Mango Рынки обдумывает урегулирование CFTC в связи с нарушениями в сфере торговли Криптo

cryptonews.ruPubblicato 2023-08-23Pubblicato ultima volta 2024-09-23

Децентрализованная Криптo Mango Рынки уже пережила изнурительную многомиллиардную атаку и дорогостоящие регуляторные расследования, которые она повлекла за собой. Группа может вскоре получить еще один удар: шестизначное урегулирование с Комиссией по торговле товарными фьючерсами (CFTC).

Криптo деривативный торговый центр сталкивается с обвинениями CFTC в том, что он якобы не зарегистрировался в качестве товарной биржи, незаконно предлагал услуги клиентам из США и не проверял личности своих клиентов, согласно заявлениям на сервере Discord и предложению на странице управления. DEX позволяет пользователям торговать бессрочными фьючерсными контрактами.

В воскресенье юридический представитель Mango Рынки раскрыл расследование и предложил резолюцию : руководящий орган биржи Mango DAO выплатит CFTC штраф в размере 500 000 долларов. Mango DAO не признает и не отрицает никаких правонарушений, но избежит предстоящего судебного разбирательства.

Урегулирование T решено. Оно все еще должно быть одобрено держателями токена управления Mango Рынки, MNGO. На момент публикации предложение было практически готово к одобрению. Как только это препятствие будет преодолено, предложение об урегулировании также должно быть принято комиссарами CFTC.

Mango DAO уже ездила на этом регуляторном поезде боли раньше . Буквально в прошлом месяце она проголосовала за предложение шестизначной компенсации Комиссии по ценным бумагам и биржам. Позже она отправила почти $700 000 в стейблкоинах для покрытия «штрафа», возникшего из-за обвинений в продаже MNGO в качестве незарегистрированной ценной бумаги.

ONE месяц до того, как крах FTX в ноябре 2022 года опустошил биржи DeFi на Solana, Mango Рынки потерпела собственную катастрофу . Самопровозглашенный теоретик игр Ави Айзенберг провернул «высокоприбыльную» рыночную манипуляцию, которая уничтожила активы биржи и в конечном итоге привела его в тюрьму.

Хотя Mango Рынки вернула часть своих денег от Айзенберга, она так и не оправилась от удара ни финансово, ни репутационно. Событие также привлекло внимание нескольких американских регуляторов, включая CFTC.

Согласно сообщению на сервере Discord от юридического представителя Mango DAO, компания потратила 148 176 долларов США на судебные издержки и более 78 000 долларов США на дополнительные расходы, связанные с преодолением возникших юридических проблем.

CFTC не отреагировала на запрос CoinDesk немедленно.

Letture associate

Introduction to the Concept of World Models: A Story from Psychology to the Main Battlefield of AI

**World Models: From Psychology to AI's Core Concept** "World model" is a trending but often confusing term in AI, describing a system that allows machines to internally simulate, predict, and rehearse potential outcomes before taking real-world action—like a mental "sandbox." While definitions vary—Yann LeCun emphasizes physical understanding, OpenAI's Sora is a video-based "world simulator," Google DeepMind's Genie 3 creates interactive 3D environments, and companies like Alibaba and Tesla focus on practical applications—the core goal is consistent: reduce reliance on vast real-world data by creating an internal, predictive model for safer and more efficient AI. The concept has deep roots, tracing back to psychologist Kenneth Craik (1943). In AI, it was revitalized by researchers like David Ha and Jürgen Schmidhuber (2018). Major technical approaches include: 1) generative video models (e.g., Sora) for visual realism; 2) abstract predictive models (e.g., LeCun's JEPA) for efficiency and physical reasoning; and 3) explicit 3D simulators (e.g., NVIDIA Omniverse) for precision. Fei-Fei Li proposes a classification based on the AI action loop: renderers (output observations), simulators (output world states), and planners (output actions). The emerging "World Action Model" (WAM) paradigm aims to unify future prediction and action generation. An industry framework is forming: upstream (data, compute, sensors), midstream (general and vertical platforms), and downstream applications (autonomous driving, robotics, gaming, etc.). Autonomous driving is currently the most mature use case. The current lack of a unified definition reflects the field's early, dynamic stage, similar to past tech revolutions. Different approaches—focusing on pixels, physics, or behavior—represent parallel explorations of how best to compress and understand the world. This diversity, while seemingly chaotic, signals that world models have moved from an academic idea to a critical industrial battleground, ultimately aiming to give machines the ability to understand, imagine, and reason about the world.

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Introduction to the Concept of World Models: A Story from Psychology to the Main Battlefield of AI

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Building the Bright Path While Secretly Crossing Chencang: Is Walsh Paving the Way for a September "Rate Cut"?

The title "Building the Plank Road Openly While Secretly Crossing at Chencang: Is Walsh Paving the Way for a September 'Rate Cut'?" suggests Federal Reserve Chair Kevin Walsh's hawkish stance may be a deliberate smokescreen. Academy Securities analyst Peter Tchir argues in a report that markets, currently pricing a 75% chance of a September hike, are missing a potential path to a September rate cut that Walsh himself might be quietly preparing. Tchir posits that Walsh's hawkish rhetoric aims to suppress long-term yield risks (with the 10-year Treasury yield falling recently) while creating room for a narrative shift based on upcoming data. The potential political endgame, according to this view, could be rate cuts in September and October, ahead of the midterm elections. This hinges on a political logic where the Trump administration's preference for lower rates remains unchanged. A core part of Tchir's argument involves redefining inflation metrics. He contends the Fed under Walsh may deprioritize the PCE index, criticizing its lagging components like Owners' Equivalent Rent (OER). Instead, he points to alternative, more real-time indicators like the New Tenant Repeat Rent Index (NTRR) and the Truflation daily index, which shows core inflation around 1.45%. He suggests the Fed could shift its data narrative to justify policy easing. Furthermore, Tchir downplays AI-driven inflation fears. He argues that consumer price sensitivity, evidenced by negative market reactions to price hikes (e.g., Apple), contradicts persistent inflation narratives. He also separates AI/data center spending—which he sees as relatively rate-insensitive—from broader consumer affordability issues, implying rate hikes are misdirected. Based on this analysis, Tchir sees a re-pricing of rate cut expectations as likely, creating opportunities in short-duration Treasuries. He maintains a neutral-to-slightly-bullish view on the long end of the yield curve. For equities, he recommends a significant overweight in energy (especially global nuclear assets) and, within defense/security themes, an overweight in biotech/pharma versus an underweight in semiconductors, expressing caution on AI/data center valuations.

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Building the Bright Path While Secretly Crossing Chencang: Is Walsh Paving the Way for a September "Rate Cut"?

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"King of Shilling" Hayes Strikes Again, This Time Setting His Sights on Deribit

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"King of Shilling" Hayes Strikes Again, This Time Setting His Sights on Deribit

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