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蓝狐
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蓝狐笔记,通往web3的世界。 (1.仅记录想法,没有客观只有主观,不能作为投资建议 ;2.蓝狐笔记只有此号,没有任何telegram或discord等群,没有其他分号,不会要求任何人参与投资,也不会发表跟区块链无关内容 ;3.不会发布链接,不要点击,谨防受骗。)
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蓝狐
You've raised a sharp and excellent question. Once the mindshare market on Polymarket becomes large enough and liquid enough, Kaito's mindshare score will gradually evolve from passively "measuring attention" to actively "generating attention," eventually transforming from a simple reflective indicator into a fully reflective asset. Here are some speculations about this evolution: 1. The signal begins to self-reinforce. Once some savvy traders discover that betting on a particular mindshare project, YES shares, is profitable, some early adopters will buy mindshare YES shares. The community sees the score rising, so they work harder to yap, driving real discussion, further increasing the score, pushing up YES shares, and thus profiting. In other words, initially it only reflects attention, but when attention becomes a betting behavior, this will feed back into the attention score itself. 2. Once the first scenario occurs, professional operators of "mindshare projects" will emerge, perhaps becoming a phenomenon within the next year (if there is liquidity). For example, by artificially inflating the price of YES shares in a mindshare project on Polymarket, and then having KOLs follow suit, driving up discussion volume, and exceeding a certain score, the manipulators who had positioned themselves beforehand ultimately profited from the Polymarket pool. 3. Another extreme scenario is the emergence of a "mindshare bubble" or a "mindshare trap." For instance, some manipulators might push the probability of YES shares in a mindshare project to over 90%, leading some in the community to believe the project will revive, releasing false signals to the market, causing unsuspecting investors to enter, inflating the token price, then the manipulators exit, the score drops, and a collapse occurs. Kaito's "mindshare" score requires continuous upgrades to its countermeasures; otherwise, future manipulation could mislead the market, releasing false signals, ultimately harming unsuspecting players. For ordinary investors, if they see a mindshare market price fluctuate dramatically in a short period, this might be a "mindshare trap."
zarah_khaleel
@zarah_khaleel
What if Kaito’s signals begin shaping the market more than the market shapes the signals?? At that point the data isn’t just measuring attention it’s creating it. How do you think that kind of feedback loop would affect the reliability of predictions, especially when traders x.com/lanhubiji/stat…
KAITO
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蓝狐
Excellent question. Advances in ZK technology will gradually transform the previously almost irreconcilable contradiction (performance versus decentralization) into a positive cycle: higher throughput leads to stronger decentralization. 1. Lowering Hardware Barriers Previously: Proving an Ethereum block required 50-160 high-end GPUs, costing $300,000-$500,000, meaning only companies could afford it. Afterward: 2-8 RTX 5090s are sufficient (cost < $15,000), allowing individuals and studios to participate in full-fledged proof nodes. Evolutionary Direction: Proofers shift from an "oligopoly" to "tens of thousands of miners," naturally increasing decentralization. 2. Changes in Economic Incentives Previously: Only centralized sorters earned money. Afterward: Whoever provides proof gets paid (Succinct Prove, Brevis ProverNet's proof-for-profit market). Evolutionary Direction: A true "proof-as-mining" market emerges; the more participants, the more censorship-resistant the network. 3. L1 itself will also benefit. Once the cost of proving a very large block becomes acceptable, the community can confidently increase the L1 gas limit without worrying about "verifiers not keeping up." Result: L1 throughput increases 3-5 times, while running a full node still only requires a regular consumer-grade computer; decentralization increases rather than decreases. 4. Privacy becomes a new moat for decentralization. ZK technology enables contracts to read the entire network's history and cross-chain data without trust. In the future, privacy-focused DeFi, zkML, and RWA will no longer rely on centralized oracles → reducing the attack surface and becoming more decentralized. In short, ZK is no longer a compromise of "sacrificing decentralization for scalability," but rather a lever to "push decentralization to new heights with verifiable computation."
BTC Frogger
@BTCFrogger
how do you think these zk breakthroughs will shape the balance between decentralization and throughput in the next year
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蓝狐
Recent progress in Ethereum's ZK technology has exceeded expectations, especially the recent breakthroughs by Succinct and ZKSync. Succinct's SP1 Hypercube can prove 99.7% of Ethereum L1 blocks in 12 seconds using 16 RTX 5090 GPUs, a 5x efficiency improvement over six months ago; ZKSync Airbender recently demonstrated generating Ethereum L1 blocks using two 5090 GPUs. Succinct optimizes a low-latency general-purpose zkVM; ZKSync's Atlas/Airbender integration achieves sub-second settlement and 15k TPS (specifically referring to high-frequency payments/transfers, not general-purpose); Brevis emphasizes cross-chain data coprocessors. The efforts of these three have greatly advanced the entire Ethereum ZK ecosystem: all three are working to build the ZK infrastructure stack: general-purpose proofs (Succinct) + efficient rollups (ZKSync) + data bridging (Brevis), driving the Ethereum ZK ecosystem from fragmentation to integration. The above progress is just some data; more importantly, what does this progress mean for the Ethereum ecosystem? * Higher TPS It allows for a more confident increase in gas limits. Previously, ZK proved computationally intensive, typically requiring 50-160 high-end GPUs to process a block in 12 seconds. Now, if progress reaches the point where only two 5090 GPUs are needed, it means the feasibility of proving larger blocks (higher gas limits) increases. This directly improves L1 throughput without sacrificing decentralization. * Lower Costs L2 costs, in particular, will continue to decrease, potentially dropping to a cent or even a fraction of a dollar. L2 fees, such as those for zksync, will continue to decline, becoming barely noticeable to ordinary users. Furthermore, the Fusaka upgrade in early December, and the gradual increase in blob capacity, will further reduce L2 costs. * Increased ETH Burning Following Fusaka in early December, Blob capacity increased. While L2 fees will decrease, the fee guarantee mechanism after the Fusaka upgrade (EIP7918), combined with ZK technology, has the potential to further drive the development of L2 applications. More application chains similar to Lightner will emerge, and the increased transaction volume could lead to more ETH burning. In summary, the Ethereum L1/L2 ecosystem has gradually shifted from "expensive/slow" to "provable scaling." Succinct, Zksync, and Brevis have contributed to the overall expansion of the Ethereum ecosystem without sacrificing decentralization (and even facilitating its further decentralization). From an ecosystem development perspective, this has laid an important foundation for the Ethereum ecosystem, especially for L2 to truly transition to consumer-grade applications. Future scenarios such as privacy DeFi, AI proxy economics, and RWA will all benefit. The subsequent ecosystem evolution will become increasingly interesting.
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蓝狐
The collaboration between EigenCloud, Kaito, and Polymarket is interesting. While it appears complex, it's easy to understand in layman's terms. The collaboration fully combines the strengths of each party, somewhat like a "three-layer collaborative stack," which can be likened to an "attention prediction pipeline"—Kaito is the input layer, generating data signals; EigenCloud is the trust layer, responsible for verifiable execution; and Polymarket is the output layer, handling user trading interactions. The general process is: Internet data (Twitter/Discord) → Kaito AI (generates mindshare scores) → EigenAI verification (re-execution + ZK proof) → Polymarket market (betting scores) → Settlement (audit passed, winners profit). For example, suppose there's a prediction bet: "Which prediction platform is the most popular?" How is this generated, verified, and settled? First, Kaito AI scans Web3 sources and calculates mindshare scores: Polymarket = 45%, Kalshi = 30%, and others = 25%. Then, a market is created on Polymarket: "This week, Polymarket mindshare > 40%?" Users buy YES (betting Polymarket is leading) or NO shares. After the AI signal is generated, EigenCloud verifies it (rerunning the model to check for output consistency). At settlement, the audit is made public (visible on-chain), and the winner automatically profits. So, what are the benefits for all three parties in this collaboration? For Eigen, the main benefit is increased revenue. The Kaito model runs on EigenCloud, and each additional verifiable calculation contributes to Eigen's value accumulation. The more popular the prediction market based on Kaito's output, the greater the demand for AI verification, and the more beneficial it is for Eigen. For Polymarket, there's an opportunity to earn more transaction and settlement fees. For Kaito, it helps to make its mindshare score more influential and expand its market size. In short, it's a win-win collaboration for all three parties.
EigenCloud
@eigencloud
11-21
Announcing verifiable mindshare markets on Polymarket. We're excited to make mindshare verfiable with @KaitoAI, unlocking a new class of markets. Kaito’s AI runs on EigenAI, turning what used to be an opaque model into verifiable compute that anyone can audit before @Polymarket x.com/KaitoAI/status…
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