CryptoQuant: Стейблкоины помогут биткоину сохранить бычий тренд

cryptonews.ruОпубліковано о 2022-02-02Востаннє оновлено о 2024-10-02

Эксперты инвестиционной компании CryptoQuant заявили, что стейблкоины стали своеобразной «кровеносной системой» для биткоина в частности и крипторынка в целом. Благодаря этому бычий тренд первой криптовалюты сохранится, сочли аналитики.

В CryptoQuantсообщили, что рост рыночной капитализации стейблкоинов в августе и сентябре составил около $172,75 млрд, увеличившись за два месяца на $8,73 млрд.

По наблюдениям экспертов, с 10 сентября зафиксирована высокая корреляция между курсом первой криптовалюты и чистым притоком стейблкоинов на централизованные торговые платформы — свыше 90%.

Совокупная рыночная стоимость стейблкоинов достигла максимума апреля 2024 года, что следует воспринимать как бычий сигнал для основных криптовалют. После изменения процентной ставки Федеральной резервной системы США выпуск стейблкоинов ускорился, что отражает растущую уверенность инвесторов в крипторынке, объявили аналитики.

Ранее генеральный директор майнинговой компании CleanSpark Зак Брэдфорд (Zach Bradford) заявил, что произойдут два скачка курса биткоина, прежде чем первая криптовалюта вернется к медвежьему тренду.

Пов'язані матеріали

A Company Once on the Brink of Bankruptcy Just Surpassed Bitcoin in Market Cap

On June 22nd, driven by rising stock prices, SK Hynix’s market capitalization reached $1.35 trillion, surpassing Bitcoin's total market cap of approximately $1.29 trillion. This temporarily made it South Korea's highest-valued company. The core driver of this surge is HBM (High Bandwidth Memory), for which SK Hynix is the primary supplier to NVIDIA, holding over 60% market share. AI's demand for high memory bandwidth has translated into immense profitability, with SK Hynix reporting a 72% operating profit margin in Q1. The company's success follows a 13-year bet on HBM technology, beginning in 2009. It nearly failed after the 2001 dot-com bubble, was acquired by SK Group in 2012, and was subsequently recapitalized to continue its long-term HBM development. The article contrasts this with the Crypto AI narrative. Capital currently favors AI infrastructure players like SK Hynix due to "real orders, physical barriers, and quantifiable profit margins." In comparison, Crypto AI projects, promising decentralized compute and data markets, remain largely conceptual with limited tangible progress. Examples include Bittensor, whose core mechanisms are still under development, and Bitcoin miners transitioning to AI, who face significant funding gaps and execution challenges. The piece cites analysis suggesting the AI sector has absorbed nearly all new market liquidity since 2022, leaving little for crypto. It concludes that the current AI infrastructure红利 is captured by entities with proven technical barriers and supply capabilities, while crypto networks still need to define their concrete role in the value chain.

链捕手20 хв тому

A Company Once on the Brink of Bankruptcy Just Surpassed Bitcoin in Market Cap

链捕手20 хв тому

Bittensor Moves Towards Ultimate Decentralization: The Critical 18 Months for the TAO Ecosystem is Here?

Bittensor, a decentralized AI protocol, is accelerating its transition to full decentralization over the next 18 months, as outlined in a recent post by co-founder Const. The project currently operates in a "semi-decentralized" state: ownership and network participation are open and permissionless, with TAO distribution based on competitive contribution. However, protocol upgrades and governance have remained under core team control to enable rapid iteration in the fast-evolving AI sector. This strategic shift comes as the ecosystem matures, boasting 128 subnets and a large community. Const argues that continued centralization now poses risks, including single points of failure and regulatory scrutiny. The upcoming decentralization roadmap includes optimizing validator competition, opening liquidity pools, introducing governance rights for Alpha holders, and refining economic models. The move could fundamentally reshape TAO's value proposition, adding governance premiums to its existing valuation based on AI narrative and scarcity. It also signals a potential maturation of the AI crypto sector, where competition may shift from hype to sustainable protocol design and real economic activity. Bittensor positions itself not just as another AI token, but as foundational infrastructure aiming to decentralize intelligence production—analogous to Bitcoin's role in decentralizing money—with the goal of creating a resilient "Millennium Intelligence Federation."

marsbit32 хв тому

Bittensor Moves Towards Ultimate Decentralization: The Critical 18 Months for the TAO Ecosystem is Here?

marsbit32 хв тому

Japan's AI Dark Horse Emerges: How a 7B Small Model Challenges Fable and Mythos?

In June 2026, Sakana AI's new model Fugu caused a stir in the AI community. Its Fugu Ultra variant achieved scores of 73.7 on SWE-Bench Pro and 82.1 on TerminalBench 2.1, surpassing GPT-5.5 and Claude Opus 4.8, and was claimed to be comparable to export-restricted models like Fable 5 and Mythos Preview. Remarkably, the core of this high-performance system is not a massive model, but a small 7B-parameter RL Conductor model. Fugu operates as a multi-agent orchestrator: the 7B model acts as a "foreman," dynamically analyzing user tasks and delegating subtasks to a pool of top-tier global models (e.g., GPT-5, Gemini 3.1 Pro). It then synthesizes and verifies their outputs. This architecture represents a paradigm shift from monolithic models to an expert-team approach. It enhances performance in complex, multi-step engineering tasks like code review and security testing by enabling cross-validation from specialized models, improving long-session stability and token efficiency. However, Fugu's strengths come with trade-offs: it faces inherent latency due to multiple API calls, relies heavily on underlying US model APIs (creating dependency risks), and its benchmark comparisons with Fable/Mythos are based on reported scores, not head-to-head testing. For Japan's AI ecosystem, which lacks the massive compute and data resources of the US or China, Fugu exemplifies an "asymmetric breakthrough" strategy. Instead of competing directly in parameter scale, it focuses on intelligent orchestration of existing global models, offering a degree of AI sovereignty and resilience. While a significant system-level innovation, its ultimate capability is still bounded by the underlying models it coordinates.

marsbit33 хв тому

Japan's AI Dark Horse Emerges: How a 7B Small Model Challenges Fable and Mythos?

marsbit33 хв тому

Торгівля

Спот
Ф'ючерси
活动图片