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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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first_img OpenAI claims to have solved over 100 long-standing open problems in the majority of mathematical fields

OpenAI announced the establishment of an independent advisory group on mathematics and artificial intelligence in collaboration with mathematicians, hosted by the Institute for Advanced Study in Princeton. OpenAI stated that its new internal model, which began training on August 28, has solved the Navier-Stokes Millennium Prize Problem and addressed over 100 long-standing open problems in most areas of mathematics, with progress that surprised its internal mathematicians.The group will provide advice on the review and dissemination of emerging results, academic and professional standards in mathematical research, and how OpenAI tools can support mathematical research and learning. Initial members include François Charles, Camillo De Lellis, Timothy Gowers, Martin Hairer, Nikhil Srivastava, Ulrike Tillmann, Ravi Vakil, Edward Witten, and Melanie Matchett Wood.The group operates independently of OpenAI, and members are not compensated by OpenAI; they can proactively provide advice, comment on its impact on mathematics, and make public recommendations. Previously, mathematicians expressed concerns in an open letter titled "A Severe Misalignment of AI in Mathematics" regarding the use of solving open problems as a benchmark for AI. The group is not responsible for providing advice on the pace of OpenAI's internal mathematical progress.

first_img Justin Sun: Establish the Justin Sun Prize to reward mathematically verified proofs

The founder of TRON, Justin Sun, announced the establishment of the "Justin Sun Award," which currently focuses only on mathematics. He stated that the award follows the problem rather than the individual, with no annual meeting, nominations, or age restrictions; each problem has two columns for signatures, one for the prover and one for the person who formalizes the proof and writes it into the machine. Both can be the same person, or they can be a person, AI, or a person using AI. The condition for triggering the prize is that the machine verifies the proof from the first line to the last line without error. Once verification is passed, the names in the two columns become the prize owners for that problem.The rules also include: before machine verification, if the mathematical community has accepted a human proof, it can be listed first, with the prize remaining unchanged, and the status being "Proven, awaiting formalization." The prize in the proof column is only awarded to problems that are solved after being listed; for problems that were already solved at the time of listing, the prover is still credited, but the prize is only awarded to the person who completes the formalization, not retroactively for the history of mathematics. The list of problems is determined by Justin Sun's signature for the listed problems and pricing; once listed, the price can only increase, and money can only be exchanged, not refunded. Mistakes in the problems will still be paid, and they will be re-listed afterward; beyond pricing, verification, payment, and naming, he does not participate in voting.Justin Sun stated that the focus of public welfare will shift to this award, with the initial prize pool already deposited into the blockchain, with the address and balance made public. He only retains the right to continue injecting funds; the award proof and prize distribution will also be made public on the chain. He mentioned that naming it after a person is to avoid name changes due to institutional changes and expressed that wealth comes from mathematics, hoping to "come from mathematics and return to mathematics."
2026-09-16

Coldcard has suspended the automatic deletion of customer data due to a security incident and will retain relevant records in accordance with the law

The cryptocurrency hardware wallet manufacturer Coldcard has released an update on its customer data retention policy. Due to legal compliance requirements arising from the security incident disclosed on July 30, the company has temporarily suspended its original automatic customer data deletion mechanism.Previously, Coldcard's standard practice was to automatically clear customer records after 120 days, retaining only the user's email address and country information, while allowing customers to request early deletion of data at any time after product delivery. Coldcard stated that due to the security incident involving ongoing and potential legal proceedings, the company is obligated to retain records that may be relevant to litigation. Therefore, customer data that was originally scheduled for deletion will be temporarily retained until the law permits the resumption of normal processes.However, users can still request Coldcard to handle their personal information according to the original data retention policy. If users wish for their data not to be included in this legal retention scope, they can contact official customer service to make a request. Coldcard emphasizes that the retained data will be strictly protected, accessible only to authorized personnel, and will not be used for any purposes other than fulfilling legal obligations. The company will restore the previous automatic data deletion mechanism once legally permissible.

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.
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