testing

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.

Douyin is currently conducting an internal test of the AI Workshop, aimed at ordinary creators and developers, providing a complete link from AI application building, debugging, and operation to platform distribution, deeply integrating with Douyin's internal traffic system. The AI development framework, interface capabilities, and cloud storage services are all built into the creator's backend.The Douyin App's recommendation page has added a new content form interest card, used to showcase AI applications created in the AI Workshop. Users can directly interact with these cards while browsing the recommendation page, without needing to switch to a mini-program or leave the main app, allowing them to complete Q&A queries, fun interactions, and light tool experiences within the information flow. The interest card relies on Douyin's personalized recommendation distribution, supporting custom gameplay and styles.Creators who do not understand coding can use natural language to describe their ideas for building, while technically skilled developers can modify underlying files for deep customization. Debugging, real-device preview, and publishing can all be completed in the same environment. The produced works can be directly converted into interest cards for placement in the recommendation stream. This product is currently in the invitation-only internal testing phase.

According to The Block, ZKsync developer Matter Labs has open-sourced the permission engine of its distributed ledger platform Prividium for financial institutions, allowing organizations to run, inspect, and modify core code in their own environments. The German central bank has become the first institution to test and deploy Prividium.Matter Labs CEO Alex Gluchowski stated that feedback from regulators regarding commercial core means reliance on a single vendor, and that open-sourcing the core "structurally eliminates adoption barriers."Other components of Prividium, such as the ZKsync OS core and Atlas sequencer, have previously been open-sourced. The permission engine is planned to operate as an independent component, allowing institutions to deploy it without a commercial agreement, but management tools and integration with existing systems remain commercial products. Gluchowski said, "The central bank running public code is the clearest signal in this direction."

DeepSeek has started internal testing of version 4.1 Flash intermediate version. The official WeChat group notification states that the new model has a new architecture, natively supports multimodal capabilities, is more powerful, faster, and cheaper. The current billing is the same as V4 Flash, with a maximum of 20 concurrent sessions per account.Users can now directly call it, and there is no need to change the base_url, just replace the original model ID with deepseek-v4.1-flash-expires-on-0910.

Licheng, Jingyuan Electronics, and Silergy all reported year-on-year and month-on-month revenue growth in August, with Licheng and Silergy setting new historical highs for two consecutive months. Licheng's consolidated revenue in August was 8.558 billion New Taiwan Dollars, a month-on-month increase of 3.48% and a year-on-year increase of 24.46%. After breaking the 8 billion mark for the first time in July and setting a historical high, August saw another record. The cumulative revenue for the first eight months reached 61.258 billion New Taiwan Dollars, a year-on-year increase of 30.83%. Jingyuan Electronics reported revenue of 4.08 billion New Taiwan Dollars in August, a month-on-month increase of 2.23% and a year-on-year increase of 31.58%. The cumulative revenue for the first eight months was 29.404 billion New Taiwan Dollars, a year-on-year increase of 35.53%. Silergy's revenue in August was 2.07 billion New Taiwan Dollars, with a month-on-month increase of nearly 3% and a year-on-year increase of nearly 29%. The cumulative revenue for the first eight months reached 15.26 billion New Taiwan Dollars, a year-on-year increase of over 20%.Licheng's main source of growth this year remains the rebound in demand for memory packaging and testing. Licheng previously anticipated that revenue in the third quarter would show single-digit quarter-on-quarter growth, with the fourth quarter having the potential to exceed the third quarter. The momentum for memory orders is expected to continue until the end of the year, with a positive market outlook at the beginning of next year. In addition to its core memory business, advanced packaging has become a key focus for the next phase of development. The panel-level packaging has already been adopted by American clients, and the production capacity of the P11 plant has been secured by clients, with plans to enter the mass production phase of integrated ASIC and HBM AI chips by mid-2027.Jingyuan Electronics has been actively expanding its high-end testing capacity in recent years, with AI-related products becoming an important driving force for its operations. The testing demand for AI GPUs, ASICs, and high-performance computing chips remains its main source of growth. Silergy pointed out that the demand for AI and high-speed interconnects is strong, including an increase in demand for high-performance computing chips such as CPUs, GPUs, ASICs, and AI accelerators. After completing the cleanroom construction at the newly acquired Hukou plant in February, Silergy began mass production in July, currently achieving 40% of the total capacity of the plant and gradually taking on new demand from overseas clients.

According to the official announcement, Binance has launched the AI feature suite "Binance AI," which is currently in Beta testing. The aim is to help users interpret complex market data, identify market dynamics, and reduce information noise through AI.It is reported that Binance AI will provide a personalized information interface, AI market insights covering both crypto assets and traditional assets, as well as concise and timely market dynamic updates. The first batch of users can apply to participate in the testing, and users who qualify for the whitelist will receive access instructions via email.Currently, the Binance AI Beta is only open to Binance users who have completed identity verification. The number of spots is limited and will be distributed in batches. Submitting an application does not guarantee testing eligibility. Binance also stated that user feedback will be used to further improve the product.

Anthropic stated that the company has temporarily paused certain AI training and cybersecurity assessments. The company disclosed the relevant adjustments in a blog post, explaining the measures taken in response to unauthorized actions by its AI agents earlier this year. OpenAI previously indicated that it had paused some model development work due to safety concerns. Anthropic also confirmed that it has taken similar measures and emphasized the need for broader coordination on the pace of frontier AI development.Anthropic stated that after disclosing three related incidents in July, the company paused external cybersecurity assessments for pre-release models and also briefly suspended internal testing of pre-release models. Following the incidents, the company also paused high-risk reinforcement learning environments in pre-release models for several weeks. Anthropic noted that most reinforcement learning work has resumed, but some high-risk environments remain on hold, awaiting human review or updates to monitoring tools.

According to a report by the Economic Daily, ASE Technology Holding benefited from the increased capacity of Google TPU, significantly adding advanced packaging and testing orders. Intel is accelerating the promotion of its EMIB advanced packaging platform while simultaneously expanding its outsourcing orders to ASE Technology Holding, with the previously raised testing quotes showing benefits. Google continues to increase its AI capital expenditures to expand data centers, using TPU to support the Gemini large model, AI agents, and Google Cloud services. The market estimates that Google TPU will enter a large-scale production phase by 2028, with shipments expected to reach 12 to 15 million units. ASE Technology Holding has mastered 2.5D, 3D advanced packaging, and high-end testing technologies, and Google is also expanding its use of TSMC's advanced processes and CoWoS capacity.Intel is racing to advance its EMIB packaging platform, with major cloud companies like Meta and Google successively adopting the EMIB and EMIB-T platforms. ASE Technology Holding, positioned as a pure testing and packaging foundry, can directly procure organic embedded silicon bridge substrates to undertake backend wafer-level assembly and high-end testing services. Wu Tianyu, the Chief Operating Officer of ASE Technology Holding, believes that Intel's EMIB and TSMC's CoWoS are not zero-sum competitors. As the testing time for AI chips lengthens, the costs of equipment, materials, and labor are rising, and high-end packaging and testing capacity is becoming increasingly tight. Major testing and packaging factories have gradually raised prices based on products, capacity, and customer conditions, with increases of about 5% to 10%.