特朗普转发添热度,Polymarket成大选民调新平台?

Odaily星球日报Pubblicato 2024-02-01Pubblicato ultima volta 2024-02-01

Introduzione

特朗普有多大可能当选美国总统?

去中心化预测市场 Polymarket 热度再起,平台新账户数创历史新高,据 Dune 数据,Polymarket 2024 年 1 月交易额达 5134 万美元,创月度历史新高。

特朗普转发添热度,Polymarket成大选民调新平台?

在 Polymarket 上赌谁会当选美国总统

Polymarket 流量近期大幅增长的原因除了 1 月初的比特币 ETF 是否会通过这个预测,还有美国大选。

距离美国总统大选还有近十个月,特郎普作为参选人之一且是一个善于玩弄社交媒体的政治人物,已经连续几次在其创办的媒体 Truth Social 上转发他在 Polymarket 上的赔率,这为 Polymarket 带来了很大的曝光。如今,政治类赌注在 Polymarket 上流量都十分高。

特朗普转发添热度,Polymarket成大选民调新平台?

左图为 Polymarket 站内流量排名;右图为特郎普转发其 Polymarket 上的赔率截图

Polymarket 上热度最高的预测市场是「 2024 年总统选举获胜者」,每个结果的起始交易价格为 0.5 美元,价格会根据用户在输赢双方下注的金额而变化,价格(赔率)代表当前事件发生的概率,也就是说当前价格为 0.5 美元意味着特郎普有 50% 的概率会当选总统。如果价格上涨至 0.7 美元,意味着特朗普有 70% 的概率赢得提名。截至撰稿时,该市场的赌注达到了 3367 万美元。

Polymarket 的运作模式颇为独特,用户可以将自己对未来某件事的预测转化为实际的投资组合,而这些投资选择实际上是用户对各类信息的深度解读和未来展望的具象表示。成功的预测不仅能带来潜在的经济利益,同时也证明了交易者对特定话题的深刻洞察力。比如对于比特币 ETF 相关的

自 2020 年首次亮相以来,Polymarket 一直是加密 Degen 打赌的首选目的地,用户可以通过加密钱包使用 USDC 买卖 shares,做市商可以在每个市场提供流动性而获得每周奖励。而政治选举预测则是预测市场能大范围传播和流行的最大推动力之一。当这二者结合,Polymarket 又一次吸睛无数。此前 2020 年的选举月,Polymarket 的月收入甚至已经超过 SushiSwap 成为区块链中产生费用第四高的项目。

就连以太坊创始人也会在 Polymarket 上对政治选举进行下注,一个月前,Vitalik 曾在 Warpcast 上表示,「我的非常保守,押注于无聊但可能获胜的多元市场政治投资组合似乎表现良好」。

特朗普转发添热度,Polymarket成大选民调新平台?

Crypto 之外,Polymarket 的 PMF

尽管 Polymarket 是一个部署在 Polygon 上实打实的去中心化市场项目,但其已经完成了在加密之外获取 PMF 的蜕变。在 Polymarket 主页导航栏上可以看到,Crypto 只是其中一个板块,除此之外还有政治、中东局势、体育、流行文化等主题。Mass Adoption 一直是部分加密项目的梦寐以求的目标,Polymarket 似乎又一次显示出了自己的潜力。

特朗普转发添热度,Polymarket成大选民调新平台?

上周,1co nfirmation 的 GP Richard Chen 在《计算机 vs 赌场:加密行业的文化战争》一文中提到赌场传奇人物 Steve Wynn 如何将拉斯维加斯从单一的赌博中心转变为综合性娱乐目的地,Wynn 在 1989 年开设 The Mirage,首创在赌场外提供丰富的娱乐体验,如音乐会表演和购物商场等,这一战略的成功促使其他赌场效仿,大大增加了访问拉斯维加斯的游客量。

因此,Richard 认为加密行业也应该减少零和游戏,转向提供正和体验。而预测市场就是完成这一使命的最佳选择之一,既可以作为投注平台,也能成为获取信息的来源。

市场预测长期以来一直被视为认知技术领域的圣杯,早在 2014 年,Vitalik 就对使用预测市场作为治理机制(即 futarchy)表示兴趣。然而,到目前为止预测市场在实际应用中并没有取得太大进展,并且通常存在一系列常见问题:大部分参与者往往非理性,拥有「正确知识」的人除非能够涉及大额资金,否则不愿意投入时间和风险进行投注,市场流动性通常也不足。

Vitalik 在昨日发布的博文中提到,「如果人们愿意在体育赛事上投注数百亿美元,那么为什么他们不会在美国选举或其他重大事件上投入足够的资金,以吸引严肃的参与者呢?」然而这个论点必须面对一个事实,就是以往的版本并未达到这样的规模。不过,Vitalik 依旧看好预测市场,因为他认为人工智能将会有广泛参与预测市场的可能性。

但在与 AI 广泛结合之前,我们仍需考虑 Polymarket 当前面临的问题,一个是除了政治(争议性较大和周期性事件)之外,还有哪些事件可以为平台带来稳定的用户和流量;另一方面如果 Polymarket 成功,会为加密市场带来哪些好处,围绕它可以构建什么样的衍生事物,让这个市场保持持续的活力?

推特上有 Taylor Swift 的粉丝转发 Polymarket 上关于 2024 年格莱美最佳歌曲的预测市场,并将 Taylor 与另一个流行歌手 Billie Eilish 进行赔率比较。传统市场的玩家越来越多参与进来,Polymarket 的前景或许会更加明朗。

Letture associate

Stablecoins Finally Find Real Yield: An In-Depth Look at On-Chain Reinsurance Re | A Conversation with Re Founder Karan Saroya

Stablecoin Real Yield Found: A Deep Dive into On-Chain Reinsurance with Re's Karan Saroya As stablecoin supply exceeds $170 billion, the search for sustainable, non-speculative yield intensifies. Re, an on-chain reinsurance platform, provides an answer: connecting stablecoin capital to the trillion-dollar traditional reinsurance market. Re operates as a regulated reinsurer, accepting stablecoin deposits as collateral to back US insurance companies. These insurers pay premiums, generating yield that flows back to on-chain depositors. Currently supporting 35 insurers and underwriting $500 million, Re projects scaling to over $1 billion soon. Key insights from a Bankless podcast with founder Karan Saroya and investor Avichal of Electric Capital: 1. **Uncorrelated, Real-World Yield:** Re offers stablecoin holders access to reinsurance returns (targeting 12-14%+), an asset class entirely separate from crypto or equity markets. 2. **Operational Efficiency via Smart Contracts:** Re replaces traditional, labor-intensive capital fundraising with smart contracts, allowing a ~12-person team to compete with industry giants. 3. **Regulatory Leverage:** For every $1 of collateral, regulations allow backing $5-7 in written premiums. This leverage amplifies returns from the underlying risk-free rate. 4. **DeFi Integration:** Depositors receive receipt tokens, which can be used in protocols like Morpho for "looping," potentially pushing yields to 18-20%+. 5. **The "DeFi Mullet" Model:** A compliant front-end (regulated reinsurer) paired with a decentralized back-end (smart contracts, DeFi capital markets). 6. **RE Governance Token:** Modeled on Lloyd's of London, the token governs the central capital pool's allocation, counterparty acceptance, and parameters. 7. **Real Economic Impact:** Capital funds real-world productivity (factories, clinics, businesses) via insurance, moving beyond crypto's internal loops. The discussion highlights a pivotal moment: DeFi's supply-side infrastructure is now met by real demand for productive yield, potentially kickstarting a flywheel where vast on-chain stablecoin capital seeks these real-world returns.

链捕手36 min fa

Stablecoins Finally Find Real Yield: An In-Depth Look at On-Chain Reinsurance Re | A Conversation with Re Founder Karan Saroya

链捕手36 min fa

1996 or 1999? Walsh's First Test is 'How to View AI'

"1996 or 1999? Wall's First Big Test Is 'How to View AI'" Federal Reserve Chairman Wall's initial challenge is not whether to raise or cut rates, but a more fundamental judgment: what kind of boom is the current AI boom? This will determine the Fed's policy path and define his legacy. Economics is split between two opposing views, according to reporter Nick Timiraos. One sees imminent productivity gains that will increase supply and cool inflation, allowing the Fed to hold steady. The other argues that while productivity benefits are distant, demand shocks are here now, and waiting for data confirmation risks missing the intervention window, forcing sharper rate hikes later. Wall has signaled a leaning toward the first view, echoing 1996-era Alan Greenspan, who embraced strong, productivity-driven growth without fear of inflation. However, Wall faces a different macro environment than Greenspan did, with tariff pressures, expanding fiscal deficits, and diminishing globalization benefits, which could force more significant inflation pressures even if AI benefits materialize. Wall's logic, expressed before taking office, is that AI-driven productivity gains won't show in official data for years. If the Fed waits for confirmation, it might mistakenly tighten policy and choke off the very growth that could suppress inflation. This argues for using forward-looking narratives over lagging data. Chicago Fed President Austan Goolsbee presents a key counter-argument. He distinguishes between expected and unexpected productivity booms. A widely anticipated boom, like the current AI wave, can cause people to spend future wealth gains in advance, overheating the economy before productivity actually rises, thus requiring preemptive rate hikes. He cites rising costs for AI data centers as evidence of such overheating. Fed Governor Christopher Waller offers a rebuttal to Goolsbee, noting the "expected spending" mechanism only works if people can borrow against future income, which many households cannot do due to borrowing constraints. Wall also faces a paradox related to his desire to reduce the Fed's use of "forward guidance" (pre-announcing policy moves). This practice was established in 1999 when Greenspan began signaling hikes to avoid market shocks. If the economy follows a less optimistic path, Wall may be forced to choose between using the guidance he wants to abolish or risking market volatility by staying silent. The ultimate question defining Wall's first major test remains: Is this 1996 or 1999?

marsbit1 h fa

1996 or 1999? Walsh's First Test is 'How to View AI'

marsbit1 h fa

Ethereum Q1 2026 Report: Fees Decline, Users and Transaction Volume Hit New Highs

Ethereum Q1 2026 Report: Fees Down, Users & Transactions Hit New Highs Token Terminal's Q1 2026 report on Ethereum presents a pivotal development: the network achieved record highs in monthly active users (13.2M, +85.9% YoY), total transactions (200.4M, +81.5% YoY), and throughput (25.78 TPS), while transaction fees on the mainnet plummeted by 47.9% quarter-over-quarter. This shift is attributed to the network's strategic move into a "low fees for scale" phase, exemplified by the Fusaka upgrade which increased data capacity and lowered block space costs, releasing pent-up demand (a manifestation of Jevons's Paradox). The report highlights a core narrative shift for Ethereum: from a DeFi-centric blockchain to a global financial settlement layer. It maintains a dominant position in tokenized assets, holding majority market shares among top chains in stablecoins (61.8%), tokenized funds (73.0%), and tokenized commodities (84.0%). Growth in tokenized funds (+73.1% YoY) and commodities (+325.9% YoY) was particularly strong, driven by institutions like BlackRock and JPMorgan entering the space. Contrasting these usage gains, several USD-denominated value metrics declined in Q1: fully diluted market cap fell 30.3% QoQ, total value locked (TVL) dropped 11.0%, and ecosystem transaction volume decreased 24.0%. The report interprets this as Ethereum prioritizing long-term network expansion and cementing its role as the default settlement layer for finance over short-term fee capture. The commentary from Etherealize argues that, much like the early internet, Ethereum's open, permissionless model is poised to win over closed alternatives as institutional tokenization accelerates.

marsbit3 h fa

Ethereum Q1 2026 Report: Fees Decline, Users and Transaction Volume Hit New Highs

marsbit3 h fa

He Just Raised 2.7 Billion, and Li Fei-Fei Also Invested

Pete Florence, a former senior research scientist at Google DeepMind and a key contributor to the Vision-Language-Action (VLA) model architecture, is deliberately distancing his startup, Generalist AI, from the trendy "world model" label. He argues that the industry should prioritize concrete goals over buzzwords. His goal is to create robots that can perform a vast range of unseen tasks with high speed and success rates, without needing task-specific training data. Recently, his company raised $400 million (¥2.7 billion) at a $2 billion valuation. Notable investors include NVIDIA's NVentures, Bezos Expeditions, NFDG, as well as Xiaomi co-founder Lin Bin, Zoom founder Eric Yuan, and renowned AI scientist Fei-Fei Li. Florence's approach stems from his academic background at MIT under Professor Russ Tedrake, focusing on understanding the physical world. After joining DeepMind, he developed models like Transporter Network and co-created the VLA framework. He left in 2025 to found Generalist AI. The company has launched two models: GEN-0, which demonstrated that scaling laws apply to physical motion, and GEN-1. GEN-1 was trained on over 500,000 hours of physical interaction data collected via a specialized wearable device. It achieves a 99% success rate on precise mechanical tasks like folding boxes and maintains performance three times faster than its predecessor. Florence believes GEN-1 is reaching a commercial utility threshold similar to the GPT-3 inflection point. The substantial funding round, following GEN-1's release, signifies strong investor confidence in Generalist AI's practical, goal-driven path to creating versatile, useful robots, regardless of the "world model" terminology.

marsbit3 h fa

He Just Raised 2.7 Billion, and Li Fei-Fei Also Invested

marsbit3 h fa

Trading

Spot
Futures
活动图片