Taurus запустила сервис стекинга для институциональных клиентов в партнерстве с Everstake

cryptonews.ruPubblicato 2025-12-19Pubblicato ultima volta 2025-12-19

Партнерство позволяет соединить инфраструктуру валидаторов Everstake с регулируемой системой хранения активов Taurus. В результате институциональные клиенты получают доступ к заработку на сетях с механизмом доказательства доли владения (PoS).

Согласно анонсу во вторник, Taurus — швейцарский провайдер инфраструктуры цифровых активов, регулируемый FINMA, — встраивает некастодиальные сервисы стекинга Everstake в свою систему хранения.

Благодаря интеграции банки и институциональные клиенты Taurus смогут делегировать валидаторам Everstake такие активы, как Solana (SOL), Near Protocol (NEAR), Cardano (ADA) и Tezos (XTZ). При этом приватные ключи и операционный контроль останутся в рамках привычных процессов хранения.

Everstake поддерживает более 80 сетей с механизмом доказательства доли владения. Объем активов в стекинге достигает около $7 млрд. Компания обеспечит необходимую инфраструктуру валидаторов.

Taurus основана в 2018 году в Швейцарии. Компания предоставляет инфраструктуру цифровых активов для банков и институтов — включая хранение, выпуск, торговлю и токенизацию.

В мае Taurus заключила партнерство с Parfin — институциональным провайдером блокчейн‑решений. Цель сотрудничества — расширить присутствие в Латинской Америке за счет услуг токенизации для финансовых организаций.

Рост институционального стекинга

Cтекинг — блокировка токенов для обеспечения безопасности сети с механизмом доказательства доли владения (PoS) в обмен на вознаграждение в виде нативных активов. Услуга набирает популярность среди институциональных инвесторов: технология выходит за рамки децентрализованных финансов (DeFi) и интегрируется в регулируемую инфраструктуру.

В феврале крупнейший протокол ликвидного стекинга Lido (LDO) представил версию Lido v3 с новыми stVaults. Решение позволяет институциональным стейкерам эфира настраивать параметры в соответствии с требованиями регулирования и операционного контроля.


Протоколы ликвидного стекинга и рыночная капитализация. Источник: DefiLlama

В октябре Coinbase пошла по аналогичному пути: компания расширила интеграцию с Figment. Теперь институциональные клиенты могут размещать в стекинге более широкий спектр активов PoS напрямую через подразделение хранения.

Anchorage Digital расширила предложение Hyperliquid, добавив стекинг HYPE через свой американский банк и лицензированную структуру в Сингапуре. Функция стекинга, работающая на инфраструктуре валидаторов Figment, также будет доступна через кошелек самохранения Anchorage.

Ранее банк добавил услуги хранения и стекинга для токена STRK сети Starknet (сентябрь). Это расширило институциональный доступ к активу и его возможностям по генерации дохода.

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NVIDIA CPU Advances, China's RISC-V Responds: Semiconductor Deep Dive - Part Four

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My Coding Betting Dashboard is Profiting, but Polymarket is Truly Not a Good Place for 'Arbitrage'

The author built a custom monitoring dashboard for Polymarket, a prediction market platform, and tested it with $1,600, achieving over 30% returns. However, the core argument is that Polymarket is not a good venue for traditional arbitrage. The dashboard has two main sections: a "Portfolio Dashboard" for tracking active positions with key metrics like total capital, P&L, and a risk-control module using a tier system (T1, T2, T3), and an "Opportunity Watchlist" for monitoring markets. The article details a critical structural trap in binary markets: a bet with a high perceived probability of success still carries a 100% loss risk if wrong. The author's T1/T2/T3 system is designed to manage this by limiting position sizes based on conviction and time horizon, emphasizing that high confidence should not equal high concentration. A key insight is the danger of "pseudo-diversification"—betting on different markets driven by the same underlying variable. The author concludes that Polymarket offers few true low-risk, arbitrage opportunities. It is instead a high-risk environment where wins can create a false sense of mastery, leading to large losses. The platform is better viewed as a training ground for honing judgment through disciplined, framework-driven betting rather than a reliable income source. The tools help transform intuition into structured, rule-based decisions to mitigate the risk of catastrophic errors.

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My Coding Betting Dashboard is Profiting, but Polymarket is Truly Not a Good Place for 'Arbitrage'

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WeChat AI Card Hands-On Guide: Has the AI Shopping Era Arrived?

**"WeChat AI Card" Practical Test Guide: Has the Era of AI Shopping Arrived?** WeChat has officially launched the "AI Exclusive Card," a feature integrated into its Workbuddy AI assistant. This card is designed to handle payments for AI-initiated purchases. Our hands-on test reveals it's not yet a tool for fully autonomous AI shopping, but rather a controlled payment layer for AI agents. The AI Card functions as an isolated sub-wallet within WeChat Pay. Users must bind the card and transfer funds into it from their main wallet. Crucially, every transaction requires explicit user confirmation via smartphone scan; AI cannot spend autonomously. Currently accessible through the Workbuddy agent, the card targets specific digital consumption scenarios: purchasing paid content (reports, data), calling paid APIs/tools, and subscribing to services. Its design prioritizes security and control by separating funds and mandating approval for each payment. We tested a real-world scenario: ordering bubble tea via Workbuddy using a "Meituan Life Assistant" skill. The process encountered multiple hurdles: high "skill" usage costs (exceeding daily free credits), and most importantly, while a payment was successfully initiated, the AI purchased an incorrect product (a mismatched group-buy coupon instead of the desired drink). This highlights the current limitation: the **AI Card only solves the payment step**. The broader challenge lies in the **AI agent's execution chain**—accurately understanding intent, navigating third-party platforms, selecting the right product, and ensuring proper fulfillment. The payment succeeded, but the purchase failed to meet the user's need. In conclusion, the WeChat AI Exclusive Card is a cautious, early-step experiment in AI commerce. It provides a secure, user-controlled payment method for agent interactions but is not yet capable of reliable, end-to-end complex purchases. For now, it's best used for low-value, low-risk digital services with careful user verification at each step. The vision of AI handling complete shopping tasks remains a work in progress.

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