Курс биткоина за сутки обвалился на $2 тыс.

RBK-cryptoОпубліковано о 2024-08-12Востаннє оновлено о 2024-08-12

Общая капитализация крипторынка за 24 часа сократилась почти на $100 млрд

Курс биткоина (BTC) за сутки упал более чем на $2 тыс. Первая криптовалюта за 24 часа опустилась в цене с $60,7 тыс. до $58,4 тыс. К утру 12 августа монета подешевела на 4,4%, по данным CoinGecko.

BTC/USD
58 303 -2 909 (-4,75%)
ОКХ Aug 12 09:53:10
1д
3д
1м
3м
1г
5л

Курс Ethereum (ETH) за сутки снизился на 4%. Ведущий альткоин торгуется по $2,55 тыс., днем ранее его цена достигала $2,7 тыс.

Общая капитализация крипторынка уменьшилась за 24 часа почти на 100 млрд. Объем ликвидаций позиций трейдеров на криптобиржах за сутки составил $155 млн, большая часть из них — лонги по BTC и ETH.

Телеграм-канал РБК-Крипто — подпишитесь и будьте в курсе самых главных и актуальных новостей о криптовалюте

Такие криптовалюты из топ-100 по капитализации, как Optimism (OP), Mantra (OM) и Beam (BEAM), за ночь подешевели более чем на 10%. Рост показала только монета Sui (SUI) — она подорожала на 1%.

Опрошенные «РБК-Крипто» эксперты указали на то, что на этой неделе ожидается насыщенный экономический календарь с фокусом на данных по инфляции в США. В то же время аналитики рекомендуют инвесторам проявлять осторожность из-за сохраняющейся волатильности и низкой ликвидности рынка.

«РБК-Крипто» запустил мониторинг криптовалютных обменников. Выбирайте надежный обменный сервис с выгодным курсом на yourcryptoex.ru или в удобном телеграм-боте.

Пов'язані матеріали

Embodied Intelligence 'Gaokao' is Insanely Hard, Humans Score 100, Best Model Only 12.8

Embodied AI Faces a Daunting "Everest": New Benchmark Reveals Huge Gap Between Models and Humans A comprehensive new benchmark for robotic manipulation, RoboDojo, has been released, painting a stark picture of the current state of embodied AI. It serves as a unified evaluation platform covering both simulation and real-world robot tasks. The benchmark assesses five core capabilities: Generalization (adapting to new scenes/objects), Memory, Precision manipulation, Long-Horizon multi-step tasks, and Open semantic understanding. It includes 42 simulation tasks and 18 standardized real-world tasks across three dual-arm robot platforms. The results are sobering. In simulation, the best-performing generalist robot policy achieved an average success rate of only 8.80%. Performance in the real world was slightly higher but still low, with the top model succeeding 12.8% of the time on average. In stark contrast, human experts scored 76.03% in simulation and 100% in real-world tests. The benchmark highlights significant, uneven gaps in current models' abilities. While some excel in specific areas like visual recognition or simple actions, they struggle with reliability, especially in long-horizon tasks where errors accumulate and in open-ended semantic instructions. The low scores, particularly in real-world deployment with physical uncertainties like camera noise and contact dynamics, underscore that today's models are far from being robust, general-purpose operational robots. RoboDojo is more than just a ranking; it's an infrastructure designed for fair, reproducible comparison. Its companion system, XPolicyLab, standardizes the interface for different models to be evaluated. Maintained by an academic consortium without commercial ties, it aims to provide a community-wide "altitude meter" to track genuine progress toward reliable and generalizable robot manipulation.

marsbit2 хв тому

Embodied Intelligence 'Gaokao' is Insanely Hard, Humans Score 100, Best Model Only 12.8

marsbit2 хв тому

Behind ANSEM's 300% Weekly Surge: The Recovery and Traps of Solana Meme Coins

The meme coin ANSEM surged nearly 299% in a week, driving a resurgence in Solana-based meme token activity. Data from DeFiLlama shows Pump.fun's weekly DEX volume reached $5.33 billion, with July 4th marking the platform's first $1 billion daily volume since April. This revival saw a spike in new token launches and heightened trading activity, with memes again accounting for over 20% of Solana's weekly transaction volume. However, industry reports highlight significant risks. The average meme coin holding time has plummeted to around 100 seconds, and sophisticated bots often front-run retail investors, acquiring large portions of supply at launch before dumping. Research analyzing thousands of projects indicates widespread market manipulation, with a majority of top-gaining tokens showing signs of wash trading and pool manipulation. While meme coins effectively attract new users and generate hype for the Solana ecosystem, the current rally raises the critical question of whether this cycle can break free from the established pattern where late-arriving retail traders become exit liquidity for early bots and coordinated groups. The market's future trajectory hinges on whether the momentum can be sustained or if it will fade, leading traders back to major assets like SOL.

Foresight News43 хв тому

Behind ANSEM's 300% Weekly Surge: The Recovery and Traps of Solana Meme Coins

Foresight News43 хв тому

Zuckerberg's 'Mango' Image Generation Model Trails Only GPT Image 2, It Learned to Revise Prompts on Its Own

Meta's MSL has launched Muse Image, an advanced image generation model nicknamed "Mango," which ranks second globally in text-to-image benchmarks, closely trailing OpenAI's GPT Image 2. Its key innovation is agent-like behavior: it searches for factual information, writes code for charts, and, most notably, has developed self-correction abilities through reinforcement learning, allowing it to revise its own outputs without explicit programming. This shift emphasizes reasoning over immediate generation. Integrated with Meta's ecosystem, Mango connects with the Muse Spark language model for complex tasks and features a unique "@" function that can incorporate public Instagram photos into generated images—raising privacy concerns as it's enabled by default. The model is directly accessible in Meta AI, Instagram, and WhatsApp, leveraging Meta's vast user base for distribution rather than competing solely on image quality. Accompanying Mango is the preview of Muse Video, a video generation model with integrated audio, currently ranked third in its category. All Mango-generated images include an invisible, persistent watermark (Content Seal) for AI identification, alongside a public detection tool. While Mango advances "thinking" image models, its use of social data poses new ethical questions about consent and digital boundaries.

marsbit1 год тому

Zuckerberg's 'Mango' Image Generation Model Trails Only GPT Image 2, It Learned to Revise Prompts on Its Own

marsbit1 год тому

Weng Li's New Blog Proposes 'Self-Evolution Should Start from Harness', DeepSeek's Cui Tianyi Endorses with Repost

Lilian Weng, former OpenAI security VP and co-founder of Thinking Machines Lab, has published a new blog post titled "Harness Engineering for Self-Improvement," proposing a pragmatic path for AI self-evolution. She argues that Recursive Self-Improvement (RSI) may practically begin at the "Harness" layer—the external runtime system governing how models use tools, manage context, and execute tasks—rather than directly from the model rewriting its own weights. The blog outlines a progression from optimizing prompts (Context Engineering) to designing workflows, and ultimately to Self-Improving Harness systems. These systems can identify their own weaknesses, propose targeted, verifiable modifications to the harness code, and validate improvements. Works like Self-Harness and Darwin Gödel Machine (DGM) demonstrate significant performance gains on benchmarks like SWE-bench through such automated harness evolution, rivaling handcrafted agents. DeepSeek researcher Tianyi Cui endorsed the view, noting harness-based self-evolution is as promising as model-based approaches. Weng emphasizes this is complementary to model training, with both reinforcing each other. However, key challenges remain: weak evaluators for subjective tasks, reward hacking, diversity collapse, managing long-term system health versus short-term success, and defining the human oversight role. The consensus is growing: the harness is a critical variable, as the same model can exhibit vastly different capabilities within different harness systems.

marsbit1 год тому

Weng Li's New Blog Proposes 'Self-Evolution Should Start from Harness', DeepSeek's Cui Tianyi Endorses with Repost

marsbit1 год тому

Russia Advances Crypto Bill After Removing Wallet Address Disclosure Requirement

Russia's State Duma Financial Markets Committee has adopted a revised cryptocurrency regulation bill. A key change removes the controversial requirement for users to disclose their wallet addresses. Instead, the new bill mandates reporting of wallet balances and transaction volumes. The legislation aims to expand investment opportunities, allowing retail investors to allocate up to 300,000 rubles annually into approved cryptocurrencies through intermediaries. It also permits licensed brokers to access select foreign exchanges. However, the bill imposes restrictions, including limits on certain international crypto transfers and a continued ban on domestic crypto payments except for foreign trade. Furthermore, cryptocurrencies will be legally recognized as property in cases like insolvency. The Bank of Russia retains its role in licensing market participants and is advancing its digital ruble project.

TheNewsCrypto1 год тому

Russia Advances Crypto Bill After Removing Wallet Address Disclosure Requirement

TheNewsCrypto1 год тому

Торгівля

Спот
活动图片