Alexander.base.eth
@0x_Alexander
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On-chain & off-code. Web3 native | Hunting airdrops and alphas | 1% better everyday is more than you can imagine.
Milky way
Joined February 2023
Hereโs the thing about gasless chains: if nobody pays gas, the native token eventually becomes useless. LightLink's entire financial engineering solves this by asking: What if we make gas optional, but use the token to fund the gasless subsidy?
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Inference Labs is building critical infrastructure for a future where AI outputs must be provable, not merely persuasive. Rather than optimising for marginal gains in speed or scale, the team focuses on verification frameworks that make model reasoning inspectable and auditable.
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Most people talk about places theyโve never truly experienced. @dagama_world is built for the opposite kind of person. Itโs designed for those who show up, observe carefully, and leave behind something useful. The core idea behind daGama is simple but powerful: credibility
Most systems online are built to reward expression. @dagama_world is built to reward presence. That distinction is subtle, but it changes everything. Instead of amplifying whoever speaks the most, Dagama verifies who actually showed up. Every contribution is tied to a
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You know @dango is merging CLOB, unified margin, cross-chain swaps into a DeFi superapp. CLOBs = precise execution, limited scope unlike AMM DEX with fragmented liquidity. @inference_labs secures AI-driven DeFi by making AI inference provable, not trusted. Instead of blindly
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The real elegance of @MemeMarketFun's deflationary design is that it structurally coordinates holding pressure. The mechanism converts trading friction (the burn tax) into a permanent supply reduction, effectively transforming the short-term cost of volatility into the long-term
The fundamental coordination challenge in a zero-utility asset is managing human attention decay. For @MemeMarketFun, deflationary tokenomics serves as the engineered incentive-to-hold, not a mere supply reduction; it structurally rewards indifference to short-term market noise,
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AI is moving into critical systems faster than trust is being established. Decisions are being automated. Capital is being deployed by agents. Outcomes are starting to matter in the real world. Yet most AI today still relies on blind trust. You are expected to believe the model
Most decentralized systems do not fail because of bad ideas. They fail because of friction. Latency. Delays. Data arriving too late to matter. Inference Labs is tackling this problem at its root by rethinking how decentralized applications access and execute data. At the center
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Infrastructure partnerships often chase scale. The clearer logic with @dagama_world and Hyra Network centers on reliability. When coordination runs on verifiable uptime and shared state, intelligence compounds because systems respond to reality, not assumptions. 1๏ธโฃ Start from
AI partnerships often focus on outputs. The deeper insight at @dagama_world with PUNDI AI centers on inputs. When intelligence trains on verified behavior, not assumptions, coordination improves and decisions gain context instead of noise. 1๏ธโฃ First principles matter.
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Inference Labs solves AI's "black box" problem by creating a layer for accountable autonomy. They use zkML to generate verifiable proofs of AI decisions, anchored on a decentralized ledger. This builds the auditable trust foundation required for autonomous systems to scale.
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๐๐๐๐๐๐๐๐ ๐๐๐๐๐๐๐๐๐๐ ๐ฅ ๐๐๐๐๐๐๐ ๐: ๐๐ซ๐ฎ๐ฌ๐ญ๐ฅ๐๐ฌ๐ฌ ๐๐ ๐๐ง๐ญ๐ฌ โ ๐๐จ๐ฐ ๐๐ ๐๐๐ญ๐ฌ ๐๐จ๐ซ๐ซ๐๐๐ญ๐ฅ๐ฒ ๐๐ข๐ญ๐ก๐จ๐ฎ๐ญ ๐๐ฌ๐ฌ๐ฎ๐ฆ๐ข๐ง๐ ๐๐ซ๐ฎ๐ญ๐ก Autonomous agents donโt fail because theyโre
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๐๐๐๐๐๐๐๐ ๐๐๐๐๐๐๐๐๐๐ ๐ฅ ๐๐๐๐๐๐๐ ๐: ๐๐ก๐๐ง ๐๐๐ซ๐ข๐๐ข๐๐ ๐๐ซ๐ฎ๐ญ๐ก ๐๐๐๐ญ๐ฌ ๐๐จ๐จ๐ซ๐๐ข๐ง๐๐ญ๐ข๐จ๐ง Truth alone doesnโt move systems. Coordination alone doesnโt guarantee correctness. Decentralized intelligence requires
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The deeper I get into @MemeMarketFun, the more I see how participation creates value. Itโs not just about holding $MFUN โ itโs about showing up, engaging, and growing alongside the community.
Consistency is starting to pay off. Being active around @MemeMarketFun has shown me that Web3 rewards those who actually participate, not just watch from the sidelines.
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ๅคๆฐ Web3 ้กน็ฎ็ๆ นๆฌ้ฎ้ข๏ผไธๆฏๆๆฏไธๅคๅคๆ๏ผ่ๆฏ็ฐๅฎ็ผบๅธญใ ็ณป็ปๅจ้พไธ่ชๆดฝ๏ผๅดไธ็ๅฎไธ็่ฑ่ใ @OfficialXYO ็ไปทๅผๅจไบ๏ผๅฎไธโๆ่ฟฐ็ฐๅฎโ๏ผ่ๆฏ่ฏๆ็ฐๅฎๅญๅจ่ฟใ XYO
ๅคงๅคๆฐไบบๆ chatandbuild ็ๆไธไธชโ็จๅฏน่ฏ็ๆๅบ็จ็ๅทฅๅ
ทโ๏ผไฝ่ฟๅชๆฏ่กจๅฑ็่งฃใ ็ๆญฃ็ไปทๅผๅจไบ๏ผๅฏน่ฏๆฌ่บซๆญฃๅจๆไธบ็ไบงๅ๏ผๆบ่ฝไฝๆญฃๅจๆไธบ่ตไบงใ Chatandbuild ไธๆฏ็ฎๅๆๆณๆณๅๆ DApp๏ผ่ๆฏๆโๆๅพ โ ้ป่พ โ
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What makes ecosystems durable is not yield, but orientation: clear paths, local context, and a reason to return tomorrow with more conviction than yesterday. Thatโs the quiet layer @dagsma_world is building in-between discovery and belonging where movement turns into memory.
@dagama_world introduces a framework that treats coordination as an evolving discipline rather than a static feature list. Its approach reframes how decentralized environments interpret signals, enabling structures that adjust intelligently instead of reacting blindly.
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Thereโs a clear shift happening right now. People are moving away from loud promises and toward systems that can actually prove what they claim. Thatโs why @inference_labs and @dagama_world feel aligned in spirit, even though theyโre building in different directions.
Sometimes progress doesnโt announce itself loudly โ it shows up quietly in the way systems start making more sense. Thatโs the signal I keep seeing from @inference_labs and @dagama_world. @inference_labs is solving a problem most people ignore: AI without proof is just
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Want to verify only safety layers? You can. Need to prove policy compliance without exposing private weights? Done. Running anomaly detection in a high-risk environment? Selective proofs make it practical. DSperse turns zkML from an academic exercise into something deployable in
Most people think the biggest problem in zkML is cryptography. It isnโt. Itโs architecture. Trying to prove an entire large AI model as a single monolithic circuit is a dead end. The memory requirements are massive. The hardware needed is unrealistic. Proving times stretch
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AI is powerful, but its real bottleneck has always been trust. Black-box outputs feel impressive until stakes rise, then doubt creeps in. @dagama_world flips this for discovery. By anchoring recommendations to on-chain proof of presence, wallet history, and rarity signals like
Most Web3 identity systems still assume trust must be granted. Someone approves you, scores you, or whitelists you. That assumption breaks the moment scale, automation, or adversarial behavior enters the system. Galxeโs stack, powered by Inference Labs and daGama, exists because
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gm ct grinders ๐ง @inference_labs Labs is pushing AI trust to the next level with Proof of Inference making AI outputs verifiable, not just believable. By combining zkML with decentralized inference, every result can be checked on-chain, protecting
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daGama restores trust in travel by replacing fake reviews with blockchain-verified, community-backed locations. AI guides discovery, users earn for authenticity, and real places rise on proofโnot paymentโturning exploration into a reliable, shared Web3 experience.@dagama_world
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โ @inference_labs The Operating System for Trustless Intelligence Inference Labs isnโt building a network itโs building the foundational operating system for trustless AI. By combining distributed compute, cryptographic proofs, agent identity, and privacy preserving execution.
โ @inference_labs Enterprise Grade Verifiability for AI Predictions Enterprise hesitation around AI isnโt about capability itโs about reliability. If an output canโt be verified, it can't be trusted in mission critical workflows.
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The voting system developed by daGama puts the power back in the hands of the community. Customers who explore, donate, and mint places will actually have a say in deciding what is important on the map. The whole process of voting is clear and is done using blockchain technology.
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.@Dagama_world is not trying to win by hype. It is trying to win by design. One thing that stands out is how the project treats participation as skill, not noise. Most platforms reward activity. Dagama rewards judgment. That difference matters because incentives shape behavior.
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daGama fixes the core flaw in every travel app: trust decay. Fake reviews, paid rankings, and stale info turn discovery into guessworkโwasting time and draining excitement. daGama reverses this by making authenticity the only scalable signal. At its core is the Multi-Level
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