Ассоциация Stand With Crypto оценивает отношение кандидатов на выборах 2026 года к цифровым активам

cryptonews.ruОпубліковано о 2025-04-24Востаннє оновлено о 2025-11-25

Организация по защите интересов криптоиндустрии Stand With Crypto, поддерживаемая Coinbase, начала опрос кандидатов на федеральных и региональных выборах об их позиции по цифровым активам перед промежуточными выборами в США 2026 года.

В уведомлении в понедельник Stand With Crypto сообщила о рассылке вопросника неопределенному числу кандидатов на выборах разных уровней. Опрос касается их позиций по «цифровым активам, криптоинновациям, проблемам банковского обслуживания, майнингу и зонированию, защите прав потребителей» и другим темам. Организация также запросила информацию о том, использовали ли респонденты криптовалюты или технологию блокчейн.

«Следующий состав Конгресса существенно повлияет на принятие в США политики, благоприятной для криптовалют, которая способствует экономическому росту, инновациям и доступности», — заявил директор по сообществу Stand With Crypto Мэйсон Линэ.

В Stand With Crypto сообщили, что будут использовать результаты опроса для определения приоритетов работы на промежуточных выборах 2026 года, включая проведение мероприятий и мобилизацию сторонников криптовалют для голосования. Представитель организации уточнил о широком распространении форм, но не назвал точное число кандидатов.

Организация уже продемонстрировала влияние на результаты выборов губернатора Нью-Джерси в 2025 году, где могла способствовать победе демократа Майки Шерилл.

На выборах 2026 года будут оспариваться все 435 мест в Палате представителей США и 33 места в Сенате, а также многие региональные должности. В 2024 году Stand With Crypto сообщала о победе 274 кандидатов, которых считали «прокриптовалютными» на основе их публичных заявлений и голосований.

«Вопросник не только существенно повлияет на итоговую оценку политиков от Stand With Crypto, но и станет основным способом получения кандидатами профиля на сайте для ознакомления избирателей по всей стране перед голосованием», — сообщил представитель организации.

Приостановка работы над структурой рынка на время праздников в США

На этой неделе члены Палаты представителей и Сената уходят на региональные рабочие периоды, возвращаясь в свои округа и штаты перед празднованием Дня благодарения в четверг.

Хотя Конгресс продолжает работу над законопроектом о создании комплексной структуры рынка цифровых активов, праздники и самое длительное в истории США прекращение работы правительства могут замедлить планы республиканцев принять закон до 2026 года.

Тем не менее последняя оценка председателя банковского комитета Сената Тима Скотта указывает на принятие закона в начале следующего года.

Пов'язані матеріали

My Grievance Against Memory Manufacturers: Samsung and Others Are Strangling the AI Capital Expenditure Cycle

Title: My Resentment Towards Memory Manufacturers: Samsung and Others Are Strangling the AI Capital Expenditure Cycle. Summary: The author argues that the DRAM oligopoly (Samsung, SK Hynix, Micron) is aggressively raising prices, jeopardizing the ongoing AI investment boom. DRAM contract prices are up nearly 700% year-over-year, with memory projected to consume 40% of hyperscaler capex by 2027. While manufacturers enjoy margins of 60-80%, the soaring cost forces cloud giants like Microsoft to significantly increase budgets. The author contends this is unsustainable, as cloud providers' free cash flow is being consumed by capex. He predicts a turning point in mid-2027, earlier than the consensus view of 2030, when capex growth will stall as cost pressures bite, leading to a peak and subsequent decline in DRAM pricing and manufacturer margins. This challenges the "end of the memory cycle" narrative, asserting that high prices will inevitably curb demand and trigger a downturn.

marsbit30 хв тому

My Grievance Against Memory Manufacturers: Samsung and Others Are Strangling the AI Capital Expenditure Cycle

marsbit30 хв тому

Mining Scale Skyrockets: Why Can't Bitdeer Hold onto Its Bitcoin?

Bitdeer's May 2026 operational data reveals a stark contrast: while its Bitcoin mining output surged to 921 BTC, a 370% year-over-year increase, its end-of-month holdings plummeted to just 171 BTC. This significant disparity highlights that the company, amidst a strategic pivot towards AI cloud infrastructure, continues to rely heavily on selling newly mined Bitcoin to fund operations and expansion, despite reporting a steady $69 million in annualized recurring AI revenue. The trend is consistent with Q1 2026 figures, where mining output reached 2,033 BTC but holdings were a mere 31 BTC, with $206.8 million from digital asset disposals. While the AI business, showing 90% GPU utilization, offers a potential future cash flow buffer to reduce dependency on Bitcoin sales, its current contribution to actual confirmed revenue remains limited. The transformation introduces new risks related to client acquisition, capital-intensive data center projects like Tydal, and delivery timelines. The core question raised is whether the AI venture will successfully generate sufficient stable cash flow to allow Bitdeer to retain more of its mining proceeds as Bitcoin treasury assets, or if the shift merely changes the form of financial pressure while Bitcoin reserves continue to dwindle.

Foresight News38 хв тому

Mining Scale Skyrockets: Why Can't Bitdeer Hold onto Its Bitcoin?

Foresight News38 хв тому

Beyond the Model Lies the Harness: Deepseek Enters the Arena, Why Has the Main Battlefield of China's AI Competition Shifted?

In mid-to-late May 2026, Deepseek internally established a new Harness team focused on code agent products, internally benchmarked against Anthropic's Claude Code. This move, marked by the formula "Model + Harness = Agent" in their job postings, signals a major shift in China's AI competition: the main battlefield is transitioning from developing large models to building toolchains and achieving workplace integration. Deepseek's direct involvement in Harness development aims to secure control over interface design and training data feedback loops, moving beyond open-sourcing powerful models. Harness, the runtime infrastructure for AI agents, handles everything beyond model reasoning—task orchestration, tool calling, context management, safety checks, and error recovery. It is crucial because agent products are not just outputs of model capability but also training grounds for it. Real-world task failures recorded by Harness can feed back into model training, creating a flywheel effect. Engineering Harness is more critical than optimizing prompts, as poor context management or error handling can drastically reduce agent success rates in multi-step, real-world scenarios. This shift is not isolated. Other major Chinese tech companies are also pursuing differentiated toolchain strategies. Tencent leverages its enterprise ecosystem (WeChat Work, Tencent Cloud) to build connectors for organizational-level AI collaboration and complex task delivery. Alibaba focuses on lowering automation barriers on the web with a front-end, browser-based GUI Agent framework, PageAgent. This diversification shows the industry recognizes that success lies not in a perfect general agent, but in vertically focused solutions built with robust engineering. The trend is validated by overseas success, such as Poland's Viktor, an AI coworker on Slack achieving $20M ARR by autonomously executing complex, multi-step tasks. This proves a shift in enterprise willingness to pay—from "AI-assisted generation" to "AI-autonomous execution." As Harness matures to provide safety guards and reliability, AI transitions from a human-supervised intern to an independent outsourcer. The competition now faces key engineering challenges: preventing "token explosion" through intelligent context compression, and building "thick frameworks" with features like sandbox isolation and checkpoint recovery for enterprise-grade stability. Geopolitical restrictions on tools like Claude Code further create a significant market vacuum for domestic solutions like Deepseek's Harness. For enterprises and developers, the focus must shift from comparing model benchmarks to evaluating a vendor's engineering capabilities, error recovery mechanisms, context management, and ecosystem compatibility when choosing AI products and platforms.

marsbit40 хв тому

Beyond the Model Lies the Harness: Deepseek Enters the Arena, Why Has the Main Battlefield of China's AI Competition Shifted?

marsbit40 хв тому

Stock Price Plummets 32% in a Month! Has MicroStrategy's 'Leveraged Bitcoin Buying' Model Reached Its End?

MicroStrategy's stock has declined 32% over the past month, with its flagship Series A Preferred Stock (STRC) falling below its $100 par value. Analysts attribute the weakness not to Bitcoin's price, but to market concerns over how the company will manage its growing fixed obligations and fund shareholder distributions. MicroStrategy recently sold a small portion of its Bitcoin holdings to meet these payments, marking a shift from its core narrative of continuous capital raises to accumulate Bitcoin. While the company asserts its substantial BTC reserves provide decades of liability coverage, the move has introduced complexity and questions about future financing efficiency. Analysts see this as a period of growing pains rather than an existential threat, noting that investor demand for higher returns reflects increased risk perception.

marsbit50 хв тому

Stock Price Plummets 32% in a Month! Has MicroStrategy's 'Leveraged Bitcoin Buying' Model Reached Its End?

marsbit50 хв тому

Soaring Export Data for Memory Chips, Market Is Redefining the Valuation Anchor for Memory Stocks

Korean storage export data for the first 20 days of June shows substantial year-on-year increases in both value and price-per-kilogram for categories like DRAM, NAND, and SSDs. This signals a potential shift beyond simple demand recovery, indicating rising prices and a product mix shift towards higher-value items, possibly influenced by AI infrastructure needs. A key point is that the surge in price-per-kilogram is not simply a uniform chip price hike. It reflects a combination of actual price increases and, more importantly, an export structure increasingly dominated by high-value-density products like HBM (High-Bandwidth Memory) and advanced DRAM, which are critical for AI servers. This suggests AI-driven demand may be spilling over from just HBM into broader memory markets. SK Hynix stands to benefit directly due to its leading HBM position. For Samsung and Micron, the implication is potential for greater margin elasticity if the tightness in high-end memory spreads to enterprise SSD and NAND prices. However, the storage sector remains cyclical. Risks include supply expansion, inventory changes, and potential slowdowns in broader AI capital expenditure. Ultimately, while the strong export data supports upward revisions for storage company earnings and fuels discussion of an "AI infrastructure bottleneck premium," a definitive valuation shift from a cyclical to a structural story depends on upcoming quarterly reports. Investors need confirmation from SK Hynix, Samsung, and Micron that improvements in average selling prices, product mix, and, crucially,毛利率 are sustained over multiple quarters.

marsbit2 год тому

Soaring Export Data for Memory Chips, Market Is Redefining the Valuation Anchor for Memory Stocks

marsbit2 год тому

Торгівля

Спот
Ф'ючерси
活动图片