Hyperliquid проведет голосование валидаторов по вопросу утверждения тикера USDH для стейблкоина

cryptonews.ruPublicado em 2025-03-07Última atualização em 2025-09-08

Децентрализованная биржа Hyperliquid проведет голосование валидаторов 14 сентября по вопросу утверждения тикера USDH для нового собственного стейблкоина. Это решение направлено на снижение зависимости от внешних стейблкоинов, таких как USDC, и подчеркивает роль сообщества в управлении сетью.

Ключевые детали голосования:

  • Сроки:

    • Подача предложений — до 10 сентября 10:00 UTC.

    • Заявления валидаторов — до 11 сентября.

    • Голосование — 14 сентября с 10:00 до 11:00 UTC.

  • Условия:

    • Тикер USDH не предоставляет стейблкоину особых привилегий.

    • Валидаторы Фонда воздержатся от голосования, чтобы избежать централизованного влияния.

  • Контекст:

    • USDH позиционируется как альтернатива стейблкоинам с мостом (например, USDC).

    • Некоторые протоколы в экосистеме выражают недовольство из-за возможного преимущества USDH перед их собственными решениями.

Стратегические цели Hyperliquid:

  1. Снижение зависимости от USDC:

    • Перераспределение резервного дохода внутри экосистемы.

    • По оценкам аналитика Jaehyung Ha (Presto), при 15% доле ликвидности USDH может привлечь $5,5 млрд и генерировать $220 млн годового дохода для держателей HYPE.

  2. Усиление роли сообщества:

    • Голосование демонстрирует децентрализованный подход в противовес централизованным биржам.

    • Модель управления призвана обеспечить прозрачность и снизить риски внешнего влияния.

  3. Технические изменения:

    • После обновлений сети котируемые активы станут неразрешимыми, что позволит любому пользователю создавать торговые пары без одобрения.

Возможные последствия:

  • USDH может стать экономическим рычагом для экосистемы Hyperliquid, усиливая её самостоятельность.

  • Голосование станет тестом на готовность сообщества принимать ключевые решения и снижать зависимость от внешних стейблкоинов.

Leituras Relacionadas

Just now, DeepSeek V4 updates with DSpark, improving inference speed by 80%

DeepSeek has updated its DeepSeek V4 model with the DSpark speculative decoding framework, achieving a significant 60-85% speedup in generation for Flash models and 57-78% for Pro models while maintaining the same overall throughput. This engineering-focused update, rather than a core architectural change, introduces DSpark to address latency and throughput bottlenecks in high-concurrency production environments. DSpark combines high-throughput parallel generation with adaptive load-aware verification. Its key innovations include a semi-autoregressive generation architecture to model dependencies within token blocks and a hardware-aware confidence-scheduled verification system. This system uses a confidence head to predict token acceptance probabilities, allowing it to dynamically optimize verification length per request and allocate compute only to tokens with the highest expected payoff. The asynchronous scheduler is designed for real-world deployment, ensuring zero-overhead scheduling and continuous CUDA graph replay while preserving the target model's output distribution. In tests across mathematical reasoning, code generation, and daily dialogue, DSpark outperformed state-of-the-art models like Eagle3 and DFlash, increasing average acceptance length by 26.7%-30.9% and 16.3%-18.4% respectively on Qwen3 target models. DeepSeek also open-sourced DeepSpec, a full-stack codebase for training and evaluating speculative decoding draft models, providing a standardized toolkit that includes data preparation tools, model implementations, training code, and evaluation scripts.

marsbitHá 2h

Just now, DeepSeek V4 updates with DSpark, improving inference speed by 80%

marsbitHá 2h

BIT Research: The 2028 Halving Is Not the End, the Real Shake-Up of the Bitcoin Mining Industry Is Just Beginning

The Bitcoin mining industry is undergoing its most complex structural adjustment since inception. Despite Bitcoin's price holding near $61,000 and the network hash rate approaching a record 1 ZH/s, miner profitability is deteriorating. The industry is operating close to its breakeven point, with the 2028 halving expected to accelerate consolidation. The challenges extend beyond the halving's subsidy reduction; the industry's revenue model has yet to successfully transition towards a fee-driven structure. Increasingly, mining companies are evolving from simple Bitcoin producers into infrastructure and energy operators, including providers of AI/HPC computing power. Competition is shifting from pure hash rate expansion to business model upgrades. Economic pressure is evident. The theoretical daily mining revenue at current prices is around $78 million, yet the actual figure is only about $33 million—a 136% gap. Transaction fees remain low at roughly $220k daily, far below historical implied levels. With a current estimated industry-wide breakeven price near $65,000, mining alone is struggling to generate ideal profits. The 2028 halving is projected to push the fundamental production cost floor to approximately $93,289. This will likely accelerate a shift towards consolidation among larger, well-capitalized miners with diversified revenue streams. Competitive advantage will belong to institutionalized players with access to low-cost energy, AI/HPC hosting operations, and stronger balance sheets. In essence, Bitcoin mining is transitioning from a "mining business" to an "infrastructure business." Future profitability and resilience will depend less on block rewards and more on diversified income sources like energy management and computational infrastructure services. For investors, the key question is not the halving itself, but which miners can successfully navigate this business model transformation.

marsbitHá 3h

BIT Research: The 2028 Halving Is Not the End, the Real Shake-Up of the Bitcoin Mining Industry Is Just Beginning

marsbitHá 3h

This is How God Karpathy Uses Claude?

Andrej Karpathy, a prominent figure in AI, has reportedly joined Anthropic, leading to a noticeable decrease in his open-source contributions and social media activity. A document claiming to be his personal "CLAUDE.md" file—a set of instructions for the Claude AI to follow within a specific codebase—has been circulating online. While its authenticity is unverified, the content aligns closely with Karpathy's publicly shared principles on effective AI-assisted programming. The document outlines key rules for AI coding assistants, emphasizing the importance of reading existing code thoroughly before writing new code to maintain consistency. It advises against over-engineering, advocating for simple, surgical modifications that match the project's existing style. Other guidelines include clarifying assumptions upfront, writing meaningful tests, thoughtful debugging, and carefully considering dependencies. The core message is that these principles help prevent common AI coding failures, such as introducing unnecessary abstractions, style drift, or making invisible architectural decisions. The community has noted that even experts like Karpathy require detailed instructions to guide AI effectively, akin to managing a junior developer. A related GitHub repository, "andrej-karpathy-skills," which encapsulates these ideas, is reported to significantly reduce Claude's code error rate. Ultimately, the advice stresses that the best CLAUDE.md is tailored to one's own tech stack and coding practices.

marsbitHá 3h

This is How God Karpathy Uses Claude?

marsbitHá 3h

Trading

Spot
活动图片