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Google Quantum Chip Breakthrough: Reducing Key Computation Error Rate, Early Bitcoin Wallet Quantum Risks Under Attention

Google stated that its Willow quantum chip reduces the error rate in preparing the special states (Magic States) required for quantum computing by about 40 times through a method called "Cultivation." The related research was published this week in Science, which is expected to lower the hardware costs of future large-scale quantum computers and draw more attention to the potential threat of cracking Bitcoin wallets.Magic States are a key resource needed to perform certain quantum computing operations, and their preparation process consumes a significant amount of hardware. Google's experiment achieved about 99.99% state fidelity, but only about 8% of attempts passed the screening. Researchers indicated that future experiments need to be scaled up and issues such as real-time operation and error correction need to be addressed. In March of this year, Google estimated that under specific hardware assumptions, future quantum computers might only need fewer than 500,000 physical qubits to crack the cryptography used in Bitcoin and Ethereum wallets.For Bitcoin, some early wallets' public keys have been public since their mining, theoretically making them targets for future quantum attacks; while wallets with undisclosed public keys may face different attack conditions. However, this breakthrough does not mean that quantum computers are capable of cracking Bitcoin. Google's previous cost estimates for attacks assumed the use of efficient Magic States preparation schemes, so this result cannot simply be understood as a 40-fold reduction in the cost of cracking Bitcoin. Research is still in the advancement stage of quantum hardware and error correction technology, and the complete equipment and engineering capabilities required for actual attacks have not yet been realized.

first_img Nine cryptocurrency companies established the Quantum Alliance, aiming to defend against quantum risks to 6.4 million bitcoins

According to CoinDesk, nine cryptocurrency companies announced the establishment of a Quantum Alliance on Thursday, planning to develop universal security standards for Bitcoin, Ethereum, and other blockchain networks to address the threats posed by future quantum computers.The alliance estimates that about 6.4 million Bitcoins, or 30.2% of the supply, have their public keys exposed, and future quantum computers could reverse-engineer wallet public keys to recover private keys and steal assets. The alliance explained that since no quantum computer currently has sufficient computing power, these Bitcoins cannot be stolen in this manner for the time being. Members include Hacken, Midnight Foundation under Charles Hoskinson, the quantum-resistant layer one blockchain Quantus, and Postquant Labs.There are significant differences in the industry regarding when the quantum threat will arrive. Bryn Bennett, Chief Revenue Officer of The Vault, stated that no one knows the exact date, but estimates are continuously being revised downward, and this risk can be planned for in advance. The question for custodians is not whether the threat will appear in 2028 or 2035, but whether they can complete the migration if it arrives earlier.Richard Carback, Chief Technology Officer of Postquant Labs, believes that it is realistic for machines capable of breaking existing cryptography to emerge by 2028. Recent research has lowered the estimates of the computing power required to attack Bitcoin and Ethereum, but currently, no existing machines can break their cryptography, and related predictions remain controversial.The question of whether to freeze vulnerable Bitcoins has also sparked debate. Bennett pointed out that no one is responsible for this issue; custodians only protect client assets, not abandoned assets. Freezing tokens is a governance decision of the Bitcoin network, and any freeze would set a precedent of exchanging quantum risk for property rights and neutrality. Carback prefers to transfer vulnerable tokens and suggested placing them in a trust, allowing holders who can prove ownership to reclaim their funds.Binance founder Changpeng Zhao once suggested that if quantum technology advances and Satoshi Nakamoto's approximately 1.1 million Bitcoins remain untouched, they should be frozen; Bitcoin developer Jameson Lopp also proposed limiting vulnerable tokens to prevent theft, but critics argue that freezing someone else's Bitcoins contradicts the promise that no one can confiscate Bitcoins. Achieving quantum resistance requires replacing the digital signatures that authorize transactions, which necessitates consensus among developers, miners, wallet service providers, exchanges, and users. The new signatures may also occupy more block space, increasing transaction fees or reducing the number of transactions Bitcoin can process.

JPMorgan warned that AI stocks are hard to replicate the rebound in July, and leverage risks are rising

J.P. Morgan strategist Nikolaos Panigirtzoglou pointed out that the AI stock sell-off in October may be difficult to replicate the rapid rebound seen in July. Compared to before, the current market's willingness to buy on dips has weakened, short positions are insufficient to provide potential short-covering buying, corporate buyback funds are also decreasing, and at the same time, leveraged exposure in ETFs is being rebuilt, which may further amplify market volatility. J.P. Morgan believes that, based on investor positioning and capital flows, AI infrastructure stocks do not yet appear to be in an oversold state.This round of sell-off has spread from South Korean memory chip stocks to the U.S. semiconductor sector. SK Hynix and Samsung Electronics have both seen their stock prices drop by nearly one-third over the past month, and the Philadelphia Semiconductor Index has fallen 10% over the last five trading days. Additionally, the combined $40 billion stock buyback plan previously announced by the two companies was completed ahead of schedule in mid-October, which may have caused the market to lose some of the buying support brought by corporate buybacks.Meanwhile, BlackRock CEO Larry Fink warned that if the U.S. halts data center construction, the economy could fall into recession. He stated that a significant portion of U.S. economic growth is related to capital expenditures in AI infrastructure. As market concerns deepen regarding the return on AI investments and corporate profitability, price adjustments in the AI supply chain could also impact data center construction, energy infrastructure, and related employment sectors.

first_img NEXTPredict invested $12,000 to hedge against flight cancellation risks at Kalshi

The media and conference organization NEXTPredict announced that it has executed the first trade in the flight cancellation market through Kalshi to hedge investments for its October summit, locking in $3 million in guarantees. The company paid a premium of $12,000, and if the cancellation rate of flights arriving at New York's Kennedy International Airport on October 21 exceeds 50%, the contract will automatically pay out, covering the summit costs, as October 21 is the main travel day for attendees. Susquehanna acted as the market maker for this transaction.Kalshi launched the flight cancellation market after self-certifying the contract with the U.S. Commodity Futures Trading Commission (CFTC) on July 14, allowing participants to trade on whether the cancellation volume at specific airports exceeds preset thresholds. This market does not target individual flights and has clear anti-manipulation clauses. NEXTPredict is a media and event platform focused on the global prediction market industry, launched by the NEXT.io team. Its flagship event, the "Global Prediction Market Summit," will be held from October 22 to 23, 2026, at Convene Hudson Yards in New York, bringing together founders, executives, investors, and policymakers.NEXTPredict and Kalshi position this trade as institutional hedging, similar to how airlines hedge against fuel costs or farmers hedge against crop yields, rather than betting on the fate of the summit.

first_img Microsoft CEO: Cutting-edge models should be regarded as internal risks, and control must be placed outside the models

Microsoft CEO Satya Nadella published an article discussing the trust framework for the era of superintelligence. He stated that traditional software can trace behaviors back to specific code paths, whereas current superintelligent systems lack this mechanistic understanding and cannot attribute model behaviors and outputs to specific training data or weight configurations. However, they are being deployed and are accessing sensitive data, executing critical actions on behalf of others. He emphasized that responsibility for intelligent behavior cannot be outsourced to model providers, nor can superintelligence be accepted or rejected as a series of nested black boxes.Nadella proposed that the supply of intelligence should be separated from the authorization of intelligence, surrounding nondeterministic models with deterministic system design, human control, and operational procedures, and establishing industry standards when existing standards are insufficient. He suggested managing cutting-edge models with closed-source and open-source weights as internal risks, not because they are inherently malicious, but because agents with sufficient capability that can access important systems may make mistakes or be compromised. Relevant practices include establishing identities, restricting permissions, recording activities, and setting isolation boundaries, with the transparency of the model's reasoning chain becoming a non-negotiable starting point.He further stated that permissions and action controls must be placed outside the model, and the model, orchestration layer, and action space should be separated. Principles include avoiding reliance on a single model as the sole dependency for important outcomes or for verifying its own work, ensuring that critical actions leave tamper-proof and human-readable evidence, continuously testing for failures, attacks, and boundary conditions, allowing organizations to independently decide on access and action permissions, validating independently of the intelligence being verified, presuming that the model has been compromised and supporting mid-course pauses or shutdowns, and timely disclosing and sharing lessons within the industry when failures or compromises occur. He concluded that the most trustworthy superintelligent systems are those that require the least trust in the model itself.
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