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Flash

first_img Cathie Wood: Investors should pay attention to the capital flow of AI agents

ARK Invest CEO Cathie Wood stated at a summit hosted by Robinhood in Houston that investors have traditionally "followed developers" to gauge technological trends, but now they may need to "follow agents." The AI agents she refers to are software that can perform tasks on behalf of humans, rather than just answering questions or generating text. This statement came towards the end of a discussion on AI, private markets, and technology investments.As AI agents shift from answering questions to executing operations and spending funds, the type of financial infrastructure they will use has become a focal point. SharpLink co-CEO and former BlackRock digital asset head Joseph Chalom believes that the financial system used by AI agents should not be controlled by a few banks or tech companies. He cited the example of authorized agents booking hotels, pointing out that users should be able to set spending limits, revoke authorizations at any time, and view the agents' transaction records. Additionally, users should be able to transfer the agents' identities, financial information, and permissions between different financial service providers, similar to mobile number portability.Chalom believes that open blockchains like Ethereum can provide a universal financial network for different agents, applications, and companies to use collectively, eliminating the need for each AI company to build its own closed payment system. A report from BlackRock in September also noted that AI agents could create new demands for machine-oriented payment systems, such as payment API calls, purchasing data, or renting computing power, with stablecoins and blockchain being one of the viable solutions. Coinbase's x402 is designed to enable machines to pay for online services like data or APIs.

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.

Michael Saylor proposed a digital economy policy framework: BTC should be integrated into the banking and insurance systems

Michael Saylor published a long article titled "Prescriptions for Prosperity in the Digital Economy," stating that artificial intelligence will significantly enhance the productivity of individuals and businesses, thus necessitating a more free environment for creating, financing, owning, and trading assets. He suggests establishing a "Digital Bill of Rights" for digital assets, which centers on granting individuals and businesses the rights to create, issue, custody, transfer, and use digital assets, while providing fundamental protections in financial privacy, asset ownership, and market access.Saylor believes that digital intelligence will drive the birth of a large number of new enterprises, and financing costs, complexity, and time costs should be reduced, while improving capital formation efficiency through means such as digital tokens. He proposes a goal of enabling 10 million new enterprises to secure financing, while also establishing clear issuance rules and risk-matched disclosure requirements.Regarding the digital dollar, Saylor advocates for allowing banks, fintech companies, and technology platforms to compete more fully in the digital dollar product space and for issuers to compete around yields. He believes that the U.S. can further expand the global reach of the dollar by allowing companies to develop more competitive dollar digital products.For Bitcoin, Saylor defines it as "digital capital," advocating for allowing banks to custody Bitcoin under clear rules and use it as collateral for providing credit, while also establishing a viable path for insurance companies to incorporate digital capital into their balance sheets and product designs.He specifically mentions that the Basel Accord applies a 1250% risk weight to certain crypto asset exposures, arguing that regulators should reassess the relevant capital requirements based on the actual risks of digital assets and specific business activities.

first_img Andrew Ng: AI dangers are being overhyped and development should not be paused

Stanford University professor and founder of Landing AI, Andrew Ng, stated in a post on X that recent voices advocating for the dangers of AI have made significant progress, seemingly driven by a well-orchestrated public relations campaign, and he is concerned that this poses a setback for the field. Ng indicated that there has been no unexpected dangerous turn in AI technology, and the risk of human extinction has not increased compared to a few months ago; related theories remain in the realm of science fiction.He pointed out that the biggest change lies in cybersecurity capabilities, which should be taken seriously, but will not lead to an apocalypse. Recently, the incident where the OpenAI team deployed a swarm of agents to invade Hugging Face was exaggerated by the media, for example, describing 1,200 agents working in parallel as a miraculous ability, while computers inherently run many processes simultaneously. The key factor is the vulnerabilities in the OpenAI sandbox and monitoring; fixing these vulnerabilities and strengthening monitoring is sufficient, and there is no need to pause AI.Ng also stated that large language models and agents should not be anthropomorphized; the responsibility lies with the builders and users, not the tools themselves. Pausing AI progress will cause more harm, as opponents will not slow down; engineering needs to discover and fix problems through empirical evidence. Beneficial applications still far outweigh the risks, and development should continue.
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