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first_img Canadian Prime Minister Carney established the National Artificial Intelligence Committee

On October 2, Canadian Prime Minister Mark Carney announced the establishment of the Prime Minister's National Artificial Intelligence Advisory Council in Ottawa, which will provide independent and pragmatic advice on Canada's artificial intelligence transformation. The council will bring together stakeholders from the public and private sectors to provide input on the evolution of the AI for All national strategy, covering areas such as accelerating adoption, nurturing national leading enterprises, building sovereign artificial intelligence infrastructure, enhancing AI safety, protecting democracy, and ensuring that all Canadians benefit.Council members include Ajay Agrawal, Yoshua Bengio, Sanja Fidler, John Graham, Gillian Hadfield, Jordan Jacobs, Eric Lamarre, Valérie Pisano, Senator Thomas Pitfield, Jody Thomas, Louis Vachon, Michelle Zatlyn, and of course, Patrick Pichette as a member. The council is supported by a small team from the Privy Council Office, while policy decisions and implementation remain the responsibility of the relevant ministers and departments.Carney stated that the prosperity and sovereignty of the artificial intelligence era belong to countries that can build, adopt, and govern artificial intelligence according to their own conditions, and the council will provide recommendations on how to manage risks, seize opportunities, and improve the lives of all Canadians.

first_img The number of users of generative artificial intelligence in our country has surpassed 700 million

On September 29, the Policy and International Cooperation Department of the China Internet Network Information Center released the "Generative Artificial Intelligence Application Development Report (2026)" at the "2026 (Seventh) China Internet Basic Resource Conference." The report shows that by the first half of 2026, the user scale of generative artificial intelligence in China will exceed 700 million, with a penetration rate of over 50.0%. Intelligent Q&A is the main scenario, with 76.0% of users using it to answer questions, while the proportions of users handling images or videos, text, work summaries, meeting minutes, and PPTs are 47.8%, 37.6%, and 32.5%, respectively.The usage of applications such as AI comprehensive assistants and AI efficiency office tools has increased by over 100% year-on-year. 38.7% of internet users have purchased smart hardware online in the past six months, with the purchase ratios of smart wearable devices, smartphones, and tablets being 20.2% and 18.2%, respectively. By June 2026, China's intelligent computing power scale reached 2185 EFLOPS, a year-on-year increase of 177%, and the first domestically produced 100,000 card artificial intelligence supercluster was officially put into use.Deep Exploration, Dark Side of the Moon, and others have successively released multiple trillion-parameter open-source large models, and more than 120,000 high-quality datasets have been established. The application penetration rate of artificial intelligence technology among large-scale manufacturing enterprises has exceeded 30%. In the first half of 2026, there were over 400 humanoid robot complete products, and the total annual production is expected to exceed 100,000 units. During the same period, there were 1,255 instances of investment and financing related to artificial intelligence, totaling approximately 250.14 billion yuan, reaching 78.0% and 182.0% of the total for the entire year of 2025, respectively.

first_img OpenAI: Safety justification should be submitted before cutting-edge reinforcement learning training

On September 28, 2026, OpenAI published a safety-related article, stating that before continuing any cutting-edge reinforcement learning training, structured safety documentation should be required. Ideally, such documentation should reach the evidence-based structured risk argument level used in safety-critical industries like aviation and nuclear power. OpenAI views this as a direction for effort while acknowledging the complexity arising from the emergence of AI capabilities, making it difficult to achieve the same level of rigor.The article focuses on cutting-edge reinforcement learning training and does not cover the broader alignment attributes required for internal and external deployments. The recommendations in the article reflect current practices, which are expected to continue evolving and are being implemented internally at OpenAI. Technical safeguards should cover model alignment, isolation, and monitoring, including avoiding speculative positive reinforcement rewards, offline alignment assessments and stress testing, preventing automated scorers from seeing thought chains, as well as multi-layer infrastructure security, sandbox red teaming, limiting high-bandwidth cross-sample communication, and immutable preservation of agent records.Operational guidelines include preemptive dissent across teams, approvals that can be vetoed by senior leadership, accountability of training leads for safety arguments and incident responses, as well as fail-safe pauses, internal oversight, audit access, and escalation by severity. In response to serious misalignment events, OpenAI proposes controlled access to original records, root cause analysis, operational and cultural reviews, and treating incident-derived assessments as regression tests; results of investigations should be made public, along with reviews and operational changes, and affected third parties should be notified as soon as possible.

DyorSwap: The previously identified "GIWA Mainnet" is actually a fake chain built by scammers, and compensation for affected users will be provided through treasury funds

DyorSwap officially announced that the so-called "GIWA Mainnet" identified by the team earlier is actually a fake chain set up by scammers. This fake network used the correct GIWA chain ID (9134), making it appear legitimate during the initial verification phase. The team also identified several suspicious messages and individuals within the related community that may be connected to this incident. The announcement stated that significant losses have occurred due to this fraudulent cross-chain bridge.DyorSwap stated that it is taking three immediate actions: first, contacting a professional security team to conduct further on-chain tracking and investigate the involved addresses, transactions, and fund flows; second, preserving all relevant evidence, including chat records, RPC information, cross-chain bridge addresses, and on-chain transactions; third, preparing to use treasury funds to compensate affected users, with eligibility criteria, loss verification processes, compensation scope, and detailed plans to be announced after the investigation and verification processes are completed.DyorSwap emphasized that until further notice, users should not use any unofficial GIWA mainnet RPCs, cross-chain bridges, or contracts, and should not send funds to any related addresses. The official team deeply apologizes to every affected user in this incident and states that subsequent updates will be released as soon as possible.

DyorSwap: The previously identified "GIWA Mainnet" is actually a fake chain built by scammers, and compensation for affected users will be provided through national treasury funds

DyorSwap officially announced that the so-called "GIWA mainnet" previously identified by the team is actually a fake chain set up by scammers. This fake network used the correct GIWA chain ID (9134), making it appear legitimate during the initial verification phase. The team also identified several suspicious messages and individuals within the related community that may be connected to this incident. The announcement stated that significant losses have occurred due to this fraudulent cross-chain bridge.DyorSwap stated that it is taking three immediate actions: first, contacting a professional security team to conduct further on-chain tracking and investigate the involved addresses, transactions, and fund flows; second, preserving all relevant evidence, including chat records, RPC information, cross-chain bridge addresses, and on-chain transactions; third, preparing to use treasury funds to compensate affected users, with eligibility criteria, loss verification processes, compensation scope, and detailed plans to be announced after the investigation and verification processes are completed.DyorSwap emphasized that until further notice, users should not use any unofficial GIWA mainnet RPCs, cross-chain bridges, or contracts, and should not send funds to any related addresses. The official team deeply apologizes to every affected user in this incident and states that subsequent updates will be released as soon as possible.

first_img Google disclosed the AI security agent PageBreak, which has identified over 500 vulnerabilities

The Google Product Security Team has disclosed an internal AI agent called PageBreak, used to test the security of its first-party web applications. This agent is built on Google's Gemini model and began a pilot program in November 2025, transitioning to a formal project in January 2026, with the goal of autonomously scaling vulnerability discovery and reducing manual input.Unlike common AI scanning tools, PageBreak hands over hypotheses to specialized validators after discovering suspicious defects, attempting actual exploitation in a real-time running copy of the application, and only reports once confirmed exploitable, with a false positive rate close to zero. Google claims that PageBreak has identified over 500 XSS vulnerabilities in its first-party web applications, which can be used to hijack login sessions, steal data, or impersonate users.Google stated that the security team has been overwhelmed in recent years by a large number of AI-generated vulnerability reports that appear reasonable but are not valid, making it a major challenge to distinguish real defects from hallucinations. When testing applications built using the next-generation high-assurance framework, PageBreak found only two vulnerabilities. The next step for Google is to integrate PageBreak with the automated remediation agent CodeMender, providing confirmed vulnerabilities with accompanying fixes.

first_img Anthropic: Claude identifies new enzyme systems, gene editing stocks decline

On Wednesday local time, Anthropic announced that its model Claude identified a previously undescribed enzyme system in vast DNA sequence data, with a repetitive sequence arrangement similar to CRISPR. This is the first achievement of its newly established biological laboratory, which was formed this spring and is located in the San Francisco Bay Area. Following the announcement, shares of gene editing companies fell on Wednesday, with CRISPR Therapeutics down 5.54%, Beam Therapeutics down 6.02%, and Prime Medicine down 11.58%.The related task was to search for noteworthy reverse transcriptase systems from large DNA databases. During approximately 21 hours of searching, about 950 Claude agents used around 210 million tokens, with one agent noticing a repetitive DNA sequence arranged near a certain reverse transcriptase gene. The team named this combination the array-associated reverse transcriptase system, primarily found in bacteriophages, which includes reverse transcriptase genes, adjacent accompanying genes, and a set of repetitive DNA sequences. The reverse transcriptase itself has been studied before, and the new finding is that it forms a system together with surrounding non-coding DNA sequences and functionally unknown accompanying proteins.Anthropic stated that researchers still do not know the main function of this system and have not proven that it can perform targeted modifications to DNA like mature gene editing tools. Preliminary experiments found that these repetitive sequences can produce various short RNAs, but this does not equate to having programmable gene editing capabilities. The preprint paper disclosed that to verify whether the discovery could be repeated, the team ran the same search 10 more times;
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