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BTC $64,763.27 +1.21%
ETH $1,919.07 +1.56%
BNB $587.49 +3.58%
XRP $1.08 +1.55%
SOL $74.63 +2.04%
TRX $0.3282 +0.60%
DOGE $0.0704 +0.53%
ADA $0.1699 +4.40%
BCH $218.35 +3.95%
LINK $8.48 +2.61%
HYPE $53.83 -1.94%
AAVE $98.61 +0.48%
SUI $0.6953 +1.72%
XLM $0.1723 -0.06%
ZEC $474.63 +2.72%

matic

Matic Network, now renamed Polygon, is an Ethereum scaling solution aimed at improving Ethereum's performance by providing scalable, low-cost transactions. Polygon utilizes sidechain technology and the Plasma framework to support fast, low-fee transaction processing while maintaining interoperability with the Ethereum mainnet. Its core features include support for multi-chain architecture, compatibility with the Ethereum Virtual Machine (EVM), and providing developer-friendly SDKs to help developers build high-performance decentralized applications (DApps). As the "Internet of Blockchains" for Ethereum, Polygon has significant influence in the decentralized finance (DeFi) and NFT sectors.
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hot_img OpenAI's internal model has been revealed to autonomously solve mathematical problems and bypass the sandbox, with internal testing exceeding two months

According to external disclosure information, OpenAI has been internally running an unreleased model. This model, without the aid of tools like Lean, solves the unit distance problem with a 48% probability through a single autonomous inference and can independently find a counterexample to the Jacobian conjecture based on a single prompt. In security testing, this model has bypassed the sandbox environment and submitted results that should have been released internally to GitHub in the form of a Pull Request, and it has evaded detection by splitting authentication tokens. Relevant code records show that OpenAI began benchmarking this model no later than May 9, and its internal availability has exceeded 2.5 months.Previously, OpenAI and Hugging Face jointly disclosed that last week this model breached Hugging Face's production infrastructure during a network capability assessment. The model gained internet access through a zero-day vulnerability and obtained testing solutions by stealing credentials and exploiting remote code execution paths. OpenAI stated that this incident indicates the network attack capabilities of advanced models have been effective in real-world scenarios, and they are collaborating with Hugging Face to investigate and patch the vulnerabilities. Currently, OpenAI has not publicly commented on this matter.

The Supreme Procuratorate issued a document: Systematically breaking through the threefold dilemma of using virtual currency for money laundering regulation in criminal law

According to a report by the Procuratorial Daily, researchers from the People's Procuratorate of Yuhu District, Xiangtan City, Hunan Province, and the Law School of Xiangtan University have jointly written an article proposing a systematic response plan to the regulatory dilemmas of money laundering crimes using virtual currency. The article points out that current judicial practice faces three major dilemmas: first, Article 191 of the Criminal Law limits money laundering crimes to seven types of upstream crimes, resulting in many cases being treated as "concealment crimes"; second, methods such as mixers, privacy coins, and cross-chain transfers lead to fragmented evidence chains, making traditional investigative methods difficult to penetrate; third, conflicts in the legal attributes of virtual currency, a vacuum in procedural rules, and barriers to cross-border cooperation make it difficult to recover assets.In response, the article suggests promoting "dual investigations for one case," establishing the principle of self-authentication of blockchain data, constructing a tiered standard of proof, and establishing a national-level custody and disposal platform for involved virtual currencies, while actively promoting the signing of special agreements for international criminal justice assistance in virtual currency crimes.

Gate Pay for AI Agent has completed its upgrade, further connecting the automatic payment and execution chain for AI Agents

Gate announced the completion of a new round of product upgrades for Gate Pay for AI Agent and the launch of multiple new features, further enhancing the payment and automatic execution capabilities in AI Agent scenarios. This upgrade focuses on core capabilities such as service discovery, automatic payment, pay-per-use billing, high-frequency micro-payments, multi-wallet collaboration, and automatic settlement, further integrating the payment mechanism into the AI workflow.The upgrade emphasizes enhancing the service discovery and automatic payment capabilities of Gate Pay for AI Agent. Within the scope of user authorization, AI can automatically complete payments, signatures, and result retrieval based on payment requirements during the service invocation process, reducing the need for frequent user intervention and allowing complex tasks to be completed continuously within a unified process. At the same time, Gate Pay for AI Agent supports aggregated payments and automatic settlements for high-frequency, small-value calls, thereby reducing payment overhead and improving overall execution continuity, significantly enhancing execution efficiency and reducing transaction friction.In the future, Gate will continue to promote the capability development of Gate Pay for AI Agent in the directions of automated payments, on-chain settlements, and AI service collaboration, further connecting AI Agents, digital assets, and real commercial scenarios, providing more open and efficient infrastructure support for the next generation of AI-native economy.
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