速览NEAR算法稳定币USN,与UST有何不同?

深潮TechFlow2022-04-28 tarihinde yayınlandı2022-04-28 tarihinde güncellendi

Özet

算法稳定币战争愈演愈烈。

美元

USN是一个NEAR原生的、与美元软挂钩的稳定币。
类似于LUNA与UST,为了保持挂钩,NEAR被用来吸收USN的波动性,1USN可以兑换成价值1美元的NEAR。于是产生了套利空间:当USN=0.99美元时,人们可以买入1个USN并兑换价值1美元的NEAR,获利0.01美元;当USN=1.01美元时,人们可以用1美元NEAR兑换1个USN,然后以1.01美元卖出,获利0.01美元。

美元

这里的区别在于当1美元的LUNA铸造成1UST时,LUNA会被燃烧销毁,而NEAR则不会,参与铸造USN的NEAR会被存入协议的储备基金来代替销毁,成为支撑USN的一部分。
USN 最初由NEAR 和稳定币(USDT)通过储备基金进行双重抵押,以保证在极端情况下,Decentral Bank 可以回购曾经发行的全部 USN,并且在未来,储备金也会在协议的作用下自动平衡以始终高于100%的比例维持对USN的支持。

美元

关于USN质押,USN将根据NEAR质押奖励自动生成收益率,换句话说,USN最低收益率 = 质押NEAR的APY (~11%),如果由于NEAR升值或对USN的需求增加,储备中持有的NEAR的价值上升,则 APY 会更高,根据Decentral Bank的描述,最开始收益率将在 20% 左右(猜测为了吸引一部分质押UST的人),以后也将会集成第三方DeFi项目,使得USN有多种收益机会。
这一点与UST并不相同,因为USN并没有固定收益率,可能会让很多人失望,但Anchor支撑那约20%的年化是靠它的美元储备金,相比之下,USN风险似乎小得多。
USN对抗风险的能力也比较强,这得益于它的储备金机制,如果NEAR价格下跌,协议将使用储备金中的稳定币购买更多的NEAR;而如果USN卖方过多,USN会随时得到NEAR与稳定币的双重支持。
截至目前,获得USN的唯一方式是在通过Ref Finance 的 StableSwap使用 USDT 购买 USN。我现在并不想大仓位进入USN,但我会一直关注它,我更好奇算稳得结果会如何,马上就会有另一个竞争者USDD(TORN),并且它承诺30%的APY。这是稳定币最激动人心的时刻,算法稳定币战争愈演愈烈。

İlgili Okumalar

Podcast Notes: Hyperliquid Has Become the Top Interest Point for Traditional Hedge Funds

Empire Podcast hosts Jason Yanowitz and Santiago Santos discuss the surging institutional interest in Hyperliquid, a decentralized perpetual exchange, marking the highest level of engagement from traditional hedge fund managers since Paul Tudor Jones endorsed Bitcoin in 2020. The primary driver is the demand for weekend trading of commodities like oil, especially during geopolitical tensions such as the Iran conflict, as Hyperliquid provides the only active price discovery venue when traditional markets are closed. Trade XYZ, a front-end on Hyperliquid, has seen significant growth, with weekend oil price predictions having a median error of only 50 basis points. Santos predicts commodity trading volume on Hyperliquid will surpass Bitcoin within the year and that its market cap could rise from $25 billion to $100 billion. Other key points include Kraken raising $200 million at a reduced valuation of $13.3 billion, and the SEC clarifying that self-custodied DeFi frontends like MetaMask are not subject to broker-dealer rules, resolving a major regulatory uncertainty. The hosts also note the strong correlation between crypto and macro markets, with the S&P 500 posting one of its best 10-day rallies since 1950. They highlight MicroStrategy's continued Bitcoin acquisitions and the potential of real-world asset (RWA) tokenization as a key trend. The discussion concludes with skepticism towards many L2 projects, predicting a wave of protocols truly going to zero as capital concentrates in proven assets like Bitcoin and Hyperliquid.

marsbit5 saat önce

Podcast Notes: Hyperliquid Has Become the Top Interest Point for Traditional Hedge Funds

marsbit5 saat önce

a16z: The Next Frontier of AI, The Triple Flywheel of Robotics, Autonomous Science, and Brain-Computer Interfaces

a16z presents a comprehensive investment thesis for the next frontier of AI: Physical AI, centered on a synergistic flywheel of robotics, autonomous science, and novel human-computer interfaces (HCIs) like brain-computers. While the current AI paradigm scales on language and code, the most disruptive future capabilities will emerge from three adjacent fields leveraging five core technical primitives: 1) learned representations of physical dynamics (via models like VLA, WAM, and native embodied models), 2) embodied action architectures (e.g., dual-system designs, diffusion-based motion generation, and RL fine-tuning like RECAP), 3) simulation and synthetic data as scaling infrastructure, 4) expanded sensory channels (touch, neural signals, silent speech, olfaction), and 5) closed-loop agent systems for long-horizon tasks. These primitives converge to power three key domains: * **Robotics:** The literal embodiment of AI, requiring all primitives for real-world physical interaction and manipulation. * **Autonomous Science:** Self-driving labs that conduct hypothesis-experiment-analysis loops, generating structured, causally-grounded data to improve physical AI models. * **Novel HCIs:** Devices (AR glasses, EMG wearables, BCIs) that expand human-AI bandwidth and act as massive data-collection networks for real-world human experience. These domains form a mutually reinforcing flywheel: Robotics enable autonomous labs, which in turn generate valuable data for robotics and materials science. New interfaces provide rich human-physical interaction data to train better robots and scientists. Together, they represent a new scaling axis for AI, moving beyond the digital realm to interact with and learn from physical reality, promising significant emergent capabilities and value.

marsbit5 saat önce

a16z: The Next Frontier of AI, The Triple Flywheel of Robotics, Autonomous Science, and Brain-Computer Interfaces

marsbit5 saat önce

İşlemler

Spot
Futures
活动图片