Американский регулятор отказался преследовать основателя Hex Ричарда Харта

investing.ruPublicado a 2025-04-23Actualizado a 2025-04-23

Харт опубликовал в соцсети Х письмо регулятора, адресованное окружному судье Нью-Йорка Кэрол Бэгли Амон (Carol Bagley Amon). Ведомство уведомило суд, что не намерено подавать жалобу против Харта, тем более, что срок подачи уже истек.

В июле 2023 года SEC подала в суд на Харта, обвинив его в привлечении более $1 млрд посредством предложений незарегистрированных ценных бумаг, которыми, по мнению ведомства, являлись криптовалюты Hex (HEX), PulseChain (PLS) и PulseX (PSLX). Харт также обвинялся в растрате клиентских средств на предметы роскоши и автомобили класса люкс.

В марте суд отклонил жалобу SEC, поскольку Комиссия не смогла доказать, что действия Харта были направлены против американских инвесторов. Регулятору было разрешено подать измененную жалобу в течение 20 дней, однако он решил прекратить дело.

«PulseChain, PulseX и HEX полностью победили SEC и добились нормативной ясности, которой не достигли почти никакие другие монеты. Это победа программного обеспечения с открытым исходным кодом, криптовалют и свободы слова. SEC фактически подала в суд на сам программный код. Это дело могло бы создать ужасный прецедент и нанести многомиллиардный ущерб криптоиндустрии», — написал Ричард Харт в Х.

Несмотря на то, что Харт «вышел из поля зрения» SEC, он все еще находится в «красном списке» Интерпола. Харт попал туда в декабре 2024 года, когда финские власти добивались его ареста по обвинению в уклонении от уплаты налогов. Харт все еще фигурирует в списке самых разыскиваемых преступников Европы.

При новой администрации Дональда Трампа и после ухода бывшего председателя SEC Гэри Генслера (Gary Gensler) американский финансовый регулятор завершил несколько громких дел против криптокомпаний, включая Coinbase (NASDAQ:COIN), Kraken и Consensys.

Читайте оригинальную статью на сайте Bits.media

Lecturas Relacionadas

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.

marsbitHace 38 min(s)

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

marsbitHace 38 min(s)

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.

marsbitHace 2 hora(s)

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

marsbitHace 2 hora(s)

Trading

Spot
Futuros
活动图片