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first_img Bit2Me established Bit2Shield to assist law enforcement in tracking cryptocurrency assets

Spain's largest cryptocurrency exchange Bit2Me announced the establishment of an independent company Bit2Shield (registered name CryptoShield S.L) to assist courts, police, and financial institutions in tracking, seizing, storing, and selling cryptocurrency assets. This department will support investigators in extracting wallet data, locating cryptocurrency assets, and issuing digital signature forensic reports that can be used in court, while also being responsible for fraud investigations, source of funds verification, and providing training for police, judges, and banks.This move formalizes the work Bit2Me previously conducted for public institutions. In 2025, Bit2Me handled seized cryptocurrency assets worth 1.5 million euros (approximately 1.74 million dollars) for Interpol, Europol, and the Spanish police, using blockchain analysis company Chainalysis to track the assets. Bit2Shield will store seized assets in cold wallets that require multiple signatures and arrange for their sale when ordered by authorities, with proceeds transferred to government bank accounts in euros.Bit2Shield is part of Bit2Me's expansion from retail trading to banking and public institution infrastructure, with investors including Bankinter, Unicaja, Cecabank, Telefónica, and Tether. Since Bit2Shield focuses on investigations, forensics, and training, it is not considered a cryptocurrency service provider under the EU's Markets in Crypto-Assets Regulation (MiCA); any operations involving the exchange of cryptocurrency for euros will be handled by Bitcoinforme S.L., an entity authorized by the Spanish securities regulator MiCA under Bit2Me.

Apple faces a $2.7 billion class action lawsuit: accused of unfair application tracking rules against third-party developers, gaining improper advantages in its own advertising ecosystem

According to a report by Reuters, Apple Inc. is facing a class-action lawsuit in London, with claims amounting to £2 billion (approximately $2.7 billion). The lawsuit was filed today in the London Competition Appeal Tribunal by Ann Pope, a former senior official of the UK's Competition and Markets Authority, representing app developers.The core allegation is that Apple's "App Tracking Transparency" (ATT) feature, launched in 2021, imposes stricter restrictions on third-party developers than on its own services, giving Apple's own advertising ecosystem an unfair competitive advantage. Ann Pope stated that Apple's policies "have caused very significant harm to businesses that rely on Apple as a gatekeeper."Since its launch, the ATT feature has been a focal point of concern for global regulators for several years. Apple's official stance is that the feature is designed to allow users to control whether to permit apps to track their activities across other companies and websites.However, the plaintiffs argue that the actual enforcement of this rule has a double standard—tracking requests from third-party apps require strict pop-up authorization, while Apple's own personalized ads and services can bypass the same restrictions. This lawsuit represents the latest legal challenge Apple faces regarding its ATT policy and is the first large-scale private antitrust lawsuit initiated in the UK market against Apple's app ecosystem rules following scrutiny from regulators in the EU, the US, and several other countries.

first_img Google claims that the cost of AI server memory has exceeded 75%, promoting a dual-track strategy for software and hardware

The SEMICON Taiwan 2026 Memory Summit took place on the 1st, where Nikhil Cherian, Senior Director of Supply Chain Infrastructure at Google Cloud under Alphabet, pointed out that with the popularity of multimodal and mixed expert architectures, AI computation has shifted from being power-limited to memory-limited, with high-performance memory accounting for over 75% of the cost of AI server hardware bill of materials. In the face of capacity, bandwidth, and power consumption bottlenecks, Google is breaking through the AI memory bottleneck through a dual-track strategy of hardware offloading for inference and training, and lossless quantization software algorithms.Google adopts an offloading strategy in hardware architecture, launching TPU 8i for low-latency inference and TPU 8t specialized for large-scale training. The TPU 8i is equipped with 288 GB of high-bandwidth memory, with SRAM capacity on the chip increased threefold to 384 MiB, placing dynamic conversation states and key-value caches on the chip itself to achieve zero chip-off latency. The TPU 8t forms a super-large computing cluster with 9600 chips, achieving a shared pool of HBM at a scale of 2 PB, eliminating chip-off data transfer bottlenecks, along with TPU Direct Storage technology.Google has developed the training-free TurboQuant lossless quantization algorithm, compressing the key-value cache of large models from 32 bits to 3 bits, reducing memory usage by six times without loss of accuracy, resulting in an eightfold acceleration in attention computation, and integrating old-generation DRAM technology to extend the lifecycle of components.

LeapNode receives investment from DraperDragon, laying out the Web3×AI infrastructure track

Recently, the AI computing power Token aggregation trading platform leapnode.net announced that it has received investment from the well-known cryptocurrency investment institution DraperDragon. This investment marks a strategic consensus between the two parties in the integration of AI and Web3, aiming to consolidate ecological resources, seize the wave of AI Agent development, and explore the new generation of AI-Web3 infrastructure market, fully reflecting the capital market's recognition of the opportunities and potential of this sector.LeapNode believes that the computing power Token aggregation trading platform for AI is equivalent to trading platforms for Web3. The platform first connects to over 200 cutting-edge AI models through a single API Key, with pricing at 10-30% of the official rates, service availability at 99.9%, and new models quickly launched within 48 hours. To lower the usage threshold, LeapNode has launched ready-to-use Web3 smart assistants and the Mystery Calculation Master, which have received numerous positive reviews, and introduced computing power boxes to allow users to participate in sharing platform profits. The project's vision is to connect models with user Agents and extend the A2A economy, providing support for autonomous payment settlement for AI agents and creating a core settlement layer for the AI Agent ecosystem.

The chairman of the U.S. SEC plans to restructure the securities regulatory tracking system CAT and explore the possibility of the SEC taking over and reforming the funding mechanism

Chairman Paul S. Atkins of the U.S. Securities and Exchange Commission (SEC) wrote to Robert Walley, Chairman of the Consolidated Audit Trail (CAT) Operating Committee, indicating that the SEC plans to undertake a comprehensive reform of the CAT system, including adjustments to its governance structure, funding sources, and operational model.Atkins stated that during his tenure, the SEC has significantly reduced the annual operating costs of CAT by issuing exemptions and approving amendments to the CAT NMS plan, and has eliminated the requirement to report personally identifiable information (PII) to the CAT system.These reforms have lowered system costs and the scope of data collection, but CAT still faces fundamental issues regarding costs, governance, and funding mechanisms. To address these issues, the SEC released a concept request for comments on April 16, 2026, to conduct a comprehensive review of CAT and other audit trail systems and data sources used in the regulation of U.S. securities markets.The SEC indicated that it has received hundreds of feedback comments, with one core consensus being that investors and market participants want the SEC to take more responsibility for the management and funding arrangements of CAT.Atkins stated that he has asked SEC staff to propose deep reforms for CAT, including: 1. Exploring new funding sources for CAT, including the use of congressional appropriations and transaction fees under Section 31 of the Securities Exchange Act; 2. Drafting rule proposals that, if approved, would repeal Rule 613 and require exchanges, FINRA, and broker-dealers to continue using the existing CAT infrastructure and reporting standards to submit CAT data directly to the SEC or its designated agency; 3. Assessing the internal resource needs of the SEC to prepare for the SEC's future assumption of governance responsibilities for CAT.The SEC expects that this reform will involve multiple stages and will need to be advanced simultaneously, with the overall transition potentially lasting until the end of 2027.
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