Wintermute 推出 OutcomeMarket,为选举预测市场提供动力

marsbit2024-09-17 tarihinde yayınlandı2024-09-18 tarihinde güncellendi

Wintermute 的去中心化预测市场将使用 TRUMP 和 HARRIS 代币,为 Polymarket 提供替代方案。

算法交易公司 Wintermute 宣布推出 OutcomeMarket,这是一个去中心化的预测市场平台,最初将专注于 2024 年美国总统大选,代币与候选人唐纳德·特朗普和卡马拉·哈里斯挂钩。

该平台将于下周推出,允许用户直接参与以太坊 (ETH) 及其第 2 层扩展网络 Base 和 Arbitrum 的预测市场,并且无需在链之间桥接资产。

OutcomeMarket 的平台将由无需许可的智能合约驱动——其中包含驱动去中心化应用程序 (dapps) 的代码——这意味着任何交易场所都可以列出其代币而无需征收铸造或交易费用。

去中心化

Wintermute 首席执行官 Evgeny Gaevoy 表示,该平台旨在通过降低进入门槛来创建一个更容易进入、更高效的市场。首次代币发行将以 TRUMP 和 HARRIS 为特色,允许用户对候选人在选举中的表现进行投票,同时还可以在多个交易所的去中心化金融 (DeFi) 应用程序中使用这些代币。

Chaos Labs 的预言机是“先进的人工智能和 LLM 与风险模型的独特结合”,它“提供高度精确、防篡改的数据馈送,同时将实时风险评估直接嵌入协议中”,Chaos Labs 首席执行官 Omer Goldberg 表示。Wintermute是Chaos Labs的投资者。

“中心化和去中心化交易场所都对列出此类预测市场合约表现出浓厚兴趣,但没有人以无需许可的方式开发它们,并且不收取铸币费或交易费,”他写道。

该平台将利用 Chaos Labs 的 Edge Proofs Oracle 来确保整个链上数据的完整性和可靠性。包括 Bebop、WOO X 和 Backpack 在内的几个交易场所已经承诺列出 OutcomeMarket 代币。

近年来,政治 meme 币和预测市场受到广泛关注,将加密货币投机与政治预测融合在一起。2020 年,FTX 衍生品交易所针对美国总统大选推出了类似的预测市场,交易量巨大。当然,FTX 随后因欺诈指控而倒闭。

PredictIt 和 Polymarket 等预测市场也面临监管审查,Polymarket 于 2022 年支付了 140 万美元的民事罚款,以解决 CFTC 指控。2024 年,Polymarket 的人气和交易量激增,这主要是由于人们对选举投注池的兴趣。

İlgili Okumalar

Li Fei-Fei's Latest Long-Form Article: When Video Generation, Robotics, and NVIDIA All Call Themselves World Models, We Need a Taxonomy

In a new article, Dr. Fei-Fei Li addresses the widespread and often inconsistent use of the term "world model" in AI. She proposes a clear, functional taxonomy rooted in the classic Partially Observable Markov Decision Process (POMDP) loop (agent → action → state → observation → agent). According to this framework, current systems called "world models" are different projections of this loop, categorized by their primary output: 1. **Renderers**: Output observations (pixels). Their goal is visual fidelity for human consumption (e.g., video generation models like Sora). They are the most commercially mature but are limited by a focus on appearance over physical accuracy. 2. **Simulators**: Output states (geometric, physical, dynamic representations). They provide a structurally accurate world for both human professionals (e.g., architects) and computational agents (e.g., robots for training). Li argues simulators are the crucial, underappreciated bridge, as they can underpin both rendering and planning. 3. **Planners**: Output actions. Given an observation and a goal, they decide what an agent should do next (e.g., robotic action models). This area is highly promising but remains the least mature for real-world deployment. Li highlights a key trend: the boundaries between these three categories are beginning to blur, as they all rely on a shared underlying understanding of geometry, physics, and dynamics. The logical endpoint is a unified world foundation model capable of switching between rendering, simulation, and planning based on downstream needs. This convergence, she concludes, is central to advancing spatial intelligence—enabling machines not just to talk about the world, but to truly understand, imagine, and interact with it.

marsbit2 saat önce

Li Fei-Fei's Latest Long-Form Article: When Video Generation, Robotics, and NVIDIA All Call Themselves World Models, We Need a Taxonomy

marsbit2 saat önce

Forbes Feature: Stablecoin Cross-Border Payments Are Faster, But Not Yet Cheaper

A Forbes feature delves into the state of stablecoin-based cross-border payments, noting rapid growth but a key shortfall: while faster and more accessible, they are not yet cheaper. At a recent industry conference in Mexico City, optimism about technology, regulation, and volume was tempered by discussions with practitioners. The core issue is liquidity. Traditional FX brokers charge 60-70 basis points, and stablecoins promise to slash this to 2-5 basis points. However, this theoretical cost advantage cannot be realized until deep liquidity pools are established at scale, requiring significant institutional capital inflow. A major adoption barrier is trust. Businesses often rely on long-standing relationships with traditional brokers, valuing reliability over marginal cost savings. This shift will be gradual. Furthermore, successful companies in the space are not positioning themselves as replacements for legacy systems like SWIFT, but as complements. They leverage stablecoins for speed while using traditional rails for their standardization and reliability in ensuring accurate payment details—a critical factor for supplier payments to avoid customs issues. Companies like Caliza, experiencing high monthly growth, exemplify this hybrid approach. The industry anticipates consolidation, as long-term viability will depend on securing the essential trifecta: proper licensing, robust fiat on/off-ramps, and deep liquidity. Without these, firms risk being mere intermediaries rather than building sustainable businesses.

marsbit2 saat önce

Forbes Feature: Stablecoin Cross-Border Payments Are Faster, But Not Yet Cheaper

marsbit2 saat önce

Li Feifei's Latest Article: When Video Generation, Robotics, and NVIDIA All Claim to Have 'World Models,' We Need a Taxonomy

"World Model" has become a widely used yet ambiguous term in AI. Drawing from the classic POMDP framework (agent → action → state → observation), this article proposes a functional taxonomy to clarify the concept. It identifies three distinct types, categorized by their output in the perception-action loop: 1. **Renderers**: Output visual observations (pixels). These models, like advanced video generators, prioritize visual fidelity but often lack underlying physical accuracy. 2. **Simulators**: Output the state of the world (geometry, physics, dynamics). They provide a structurally accurate representation for professionals (e.g., architects) and serve as training environments for robots and AI agents. 3. **Planners**: Output actions. Given an observation and a goal, they determine what an agent should do next, closing the perception-action loop (e.g., vision-language-action models). While renderers are currently the most commercially mature and planners are the most aspirational, the article argues that **simulators are the crucial, underappreciated hub**. By working at the level of geometry and physics, a simulator can project upwards to create visuals for humans and downwards to predict action consequences for agents. The future lies in the convergence of these three functions. Emerging research and products, like World Labs' Marble model which outputs both visual splats and physical collision meshes, are beginning to blur these boundaries. The logical endpoint is a unified world foundation model capable of rendering, simulating, and planning based on a shared understanding of spatial and temporal structures—ultimately enabling machines to understand, imagine, and interact with the physical world.

链捕手2 saat önce

Li Feifei's Latest Article: When Video Generation, Robotics, and NVIDIA All Claim to Have 'World Models,' We Need a Taxonomy

链捕手2 saat önce

İşlemler

Spot
活动图片