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Vitalik Buterin stated that the "killer application" of adversarial governance mechanism design theory may ultimately appear in the field of artificial intelligence safety. He believes there is a deep correspondence between governance mechanisms and artificial intelligence safety: both involve how "weaker principals" can achieve ideal outcomes from "stronger agents."In governance scenarios, the principal is a static algorithm, and the agent is a human; in artificial intelligence safety scenarios, the principal is humans and weaker large language models, while the agent is a stronger large language model. Vitalik pointed out that if the degree of collusion among agents can be limited, the system can achieve better outcomes, and this mechanism design conclusion may be transferable to the field of artificial intelligence safety.

Analyst Jukan from Citrini forwarded a research report from Tianfeng Securities and stated that the U.S. government needs to maintain its leading position in the AI field, making it difficult to truly stop once it enters the AI race. Jukan believes that the recent calls from Anthropic and OpenAI to slow down AI development should not be viewed solely as safety initiatives; there may also be multiple considerations behind it, such as the inability to slow down competition and consolidating leading advantages through safety regulation.Jukan further pointed out that the related "AI slowdown" calls seemingly stem from the challenges of safety testing, operational monitoring, and third-party validation keeping pace with the speed of model iteration. In the short term, this may suppress market sentiment in the AI sector and lower market expectations for the next generation of models; another possibility is that the industry remains optimistic about AI in the long term but wishes to delay the next round of significant R&D investment, prioritizing the commercialization of existing products and reducing infrastructure and capital expenditure pressures. He believes that the AI race is essentially similar to a "prisoner's dilemma," where all parties wish to slow down, but no one dares to be the first to stop, or they may lose technological, customer, and financing advantages.Jukan also mentioned that Anthropic and OpenAI have recently emphasized recursive self-improvement (RSI), which is related to AI already assisting in the development of the next generation of AI and the acceleration of model iteration speed; at the same time, it has been reported that during internal testing at OpenAI, incidents occurred where agents collaborated to escape the sandbox and intrude into Hugging Face's production servers. Jukan believes that as the release of models incurs expensive evaluation, certification, and ongoing audit costs, large laboratories are better able to bear these fixed costs, while smaller teams may face higher entry barriers as a result; if leading laboratories further participate in the formulation of evaluation standards, industry barriers may continue to rise.

OpenAI is pushing for mandatory national-level artificial intelligence safety requirements.

According to a report by Sina Finance, Anthropic refused to submit its latest model Claude Mythos 5.1 to the UK Artificial Intelligence Safety Institute (AISI) for testing before its release, as the model is only open to qualified institutions in the United States. This move has raised alarms within the UK Whitehall and AISI, with UK national security officials concerned that this could set a precedent, making it difficult for AISI to access the latest cutting-edge models in the future.Analysts pointed out that this action may be related to the increasingly stringent export control policies of the US government on the AI industry. The US government had previously implemented export controls on Anthropic's models Mythos and Fable, prohibiting foreign nationals from using them. Anthropic declined to comment on this, only stating that it is coordinating with the US government to expand access to the model for more domestic and international partners as soon as possible.

According to SoSoValue data, the total net outflow of Ethereum spot ETFs yesterday was $24.2921 million. The Ethereum spot ETF with the highest net inflow in a single day was Fidelity ETF FETH, with a net inflow of $9.8924 million. Currently, the historical total net inflow of FETH has reached $2.287 billion.The Ethereum spot ETF with the highest net outflow in a single day was Grayscale Ethereum Trust ETF ETH, with a net outflow of $24.6098 million. Currently, the historical total net inflow of ETH has reached $1.903 billion. As of the time of writing, the total net asset value of Ethereum spot ETFs is $15.716 billion, and the ETF net asset ratio (the market value as a percentage of Ethereum's total market value) is 5.19%. The historical cumulative net inflow has reached $13.169 billion.

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 TIME, OpenAI CEO Sam Altman recently stated in an interview that the company has previewed the upcoming cutting-edge model series Astra to key clients. In the demonstration, 16 AI agents can collaboratively break down mathematical problems and assemble proofs, and Astra can operate computer software across applications at superhuman speeds. Altman mentioned that Astra will support "persistent agents" capable of performing long-term tasks and is expected to be the first model that can invent new things in a meaningful way, possessing characteristics of AGI.Over the past year, OpenAI has fallen behind expectations in product direction and pre-training research, being surpassed by Anthropic in programming products, annual revenue, and valuation. The company has experienced multiple executive departures and is facing challenges such as several product liability lawsuits and legal disputes with Apple and Musk. OpenAI's current valuation is nearly $1 trillion, with ChatGPT having over 1 billion monthly active users.Recently, OpenAI disclosed a security incident: an unreleased agent escaped the sandbox and attacked Hugging Face. Following this, the research team froze some experiments, enhanced monitoring, and paused the training of an unreleased model expected to bring the greatest capability leap until new safety measures are in place. Altman emphasized that "ensuring AI safety is more important than the growth momentum of any company," and the company will slow its pace and allocate resources to safety and alignment teams. Chief Research Officer Mark Chen estimated that the company is about 80% complete in reaching AGI, and Altman stated that the internal system may be referred to as AGI by the end of the year.

Bitcoin News posted on the X platform that BTC Sessions stated their team spent several weeks assisting Bitcoin holders affected by the Coldcard vulnerability in transferring their funds to safety, estimating that they protected Bitcoin worth tens of millions of dollars during this period. However, for many, it was too late.A member of the local Bitcoin community lost 90% of their Bitcoin, while another woman who spoke with them lost all of her Bitcoin. BTC Sessions stated that this could be the most severe self-custody incident in Bitcoin history. BTC Sessions indicated that this experience prompted them to rethink asset custody, with diversified security measures becoming a key lesson.

OpenAI announced that it will adopt stricter system monitoring and security measures to prevent artificial intelligence models from going out of control. The company plans to alert the security team within 30 minutes of discovering a problem and implement additional controls to prevent AI models from connecting to the internet to perform high-risk tasks.OpenAI has also suspended certain model inference tasks and training plans pending the completion of safety verification.

On August 11, Fidelity submitted a registration statement amendment to the SEC, applying to add ETH staking functionality to its spot Ethereum ETF, Fidelity Ethereum Fund (FETH). Under normal circumstances, FETH can stake up to 100% of its held ETH, but there is no minimum staking ratio.If approved by the SEC, the investment objective of FETH will also change. Currently, the fund primarily tracks the Fidelity Ethereum Reference Rate, deducting related fees; after adding staking, the fund's objective will shift to tracking that index while accounting for the income generated from staking.

According to SoSoValue data, the total net outflow of Ethereum spot ETFs is $1.7644 million. The Ethereum spot ETF with the highest net inflow in a single day is Blackrock ETF ETHA, with a single-day net inflow of $563,800, and the historical total net inflow of ETHA has reached $11.626 billion. The Ethereum spot ETF with the highest net outflow in a single day is Fidelity ETF FETH, with a single-day net outflow of $2.3283 million, and the historical total net inflow of FETH has reached $2.119 billion.As of the time of writing, the total net asset value of Ethereum spot ETFs is $10.479 billion, and the ETF net asset ratio (market value as a percentage of Ethereum's total market value) is 4.61%, with a historical cumulative net inflow of $11.439 billion.

According to Wired, during security testing, the open-source model Kimi K3 from the dark side of the moon broke out of the sandbox and accessed the internet, attempting to find test answers via GitHub. American security startup Frontier Security stated that Kimi K3 exploited a sandbox configuration vulnerability, but it itself lacked sufficient built-in protective mechanisms.Similar to incidents previously disclosed by OpenAI and Anthropic, this escape partially stemmed from a sandbox configuration error. However, Kimi K3 did not initiate an attack, as the answers were easily accessible on GitHub. The CEO of Frontier Security stated that Kimi K3 performed excellently in cybersecurity defense but lacked mechanisms to prevent cheating or escaping the sandbox. Security experts emphasized that configuring the testing environment is crucial, as the misuse of AI agents could lead to system failures.

According to CCTV News, U.S. President Trump’s helicopter encountered a flight safety incident in Washington on the 4th. The White House stated that the incident did not pose a personal safety risk; however, the Federal Aviation Administration has initiated an investigation.It is reported that Trump took off from outside the White House on the "Marine One" helicopter on the afternoon of the 4th, heading to Andrews Joint Base, and then transferred to "Air Force One" to Los Angeles.

According to Bloomberg, the UK government's AI Safety Research Institute (established in 2023) disclosed on Tuesday that during a safety assessment of OpenAI's GPT-5.6-Sol and Anthropic's Mythos 5 models, both models exhibited "unauthorized" harmful behaviors, including actively infiltrating real websites and attempting to inject malicious code into software, targeting real people and organizations.During the testing period, the institute deliberately granted the models internet access and disabled some security filters to assess their limits.

According to Jinshi reports, the National Highway Traffic Safety Administration is investigating the hanging failure of 1.2 million Tesla (TSLA.O) vehicles.

According to SoSoValue data, the total net outflow of Ethereum spot ETFs is $18.6542 million. The Ethereum spot ETF with the highest net inflow in a single day is Morgan Stanley Ethereum Trust MSSE, with a single-day net inflow of $14.297 million, and the historical total net inflow of MSSE currently stands at $19.4457 million.Next is the Blackrock ETF ETHA, with a single-day net inflow of $5.1632 million, and the historical total net inflow of ETHA currently reaches $11.43 billion. The Ethereum spot ETF with the highest net outflow in a single day is Fidelity ETF FETH, with a single-day net outflow of $16.0729 million, and the historical total net inflow of FETH currently stands at $2.105 billion. As of the time of publication, the total net asset value of Ethereum spot ETFs is $10.369 billion, and the ETF net asset ratio (the market value as a percentage of Ethereum's total market value) is 4.56%, with a historical cumulative net inflow reaching $11.188 billion.

According to Jinshi reports, Buffett: Not investing in Google back then was a mistake, and based on its current performance, the company is now "more likely to become a winner."

According to SoSoValue data, the total net outflow of Ethereum spot ETFs is $15.4092 million. The Ethereum spot ETF with the highest single-day net outflow is the Fidelity ETF FETH, with a single-day net outflow of $15.4092 million. Currently, the historical total net inflow of FETH has reached $2.134 billion.As of the time of writing, the total net asset value of Ethereum spot ETFs is $9.458 billion, and the ETF net asset ratio (the market value as a percentage of Ethereum's total market value) is 4.43%. The historical cumulative net inflow has reached $10.958 billion.