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first_img Celsius v. Chainalysis most charges dismissed, one incitement charge allowed to proceed

According to Cointelegraph, a U.S. federal judge dismissed most of the claims made by the Celsius litigation administrator against the blockchain analytics company Chainalysis, but allowed one to proceed.U.S. District Judge Margaret Garnett of the Southern District of New York ruled on Tuesday, rejecting Chainalysis's request to dismiss the incitement charge, determining that the complaint sufficiently alleges that Chainalysis was aware that a press release issued by Celsius in 2020 contained false statements and assisted in disseminating that information.The court simultaneously dismissed 12 other claims with prejudice, prohibiting the plaintiffs from amending in this case; another 3 consumer protection claims were dismissed without prejudice, requiring the plaintiffs to amend or notify the court by October 20.The lawsuit was initiated by the Blockchain Recovery Investment Consortium (BRIC), which acts as the litigation administrator and claims manager for Celsius's bankruptcy estate, representing Celsius and some former clients in asserting rights. Chainalysis declined to comment to Cointelegraph.The core of the case revolves around a $3.3 billion "audit." In 2020, Celsius used Chainalysis's Reactor software to calculate its managed asset size and publicly announced the results as an audit.According to the complaint outlined by the court, a Celsius executive initially calculated approximately $1.18 billion in assets using Reactor, which later increased to about $3.3 billion due to adjustments in methodology.

The Inner Mongolia police in China are investigating a virtual currency money laundering case that used "free credit card repayment" as bait, involving nearly a thousand accounts

Recently, the police in Baotou, Inner Mongolia, China, investigated a virtual currency money laundering case. The criminal gang used "free credit card repayment" as bait to attract ordinary users to provide accounts. They received illicit funds from overseas gambling and fraud through false consumption, then contacted currency dealers to exchange for virtual currency and transferred it to designated addresses abroad. Through financial and on-chain data analysis, the police identified nearly a thousand involved accounts, with suspects distributed across Inner Mongolia, Shandong, Jiangsu, Hebei, Chongqing, and other regions.The Digital Currency Research Institute of the People's Bank of China stated that it is currently using large model technology to analyze the flow of funds in virtual currency transactions, restore the gang's trading patterns, and uncover clues related to illegal industries. Upon investigation, it was confirmed that seven members of the gang were illegally engaged in payment settlement business without approval from relevant national authorities, constituting the crime of illegal operation, and were sentenced to imprisonment ranging from one year and two months to two years and six months, along with fines.Using virtual currency for money laundering is a new type of money laundering crime that has emerged in recent years. Lv Wei, the president of the Inner Mongolia branch of the People's Bank of China, stated that enhancing the monitoring and identification capabilities for abnormal fund transactions related to virtual currency trading has helped successfully crack down on a major money laundering case involving virtual currency pyramid schemes, dismantling more than ten money laundering and points-running dens, and confiscating illegal gains of approximately 130 million yuan. In recent years, there have been coordinated efforts to promote the conviction and sentencing of four cases involving money laundering using virtual currency, forming a strong deterrent against illegal activities such as money laundering with virtual currency.

first_img DeepSeek open-source Ascend basic components, covering compilation, computation, and communication libraries

The artificial intelligence company DeepSeek has officially open-sourced infrastructure components for the Huawei Ascend computing platform, covering the TileLang high-level language compilation tool, computing libraries, and distributed communication libraries, corresponding to the previously open-sourced components for the NVIDIA platform. TileLang aims to provide a general-purpose, simpler programming language that can achieve the hardware performance limits, improving development efficiency and simplifying logic compared to CUDA, while its programming model can also leverage chip features.The TileLang route was first validated on the NVIDIA platform and has already supported the implementation of most operators in the training of the DeepSeek V4 series models. The open-sourced Ascend version encapsulates the underlying instructions of the Ascend C, providing a high-level programming approach without sacrificing hardware performance. Currently, every TileLang operator used in DeepSeek's training has a corresponding high-performance implementation on Ascend.The components open-sourced at the same time also include DeepGEMM, DeepEP, TileKernels, FlashMLA, and DeepSelect, which are used for general matrix operations, large-scale cross-device communication, conventional vector calculations and memory access, long-context sparse attention, and data filtering, respectively. DeepSeek claims that in multiple key tests, the related computing and communication performance has approached hardware limits; during the R&D process, the Huawei team provided support, and both parties collaborated to advance the 128-card supernode solution based on Ascend 950, with deep optimizations made for computing and communication.
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