U.S. Court Greenlights Binance’s $2.7B Settlement With CFTCCrypto Daily

cryptodailyPublicado em 2023-12-12Última atualização em 2023-12-19

Resumo

Among the stipulations imposed on Binance, the court order dictates that the exchange will no longer permit existing sub-accounts, including those opened by prime brokers, to bypass the platform’s compliance controls. Additionally, the ruling requires the company to offboard every account failing to meet proper KYC compliance requirements. 

Table of Contents

As per the terms of the settlement, former Binance CEO Changpeng “CZ” Zhao will be shelling out $150 million, while Binance will pay $2.7 billion to end the CFTC enforcement action.
Settlement Breakdown
In a significant development, the U.S. District Court for the North District of Illinois has officially approved the settlement between the Commodity Futures Trading Commission (CFTC) and cryptocurrency exchange Binance and former CEO Changpeng Zhao. 
The CFTC disclosed in a press release on December 18 that the court issued a consent order encompassing a permanent injunction, civil monetary penalty, and equitable relief against Binance and Zhao.
According to the court's ruling, Zhao is obligated to pay a hefty $150 million civil monetary penalty to the CFTC. Simultaneously, Binance is mandated to make two payments, each of $1.35 billion, to serve as a refund and penalty to the CFTC. This settlement comes in response to the court's determination that Zhao and Binance flagrantly violated the Commodity Exchange Act (CEA) and CFTC regulations.
Court Findings 
The court's findings highlight that Binance, under Zhao's direction, actively solicited customers in the United States, including quantitative trading firms. Notably, these customers engaged in digital asset derivative transactions directly on the Binance platform. 
Furthermore, the court revealed that Binance, in defiance of its own Terms of Use, permitted at least two prime brokers to establish "sub-accounts" exempt from Binance's know your customer (KYC) procedures. This enabled U.S. customers to directly trade on the platform, a clear violation of regulatory standards.
Resolutions and Acknowledgment
In a blog post dated November 21, the Binance team announced that it had been able to reach resolutions with various regulatory entities, including the CFTC, Department of Justice, Office of Foreign Assets Control, and Financial Crimes Enforcement Network. 
The post also disclosed that Zhao, Binance's founder and CEO, agreed to step down and plead guilty to violating criminal anti-money laundering requirements. The team, in a candid admission of fault, stated, 
"Binance grew at an extremely fast pace globally, in a new and evolving industry that was in the early stages of regulation, and Binance made misguided decisions along the way. Today, Binance takes responsibility for this past chapter."

Compliance Measures
Among the stipulations imposed on Binance, the court order dictates that the exchange will no longer permit existing sub-accounts, including those opened by prime brokers, to bypass the platform’s compliance controls. Additionally, the ruling requires the company to offboard every account failing to meet proper KYC compliance requirements. 
Furthermore, Binance and Zhao are obligated to certify the implementation of a corporate governance structure, including a Board of Directors with independent members, a Compliance Committee, and an Audit Committee.

Leituras Relacionadas

Just now, DeepSeek V4 updates with DSpark, improving inference speed by 80%

DeepSeek has updated its DeepSeek V4 model with the DSpark speculative decoding framework, achieving a significant 60-85% speedup in generation for Flash models and 57-78% for Pro models while maintaining the same overall throughput. This engineering-focused update, rather than a core architectural change, introduces DSpark to address latency and throughput bottlenecks in high-concurrency production environments. DSpark combines high-throughput parallel generation with adaptive load-aware verification. Its key innovations include a semi-autoregressive generation architecture to model dependencies within token blocks and a hardware-aware confidence-scheduled verification system. This system uses a confidence head to predict token acceptance probabilities, allowing it to dynamically optimize verification length per request and allocate compute only to tokens with the highest expected payoff. The asynchronous scheduler is designed for real-world deployment, ensuring zero-overhead scheduling and continuous CUDA graph replay while preserving the target model's output distribution. In tests across mathematical reasoning, code generation, and daily dialogue, DSpark outperformed state-of-the-art models like Eagle3 and DFlash, increasing average acceptance length by 26.7%-30.9% and 16.3%-18.4% respectively on Qwen3 target models. DeepSeek also open-sourced DeepSpec, a full-stack codebase for training and evaluating speculative decoding draft models, providing a standardized toolkit that includes data preparation tools, model implementations, training code, and evaluation scripts.

marsbitHá 4h

Just now, DeepSeek V4 updates with DSpark, improving inference speed by 80%

marsbitHá 4h

BIT Research: The 2028 Halving Is Not the End, the Real Shake-Up of the Bitcoin Mining Industry Is Just Beginning

The Bitcoin mining industry is undergoing its most complex structural adjustment since inception. Despite Bitcoin's price holding near $61,000 and the network hash rate approaching a record 1 ZH/s, miner profitability is deteriorating. The industry is operating close to its breakeven point, with the 2028 halving expected to accelerate consolidation. The challenges extend beyond the halving's subsidy reduction; the industry's revenue model has yet to successfully transition towards a fee-driven structure. Increasingly, mining companies are evolving from simple Bitcoin producers into infrastructure and energy operators, including providers of AI/HPC computing power. Competition is shifting from pure hash rate expansion to business model upgrades. Economic pressure is evident. The theoretical daily mining revenue at current prices is around $78 million, yet the actual figure is only about $33 million—a 136% gap. Transaction fees remain low at roughly $220k daily, far below historical implied levels. With a current estimated industry-wide breakeven price near $65,000, mining alone is struggling to generate ideal profits. The 2028 halving is projected to push the fundamental production cost floor to approximately $93,289. This will likely accelerate a shift towards consolidation among larger, well-capitalized miners with diversified revenue streams. Competitive advantage will belong to institutionalized players with access to low-cost energy, AI/HPC hosting operations, and stronger balance sheets. In essence, Bitcoin mining is transitioning from a "mining business" to an "infrastructure business." Future profitability and resilience will depend less on block rewards and more on diversified income sources like energy management and computational infrastructure services. For investors, the key question is not the halving itself, but which miners can successfully navigate this business model transformation.

marsbitHá 5h

BIT Research: The 2028 Halving Is Not the End, the Real Shake-Up of the Bitcoin Mining Industry Is Just Beginning

marsbitHá 5h

This is How God Karpathy Uses Claude?

Andrej Karpathy, a prominent figure in AI, has reportedly joined Anthropic, leading to a noticeable decrease in his open-source contributions and social media activity. A document claiming to be his personal "CLAUDE.md" file—a set of instructions for the Claude AI to follow within a specific codebase—has been circulating online. While its authenticity is unverified, the content aligns closely with Karpathy's publicly shared principles on effective AI-assisted programming. The document outlines key rules for AI coding assistants, emphasizing the importance of reading existing code thoroughly before writing new code to maintain consistency. It advises against over-engineering, advocating for simple, surgical modifications that match the project's existing style. Other guidelines include clarifying assumptions upfront, writing meaningful tests, thoughtful debugging, and carefully considering dependencies. The core message is that these principles help prevent common AI coding failures, such as introducing unnecessary abstractions, style drift, or making invisible architectural decisions. The community has noted that even experts like Karpathy require detailed instructions to guide AI effectively, akin to managing a junior developer. A related GitHub repository, "andrej-karpathy-skills," which encapsulates these ideas, is reported to significantly reduce Claude's code error rate. Ultimately, the advice stresses that the best CLAUDE.md is tailored to one's own tech stack and coding practices.

marsbitHá 5h

This is How God Karpathy Uses Claude?

marsbitHá 5h

Trading

Spot
活动图片