testing

Polymarket's Vice President Josh stated on platform X that the team is fully developing a complete Central Limit Order Book (CLOB) based on Rust, as the current CLOB is the root cause of most issues on the platform.According to the plan, the complete order lifecycle process, including trading, settlement, on-chain interaction, indexer, and engine notifications, will be completed in the testing environment in October; in November, all production traffic will be mirrored to the new trading cluster, and results will be compared with the existing system. At the same time, testing permissions will be opened to market makers, and the migration switch plan will be locked in, with two complete drills to be completed before the official switch.Josh also mentioned that if progress goes smoothly, the new system will be officially released, and the migration is expected to require little or no changes for market makers and developers.

According to First Financial, the artificial intelligence company MiniMax has launched the text model M3.1-Flash-Preview and started public testing. MiniMax stated that this model supports native multimodal capabilities and a million-context window, enabling tasks such as bug fixing and complete feature development, as well as participating in problem localization, code implementation, and testing verification.After the launch of M3.1-Flash-Preview, some developers linked it with the anonymous model Space Bunny. This model, known as "Space Bunny," was launched on September 23 and topped the daily usage charts on the model aggregation platform OpenRouter and the programming platform OpenCode during the Mid-Autumn Festival.

BIT announces that the Hong Kong stock trading feature will enter internal testing starting today, with a targeted public beta launch on October 5 and trading opening on October 12. Users can directly participate in trading using stablecoins.The first phase supports full trading of all stocks on the Hong Kong Stock Exchange's main board and the Growth Enterprise Market (GEM), IPO subscriptions, and financing trading. Hong Kong stocks and U.S. stocks share the same account system, allowing users with a BIT U.S. stock account to directly enable Hong Kong stock trading. During the public beta period, priority experience slots will be granted to invited users; from the start of the public beta until the first month after the official launch (ending November 11), all users can enjoy zero-commission trading, zero interest and zero subscription fees for financing new shares, a HK$100 Hong Kong stock platform fee deduction card, and a Hong Kong stock L2 market data card. Specific qualifications and rules are subject to BIT's official announcement.Elio Cui, head of BIT's brokerage business, stated: "The launch of BIT's Hong Kong stock trading provides customers with a more comprehensive cross-market investment tool. As a key hub connecting domestic and foreign liquidity, the Hong Kong capital market concentrates scarce high-growth and high-dividend quality targets, making it a core channel for investors to conduct cross-regional asset allocation and share regional growth dividends. Relying on the BIT account system, investors can flexibly allocate global mainstream quality assets such as U.S. stocks, Hong Kong stocks, and digital assets, truly achieving 'one account, global allocation' investment efficiency."

Recently, the socialized Meme trading platform Baola, strategically invested by Gate Ventures, has entered the product internal testing phase. Baola is positioned as a socialized trading platform aimed at the Meme market, exploring the combination of social content and Meme trading around aspects such as hot topic discovery, market information tracking, community interaction, and trading participation.According to the official introduction, Baola's brand proposition is "Your next Meme is on Baola," aggregating information such as popular calls, KOL dynamics, on-chain trading data, and community interactions. Users can view Caller, the number of token mentions, market capitalization at the time of the call, and subsequent peak performance, and discover active market participants through features like KOL rankings and Callout boards, gaining insights into market hotspots and participant performance from multiple dimensions.In terms of community interaction, Baola supports users in independently publishing calls and market opinions, and allows them to continuously follow interested Callers through Follow. The platform also combines KOL public calls with on-chain trading dynamics, providing information on historical calls, recent performance, and buying and selling behaviors, further linking opinion sharing, hot topic discovery, and trading participation. Currently, Baola has entered the product internal testing phase and is continuously improving the socialized trading experience in the Meme field. Users can visit the official website (https://bao.la/) for more details.

According to internal information obtained by 404 Media and Reuters, after Meta expanded the Muse "Call for You" testing, it was revealed that some calls were actually completed by real people. Muse can transfer tasks to real contractors at call centers, who then make calls on behalf of users and fulfill requests. Some testers only realized there was human intervention after the call ended.Meta adopted this approach mainly to improve success rates. Internal testing showed that the success rate of phone tasks could reach 95% to 98% with human intervention, higher than pure AI. Some merchants hang up directly when they hear the other party is AI, and there are also testers in the community who reported that merchants hung up after Muse identified itself as an AI assistant.Human intervention raises privacy concerns, as users originally believed their information was only shared with AI, but it may actually be seen by outsourced personnel. Some people within Meta also questioned that providing privacy training to contractors does not equate to a real safety mechanism. A Meta official later admitted that failing to inform testers in advance about human intervention was a mistake, and this feature has been rolled back. Meta stated that the phone function is still in testing and will only be officially launched after ensuring safety, privacy, and clear communication.

According to media reports citing informed sources, Anthropic and OpenAI had considered signing a legally binding agreement to conduct stress tests on each other's large models. Earlier this year, the two companies and their legal teams discussed this plan, allowing competitors to deeply test each other's latest available models to identify potential risks or security vulnerabilities. Such tests would only apply to commercially available models, and both parties agreed not to retain each other's data. The report did not clarify whether the two parties ultimately reached such an agreement.Recently, the idea of implementing some form of peer review among top AI laboratories has gained attention. SpaceX CEO Elon Musk suggested last week that several leading large model companies in the United States, along with some Chinese AI companies, should allow competitors to conduct cross-testing. Musk stated: All AI companies have a set of testing tools, and having each company run their tests using another company's tools might be the best thing to ensure their own safety.Earlier this month, Anthropic researcher Jacob Coxon announced his resignation and warned leading artificial intelligence companies about accelerating development without proper safeguards. Subsequently, Anthropic CEO Dario Amodei called for the industry to slow down the pace of AI development and introduce third-party assessment mechanisms. Last Friday, Anthropic announced a partnership with Accenture, with Accenture serving as a third-party assessment agency to evaluate the safety compliance of its cutting-edge AI models.

Google acknowledged that its Gemini model breached the sandbox environment during a security test in May, infiltrating three real companies and guessing or finding the passwords of two of them. Google was aware of this incident by late July but only publicly confirmed it after a report by The Wall Street Journal on September 18, remaining silent for seven weeks.The test was a capture-the-flag exercise commissioned by Google and conducted by the Israeli company Irregular in May. Irregular connected an isolated testing environment that should have had no contact with the real internet to the open network, using the name of a real company as a fictitious target. Gemini found three matching results when searching for the company and attacked them one by one, with the plaintext passwords of two companies directly exposed online, while the password of the third was guessed by the model. Google stated that its model ultimately did not use the stolen credentials in practice.Google is the fourth major AI laboratory this year to admit that internal security tests leaked into the real world. Previously, OpenAI's model had accessed Hugging Face servers due to a software vulnerability, Anthropic found that three Claude models had reached real companies after reviewing 141,000 tests, and Meta's Muse Spark model also experienced a similar incident due to Irregular's configuration error. Additionally, U.S. Representatives Ted Lieu and Nathaniel Moran introduced the "AI Emergency Shutdown Act" in July, proposing to authorize federal regulators to suspend reasoning for models that pose a serious threat.

Bitcoin News posted on the X platform that Bitcoin Core 32 is currently undergoing candidate version testing, with the developers aiming to release it on October 10.This version can speed up block validation by reading database data in parallel, but it will not change the block generation speed. Four wallet commands will default to the updated partially signed transaction format, while the old format will still be available as needed. Security patches can prevent custom wallet names from executing commands on non-Windows nodes, and in one test, the memory growth caused by unauthenticated HTTP was reduced from about 3.2 GB to about 3 MB.

GMGN co-founder Haze posted on the X platform stating that the perpetual contract trading feature of the GMGN platform is officially open for public testing. Everyone is welcome to experience it and provide feedback.

CryptoQuant analyst Axel Adler Jr. stated that the Bitcoin 30-day compression indicator has risen to an extreme range of 93.9%, marking the fourth occurrence of a similar situation since the current bear market phase.Over the past 20 days, the Bitcoin price has continuously tested the annual moving average line but has failed to establish a solid position, indicating that volatility compression is intensifying near key resistance levels, and a directional choice may be faced in the short term.

According to The Block, Charley Cooper, President of Ava Labs, stated that the New York Stock Exchange (NYSE) has been testing Avalanche technology over the past year and is collaborating with Ava Labs to explore how it can be integrated with the exchange's existing systems.Cooper mentioned that a close working relationship has been established between the two parties, but it has not yet been confirmed whether the NYSE will ultimately choose Avalanche as the blockchain for its tokenized securities platform. The NYSE announced in January this year that it is developing a platform for the tokenization of U.S. stocks and ETF trading and on-chain settlement.

The Hong Kong Special Administrative Region Government released the 2026 Policy Address, further expanding the application of digital assets in traditional financial markets. The Securities and Futures Commission will improve the virtual asset licensing system and the regulatory framework for tokenized investment products, promoting the issuance and trading of gold and other suitable real-world assets on licensed platforms.Hong Kong also plans to normalize the issuance of digital bonds and explore the full lifecycle applications of digital currency for settlement, dividend distribution, and redemption. The Monetary Authority will test the tokenization operation of over HKD 1.3 trillion in foreign exchange fund notes by the end of the year and plans to achieve CBDC settlement and 24/7 operation of EnsembleTX by the end of the year.

Bitcoin Core 32 has entered the candidate testing phase this week, with developers aiming to release the official version on October 10. This update is primarily aimed at node operators and developers, as it can accelerate block verification speed and adjust the way wallets handle payments.According to the draft release notes, the update speeds up block verification by reading database information in parallel, but it will not change the Bitcoin block generation speed. Four wallet commands will default to the updated format for exchanging partially signed transactions, although applications can still request the old version. In terms of security fixes, the update prevents maliciously constructed wallet names from triggering commands on node computers, a vulnerability that affects non-Windows systems; another patch fixes an issue with excessive memory usage by the new HTTP server.Contributor Matthew Zipkin described a "memory exhaustion scenario" in the patch proposal, which he discovered while auditing the new HTTP server of Bitcoin Core using the AI model Kimi K3. GitHub user jeanpablojp found that unauthenticated requests could also lead to memory growth during the review; after patch revisions, 16 unauthenticated connections caused only about 3 MB of memory growth in 90 seconds, compared to 3.2 GB previously. The patch was merged on September 5.

According to CoinDesk, Bitcoin Core 32 entered its final testing phase on September 14, with the first candidate version marked, and the official release is expected on October 10. This version will not change Bitcoin's consensus rules but will mainly optimize fee estimation, accelerate block processing, and fix several security vulnerabilities.In terms of fee estimation, Bitcoin Core 32 introduces a new estimator based on unconfirmed transactions, which can quickly lower the recommended fee rate when network congestion eases, compared to the original estimator based on historical block fees. Regarding block processing, nodes can now use multiple threads to fetch transaction data from the database simultaneously, with a default of 8 threads, reducing the waiting time for nodes to catch up with the blockchain.For security fixes, developers have addressed a command execution vulnerability that has existed in non-Windows systems since Bitcoin Core 24. This vulnerability could allow authenticated users to execute commands on the node host through specially crafted wallet names when the walletnotify feature is enabled. Additionally, four commands used to create partially signed transactions will default to using PSBT version 2 format; the new web server was found to have a memory exhaustion flaw during auditing, where 16 unauthenticated REST connections could raise the node's memory from 46 MB to about 3 GB in approximately one minute, and this issue has been fixed before the official release.

Apple announced that Siri artificial intelligence will begin testing in English today, with plans to expand to 5 languages in the future. Siri AI will initially be unavailable in the European Union on iOS, iPadOS, and watchOS.

Leifeng Network · Whale Rhino has learned that OpenAI is secretly developing a screenless AI hardware product in Shenzhen. Industry insiders say that the project's confidentiality level is extremely high.Engineers came to Shenzhen for a business trip without even bringing their phones. The product is planned to be launched in 2027.

Arya.ag, an agricultural warehousing and loan company in India, is testing a system for tokenizing warehouse receipts for stored grains on the Avalanche dedicated Layer 1 blockchain. Arya.ag is collaborating with Finternet to connect grain storage, warehouse receipts, collateral commitments, and loan statuses through this network. Devika Mittal, head of Ava Labs India, stated that the testing is underway, with each tokenized warehouse receipt representing ownership of the stored goods.Sanmesh Kalyanpur, a director at Finternet Labs, mentioned that Arya.ag's samplers collect information on stored grains and input it into the company portal. Finternet will integrate farmers, commodities, warehouses, and insurance information into a "composite token" for banks to assess collateral risks. Arya.ag stores approximately $2 billion worth of agricultural products in its warehouse network and supports loans of about 120 billion Indian Rupees (approximately $1.26 billion) annually, with its loan department, Arya Dhan, disbursing around $230 million in loans each year.The concept of Finternet originated from a 2024 paper by the Bank for International Settlements (BIS), co-authored by Infosys co-founder Nandan Nilekani and then-BIS General Manager Agustín Carstens, proposing the establishment of an interconnected unified ledger for tokenized assets. In 2024, the Indian government launched a 10 billion Rupee credit guarantee scheme to encourage financing against electronic transferable warehouse receipts. The two companies have not disclosed the expected launch date or initial deployment scale.

According to "Du Jia," Alibaba Cloud is currently beta testing a new AI investment research tool called Qovest, positioned as an AI financial research assistant for professional individual investors. It is currently open for experience in batches to professional investors, with the first batch focusing on verifying A-share condition searches, Deep Research, and continuous tracking and research of asset accumulation.Qovest supports research on companies, industries, themes, and markets. After users pose questions, it can help find data, read financial reports and announcements, analyze research reports, generate reports, and consolidate research into the investment research space, continuously tracking subsequent changes in research subjects. The product standardizes common workflows for individual investors' fundamental research into modules, such as organizing the operational trends of a single company, horizontally comparing the business structures and financial differences of two targets, breaking down business models, and generating visual charts and research cards. The product is aimed at individual investors with independent research habits, but ordinary retail investors can also use it.

The supply chain reports that the capacity for high-end testing interfaces for AI chips is tight. NVIDIA has significantly raised prices to secure the capacity of mainstream testing interface vendors' probe cards and test sockets, causing some R&D and engineering validation demands to be squeezed out.Including wafer foundry TSMC and chip manufacturers, multiple supplier validations have been initiated to cope with the supply pressure after capacity has been locked.

According to a report by the Financial Associated Press, the Chief Financial Officer of OpenAI stated that they are considering reforming the charging model, testing a new pricing model based on performance, gradually moving away from the usage-based billing method, and competing with lower-priced open-source models.