Курс биткоина рухнет до $18,000, считает аналитик

investing.ruPublished on 2024-12-30Last updated on 2024-12-30

Happycoin.club - Финансовый аналитик, известный под псевдонимом MFHoz, считает, что курс биткоина рухнет до $18,000 к середине 2026 года.

Биткоину нанесли сильный удар на уровне $100,000, на котором находится мощная психологическая зона сопротивления. Вечеринка закончена, близится крах. Цена BTC упадёт прямо до $18,000–$20,000, — написал MFHoz.

Судя по графику, опубликованному MFHoz, медвежий тренд, возникший на рынке биткоина 17 декабря после того, как курс монеты обновил исторический максимум на отметке $108,364, окажется затяжным и закончится в середине 2026-го.

Мнение эксперта о том, что дно будет достигнуто на отметке $18,000, скорее всего, основано на ширине сокращающегося треугольника, изображённого на графике.

Прогноз MFHoz на падение курса биткоина на графике

Текущая ситуация на рынке пока не столь апокалиптична, как её описывает MFHoz, однако инициативу, безусловно, удерживают медведи.

27 декабря цена BTC опустилась ниже линии средней скользящей за 50 дней и закрепилась под ней. Одновременно с этим индекс RSI на суточном графике попал в негативную область, уменьшившись до 43. В совокупности эти факторы говорят о том, что в ближайшем будущем стоимость криптовалюты снизится до $90,000. Если продавцы пробьют этот барьер, то биткоин вполне может подешеветь до $80,000 в январе 2025-го.

Читайте оригинальную статью на сайте Happycoin.club

When US Giants Collectively "Defect" to Chinese AI Models

When Silicon Valley Giants Turn to Chinese AI Models to Cut Costs A surprising trend is emerging: major U.S. tech companies are significantly reducing AI costs by switching to Chinese models. Coinbase, the largest U.S. cryptocurrency exchange, reportedly halved its AI spending after migrating to China's GLM-5.2 and Kimi 2.7 models, despite increasing usage. They achieved this through a sophisticated three-part strategy: implementing an automatic routing system to select the most cost-effective model per task, boosting cache hit rates from 5% to 60% to reuse computations, and employing "context engineering" to provide AI with more precise, less cluttered information. They are not alone. AI startup Lindy switched from Claude to DeepSeek, saving millions, while Snowflake's tests found GLM-5.2 solved 66% of coding tasks compared to Claude Opus's 67%—but at a fraction of the cost (output pricing is 5-7 times lower). While the top Western models may offer slightly better stability, the massive price differential is leading many businesses to reconsider their value proposition. This shift signals a deeper change in the AI industry, moving beyond pure performance benchmarks to a fierce cost competition. As pressure mounts, even OpenAI and Anthropic have begun slashing prices. For users, this means more choices, lower costs, and a crucial lesson: using multiple models based on task complexity, optimizing with caching, and keeping contexts lean are now key to leveraging AI efficiently and affordably.

marsbit6m ago

When US Giants Collectively "Defect" to Chinese AI Models

marsbit6m ago

BIS Report Compliance Watch: The Real Risks of Stablecoins Are Not Just 'De-pegging'

BIS Report Compliance Observations: The real risks of stablecoins go beyond "depegging" The BIS report "Anchoring trust in money: innovation beyond stablecoins" argues that while stablecoins and tokenization offer efficiency gains, their primary risk lies in fitting into an identifiable, monitorable, accountable, and regulatable financial system. Money's trust stems not just from technology but from institutional arrangements: a common unit of account, guaranteed redemption at par, liquidity support, regulatory frameworks, and financial integrity requirements. Stablecoins, operating on permissionless blockchains with pseudo-anonymity and non-custodial wallets, create systemic compliance gaps: unclear customer identity, incomplete fund origins, unexplained transaction purposes, fragmented cross-chain paths, and ambiguous liability. On-chain transparency does not equal compliance transparency. Public addresses don't reveal identity or intent. While blockchain analytics aid law enforcement, they cannot replace routine, large-scale AML/CFT controls. Effective compliance requires a closed-loop process encompassing customer onboarding, transaction monitoring, investigation, reporting, and audit. Stablecoin risks are not confined to the blockchain; they re-enter the traditional financial system via on/off-ramps, exchanges, and payment institutions. This forces banks to monitor client accounts for activity linked to virtual assets. The future direction is not to prohibit innovation but to embed rules into the technology. Tokenized finance should integrate with the existing two-tier monetary system, embedding compliance—like customer identification, pre-transaction screening, and auditable data trails—directly into the transaction flow. For compliance professionals, the key takeaway is that any new financial instrument must answer core questions: Who identifies the customer? Who monitors transactions? Who handles exceptions? Who is liable? Compliance is not the antithesis of innovation but the essential infrastructure for its sustainable growth.

链捕手7m ago

BIS Report Compliance Watch: The Real Risks of Stablecoins Are Not Just 'De-pegging'

链捕手7m ago

When American Giants 'Defect' to Chinese AI Models

Summary: The trend of major U.S. technology firms adopting more cost-effective Chinese AI models is gaining momentum. A prime example is Coinbase, the largest U.S. cryptocurrency exchange, which reportedly halved its AI expenditure by switching to Chinese models GLM-5.2 and Kimi 2.7, while its usage volume increased. This was achieved through a sophisticated cost-saving system featuring intelligent model routing (selecting the most suitable model per task), dramatically improving cache hit rates from 5% to 60%, and implementing "Context Engineering" to streamline prompts. This shift is not isolated. Other companies like the AI startup Lindy and data cloud firm Snowflake are making similar moves, drawn by the significant price disparity. For instance, GLM-5.2 costs $1.40/$4.40 per million tokens (input/output), compared to $5/$25 for Claude Opus 4.7. While top Western models may offer slightly higher stability or speed in complex tasks, the performance gap is narrowing, making the price difference harder to justify for many enterprise use cases. The implications are significant for both businesses and individual users. It highlights the importance of a multi-model strategy based on task requirements, the value of caching and reusing outputs, and the effectiveness of providing concise context. Ultimately, this migration signals a potential reshaping of the AI industry's pricing model, moving competition from pure performance benchmarks to practical cost-effectiveness, with increased choice and downward price pressure benefiting end-users.

链捕手14m ago

When American Giants 'Defect' to Chinese AI Models

链捕手14m ago

Sui Testnet Update v1.74.1 Slashes Transaction Gas Costs Via Protocol Version 128

Sui blockchain developer Mysten Labs has deployed testnet update v1.74.1, introducing protocol version 128. The primary outcome of this upgrade is a significant reduction in transaction gas costs for users and developers operating on the testnet. These optimizations are designed to enhance network performance and scalability in preparation for a future mainnet deployment. It is crucial to note that these changes are currently confined to the testnet environment. The development provides a concrete, source-verified data point regarding ongoing protocol improvements. For market participants, this represents a confirmed technical advancement to consider, though it should be weighed alongside broader market factors and does not in itself guarantee specific price movements. The story highlights a focus on foundational development amid typical market volatility.

bitcoinist15m ago

Sui Testnet Update v1.74.1 Slashes Transaction Gas Costs Via Protocol Version 128

bitcoinist15m ago

Bitcoin eyes macro jump to $70K after drop below $60k – What’s next for BTC?

Bitcoin's price recently dipped below $60,000 but has since recovered to around $61,540. While technical indicators like the RSI and MACD show some bullish signs, they are not strongly convincing. On-chain data reveals a market reset, with asset managers' net long exposure at its lowest since U.S. spot Bitcoin ETF launches, though they remain net long. Leveraged funds have significantly reduced net short positions, and open interest has fallen sharply, indicating leverage is being unwound. Long-term holders are buying at lower prices, providing support. However, Bitcoin remains below its 30-day moving average, suggesting the overall trend is not yet fully bullish. Large transfers to exchanges like Coinbase Prime have occurred, potentially indicating future selling pressure. Analysts warn that downside risk remains as Bitcoin has not reached severely oversold levels typical of cycle bottoms. The market's next major move may depend on institutional activity.

ambcrypto19m ago

Bitcoin eyes macro jump to $70K after drop below $60k – What’s next for BTC?