europe or North America. Decentralization innately supports network resilience, censorship resistance, and attack resistance. When a network communicates using RLNC that 𝐝𝐞𝐜𝐞𝐧𝐭𝐫𝐚𝐥𝐢𝐳𝐚𝐭𝐢𝐨𝐧 𝐚𝐜𝐭𝐮𝐚𝐥𝐥𝐲 𝐡𝐞𝐥𝐩𝐬 𝐬𝐩𝐞𝐞𝐝 𝐮𝐩 𝐭𝐡𝐞 𝐧𝐞𝐭𝐰𝐨𝐫𝐤 too. Because of RLNC’s fundamental properties: - Recoding - Early forwarding - Decoding with any combination of coded shards it thrives in massive globally distributed networks, whereas other propagation methods slow down. Every new node adds more coded shards to the network, so decoding gets faster. More nodes in more diverse regions shortens the hops between them, so latency drops. This is how Optimum lets chains decentralize to scale.

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MR.KEN🌎
MR.KEN🌎@MrKen40·
You can optimize execution all you want but if your P2P layer is slow none of it matters, think about this,the p2p layer is where data are gotten from for execution to be made possible if these data arrives slower then expect a slower result at the end is inevitable....
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pigeon99 🕊🕊
pigeon99 🕊🕊@9pigeon9·
Everyone thinks decentralized = slow. Optimum is proving them wrong in the most elegant way possible. @get_optimum With mump2p powered by Random Linear Network Coding (RLNC), decentralization actually becomes an advantage for speed. Here’s why: Every new node adds more coded shards to the network RLNC’s recoding + early forwarding + any-combination decoding properties thrive in globally distributed environments More nodes in more diverse regions = shorter hops + lower latency Result? An independent node operator in Asia or South America running mump2p can now close the performance gap with big enterprise operators in Western Europe or North America. Decentralization no longer trades off speed it becomes the reason the network gets faster, more resilient, censorship-resistant, and attack-resistant at the same time. This is how Optimum lets chains decentralize to scale.
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Optimum@get_optimum

Everyone thinks decentralized = slow. We're proving them wrong. Powered by Random Linear Network Coding, Optimum's mump2p improves network decentralization. When every node has access to low latency data propagation, it matters much less where that node is located or what hardware it runs on. By simply running mump2p, an independent node operator in Asia or South America can close the performance gap with enterprise operators in Western Europe or North America. Decentralization innately supports network resilience, censorship resistance, and attack resistance. When a network communicates using RLNC that 𝐝𝐞𝐜𝐞𝐧𝐭𝐫𝐚𝐥𝐢𝐳𝐚𝐭𝐢𝐨𝐧 𝐚𝐜𝐭𝐮𝐚𝐥𝐥𝐲 𝐡𝐞𝐥𝐩𝐬 𝐬𝐩𝐞𝐞𝐝 𝐮𝐩 𝐭𝐡𝐞 𝐧𝐞𝐭𝐰𝐨𝐫𝐤 too. Because of RLNC’s fundamental properties: - Recoding - Early forwarding - Decoding with any combination of coded shards it thrives in massive globally distributed networks, whereas other propagation methods slow down. Every new node adds more coded shards to the network, so decoding gets faster. More nodes in more diverse regions shortens the hops between them, so latency drops. This is how Optimum lets chains decentralize to scale.

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pigeon99 🕊🕊
pigeon99 🕊🕊@9pigeon9·
This is the kind of content that makes you really feel why Optimum matters @get_optimum You hit “Swap” on the DEX. A few seconds of suspense pass. Then finally “bang”, the tokens land in your wallet. That tiny gap between confirm and arrival? Most people never think about what’s actually happening in those seconds. @MurielMedard (Optimum CEO) breaks it down perfectly. Behind that delay is the invisible infrastructure of blockchains slow gossip networks, redundant packet forwarding, and unnecessary latency. Optimum’s mump2 powered by Random Linear Network Coding (RLNC) changes this completely. Instead of copying and forwarding the same data over and over, RLNC sends smart random linear combinations. Receivers reconstruct the original with far fewer packets → dramatically faster propagation, lower latency, and a much smoother onchain experience. This is how Optimum turns that “few seconds of suspense” into near-instant satisfaction. Real-time Web3 isn’t a dream anymore — it’s being built right now.
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Optimum@get_optimum

You've had your eye on this one for a while. You've done your research, built conviction, and patiently waited for the right entry to present itself. You check the chart for the 50th time this week and behold, a nice little dip with your name on it. "Go time", you whisper to yourself as you pull up the DEX. You set your buy amount, a respectable size, but not the full port. You learned your lesson last time. Review. Swap. Confirm. A few seconds later, "bang", the tokens hit your wallet. Amidst the feelings of satisfaction and hope for you newly filled bag you start to wonder, "what actually happened in those few seconds before my tokens arrived?" Here's a look at how your transaction lands onchain with Optimum CEO @MurielMedard 👇

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