Dter-DT(❖,❖)
3.1K posts

Dter-DT(❖,❖)
@Flaha_dter
Art Creator, Member of @Raikucom



ᴡᴇʙ𝟹 ʜᴀs ᴀ ᴍᴇᴍᴏʀʏ ᴘʀᴏʙʟᴇᴍ — ᴀɴᴅ ᴡᴇ ғɪɴᴀʟʟʏ ʜᴀᴠᴇ ᴀ ғɪx. Web3 doesn’t suffer from “forgetfulness.” It suffers from flawed architecture. At its core, it lacks a true memory layer. Modern blockchains already resemble traditional computers in many ways. But one fundamental component is still missing: a decentralized memory layer capable of supporting the next generation of the internet. At a high level, Web3 functions as a global computer. Execution environments like the Ethereum Virtual Machine and Solana Virtual Machine run across thousands of distributed nodes, powering decentralized applications. But when you look deeper, a critical gap appears. There is no unified system for efficiently storing, accessing, and updating data. Instead, Web3 relies on a fragmented patchwork of solutions-inefficient, complex, and difficult to scale. The result is clear: Slow transactions. High storage costs. Limited scalability. That’s not what decentralization was meant to achieve. ᴀ ɴᴇᴡ ᴀᴘᴘʀᴏᴀᴄʜ The industry has already pushed existing solutions to their limits. Incremental improvements are no longer enough. A new direction is emerging: leveraging algebraic coding to represent and transmit data more efficiently across decentralized systems. This leads to a fundamental question: How do we build a truly decentralized memory layer? ᴇɴᴛᴇʀ ʀʟɴᴄ ᴀɴᴅ ᴅᴇᴄᴇɴᴛʀᴀʟɪᴢᴇᴅ ᴍᴇᴍᴏʀʏ A team led by @MurielMedard stepped away from academia to tackle this challenge head-on. Their approach is built on Random Linear Network Coding—a method developed and refined over nearly two decades at MIT. RLNC encodes data into packets that move efficiently across the network. Instead of repeatedly sending the same raw data, each transmission delivers new, useful information. The impact is significant: Higher throughput. Lower latency. Greater resilience. Unlike traditional gossip protocols—where nodes often share redundant data—RLNC ensures that each piece of information received adds real value. Think of it as always receiving new information, never duplicates. ғɪxɪɴɢ ᴛʜᴇ ʙᴏᴛᴛʟᴇɴᴇᴄᴋs Today’s blockchain communication behaves like rumor spreading. It works well at first, but as the network grows, redundancy increases and efficiency drops. RLNC changes this dynamic. It removes redundancy and keeps data propagation efficient, even at scale. Reimagining Memory: From Mempool to deRAM Web3 currently relies on mempools—temporary pools where transactions wait to be processed. In simple terms, it’s like a pile of clothes on the floor. Unstructured. Unreliable. Hard to manage. In contrast, a proper memory system—like RAM in traditional computing—must be: 1.Structured 2.Consistent 3.Reliable RLNC enables a new model: decentralized RAM (deRAM). This system: -Stores active data efficiently -Supports real-time updates -Reduces storage overhead -Preserves decentralization Instead of every node storing everything indefinitely, data can be handled dynamically-just like in modern computing systems. 𝓦𝓱𝔂 𝓣𝓱𝓲𝓼 𝓜𝓪𝓽𝓽𝓮𝓻𝓼 If Web3 is to become a true global computer, execution alone is not enough. It needs an efficient memory layer. Right now, blockchain systems rely on “best-effort” mechanisms that only partially replicate real memory. What’s missing is a unified architecture: A high-speed data bus An efficient memory layer for storage and access RLNC-based infrastructure has the potential to deliver both. 𝓣𝓱𝓮 𝓑𝓸𝓽𝓽𝓸𝓶 𝓛𝓲𝓷𝓮 Decentralization without efficiency cannot scale. RLNC and decentralized memory represent a fundamental upgrade: Faster data propagation Lower latency Scalable storage Real-time access This isn’t just an incremental improvement. It’s the missing piece finally coming together. Gmum. @get_optimum @aqccapital @ChandlerOtterbe @tgogayi @ada_pegasus @vssema11 @samurai_itan





Some projects make a lot of noise, raise big money, and promise the world but in the end, they fail. Why? Because their “product” is basically just a story designed to extract money from users and funds. Then there are the quiet builders. They don’t chase hype. They focus on execution, step by step, moving forward without needing constant attention. And somehow, they not only survive , they grow stronger. That’s exactly what I see with @TemplarProtocol A cypher lending project that raised only around ~$4M… yet look at what they’ve built. Real users. Strong trust from whales. A clean, simple UI that’s easy to use no unnecessary flash, just pure functionality. It reflects how they operate: no overcomplication, just results. And the numbers speak for themselves ,TVL around ~$21M. That’s seriously impressive given where they started. I genuinely believe this year could be a big win for Templar. Let’s push it to $100M, Knights. gTemplar. Bring Templar to the world.🛡️ @Daveisacatsheep @annawobanana @vuhi0811 @HoangNg469575
















Try the mini-game Pair Up 🧩 @raikucom Find the matching pictures and collect them all! ✅ 12 characters ✅ 24 cards ✅ 1 goal - find every pair Just like @raikucom : alone they’re just cards, but together - a real team 🚀 Are you ready to test your memory? 😏 raiku.online/12/index.html











New paper is out—CryptoAnalystBench: Failures in Multi-Tool Long-Form LLM Analysis. Improving reasoning agents starts with understanding how they fail. We study the errors that emerge when agents answer open-ended questions with no clear answer. Check core failures & fixes below 🧵

What are you doing tomorrow and why is it attending the Raiku Townhall? Your handsome hosts @IDrawCharts and @_offmylawn will be filling you in on everything that happened on Solana this week! Watch live on X or our Discord for a collectible NFT! x.com/i/broadcasts/1…





