Grayscale Highlights Bitcoin’s Resilience as Community Prepares for Quantum Era

TheNewsCryptoОпубликовано 2026-04-07Обновлено 2026-04-07

Введение

Grayscale's head of research, Zach Pandl, argues that Bitcoin's primary challenge in the quantum era is not technological but social. While a recent Google study raised concerns about quantum computers potentially breaking Bitcoin's encryption, Pandl highlights that Bitcoin's UTXO model, proof-of-work consensus, and lack of native smart contracts make it less vulnerable than other cryptocurrencies. The real issue lies in the community's ability to reach consensus on how to handle the estimated 1.7 million BTC in early, quantum-vulnerable addresses—including those possibly belonging to Satoshi Nakamoto. Potential solutions include burning those coins, limiting spending from risky addresses, or taking no action. This echoes past divisive debates, like the one surrounding Bitcoin Ordinals, underscoring the difficulty of achieving community agreement.

If the Bitcoin community is unable to resolve certain tense problems, the chief researcher at Grayscale warns that resolving the quantum danger to the cryptocurrency may be more of a social than a technological task. On March 30, Google published a document that grabbed the crypto industry’s attention. The research hinted that a quantum computer might perhaps decrypt Bitcoin’s encryption with a lot less power than expected.

However, Grayscale’s head of research Zach Pandl argued that Bitcoin’s technical solution isn’t the issue; he argued that “bitcoin has lower risk than other cryptocurrencies” due to its use of a UTXO model and proof-of-work consensus, lack of native smart contracts, and the fact that certain address types are not quantum vulnerable.

Community’s Ability to Decide on a Course of Action

Pandl said that the community’s ability to decide on a course of action would be the real obstacle. The fate of the approximately 1.7 million Bitcoins (BTC) held in early P2PK addresses, including Satoshi’s estimated 1 million BTC hoard, which is now valued at over $68 billion, has sparked heated debates among the Bitcoin community.

Coins for which the private key is unavailable or misplaced must be handled by the Bitcoin community, according to Pandl’s writing. Burning the coins, purposefully reducing the pace of spending from susceptible addresses, or doing nothing are their three primary alternatives.

In 2023, a major controversy involving Bitcoin Ordinals—a technology that allows for the imprinting of data like text and pictures onto a satoshi, the smallest unit of Bitcoin—erupts over the use of blockspace. Pandl was alluding to this. Even while things have calmed down a little in the intervening two years, the two camps are still very much divided.

Highlighted Crypto News Today:

SEC Moves Crypto Safe Harbor Proposal to White House for Review

TagsBitcoinBlockchain

Связанные с этим вопросы

QWhat is the main challenge in addressing the quantum threat to Bitcoin according to Grayscale's head of research?

AThe main challenge is the community's ability to decide on a course of action, which is more of a social task than a technological one.

QWhy does Zach Pandl argue that Bitcoin has lower quantum risk than other cryptocurrencies?

AHe argues this is due to Bitcoin's use of a UTXO model, proof-of-work consensus, lack of native smart contracts, and the fact that certain address types are not quantum vulnerable.

QWhat is the estimated value of the Bitcoins held in early P2PK addresses mentioned in the article?

AThe approximately 1.7 million Bitcoins in early P2PK addresses, including Satoshi's estimated 1 million BTC, are valued at over $68 billion.

QWhat are the three primary alternatives the Bitcoin community has for handling coins with unavailable private keys?

AThe three primary options are burning the coins, purposefully reducing the pace of spending from susceptible addresses, or doing nothing.

QWhat major Bitcoin-related controversy from 2023 did Pandl allude to in relation to community divisions?

AHe alluded to the major controversy involving Bitcoin Ordinals, a technology that allows imprinting data like text and pictures onto a satoshi, which erupted over the use of blockspace.

Похожее

Silicon Valley 'Startup Guru' Steve Hoffman: Web3 + AI Could Be a Trap

Silicon Valley investor and "Godfather of Startups" Steve Hoffman warns that combining Web3 with AI is likely a trap, not a promising venture. In an interview, Hoffman argues that while AI is a foundational technology touching all industries, Web3 adds complexity, friction, and regulatory risk without solving mainstream consumer or business needs. He advises founders to focus on deep, specialized applications where startups can out-iterate giants, rather than on generic features easily replicated by large tech companies. Hoffman observes that Silicon Valley will lead foundational AI research, while China excels at rapid, large-scale application and commercialization, particularly in robotics. He stresses that AI-driven autonomous agents capable of collaborative, multi-step tasks are 2-4 years away, which will cause significant job displacement. The solution is not to slow AI but to redesign business models around human-AI collaboration and reform social systems like education and retraining. For startups, Hoffman recommends focusing on vertical, expertise-heavy domains to build defensibility. He sees major opportunities in AI fraud detection and cybersecurity. Key founder mindsets include systemic thinking over feature-focus, relentless customer centricity, building adaptive teams, and deeply understanding AI's capabilities and limits. Hoffman is also leading a non-profit initiative to establish university centers aimed at training future leaders in responsible, human-value-aligned AI innovation.

marsbit1 ч. назад

Silicon Valley 'Startup Guru' Steve Hoffman: Web3 + AI Could Be a Trap

marsbit1 ч. назад

Token Inefficient, Economy Tokenless

The article "Tokens Aren't Economical, Economics Aren't Tokenized" analyzes a pivotal shift in the AI industry from a technology-driven narrative to one dominated by capital efficiency. It highlights two concurrent trends: a severe capital shortage due to the exorbitant and recurring costs of compute (e.g., OpenAI's high burn rate) and a wave of corporate spin-offs where major tech companies are separating their AI units (like Kuaishou's Kling and Baidu's Kunlunxin). The core argument is that AI's "anti-internet" business model, where user growth increases costs rather than profits, has created a disconnect between high valuations and actual cash flow. Spin-offs address this by allowing AI assets to be valued independently. Within a parent company, they are seen as cost centers, but as standalone entities, they are priced based on their growth potential and scarcity in the primary market, leading to massive valuation premiums (e.g., Kling's estimated value tripling post-spin-off). The industry is at an inflection point, moving from "model worship" to "value realization." The competition is evolving from a pure compute (GPU) race to a broader focus on systemic efficiency and full-stack engineering (involving CPUs and orchestration) to achieve viable commercialization. The year 2026 is framed as a critical moment where the industry must definitively answer how to economically translate AI capability into tangible business value, reshaping the sector's future power structure.

marsbit1 ч. назад

Token Inefficient, Economy Tokenless

marsbit1 ч. назад

Crossing the 'Memory Wall': The Wafer-Level Revolution and Computing Power Routes in the AI Inference Era

In 2026, a historic shift occurred in AI as major cloud providers' inference spending surpassed training spending for the first time, signaling a move from "building large models" to "using large models." This shifts the core challenge from computing power to the "memory wall"—the bottleneck of data movement (model weights, activations, KV Cache) between external DRAM and processors, where energy and latency from data transfer far exceed computation itself. Companies like Nvidia face GPU idle time due to bandwidth limits. In contrast, Cerebras Systems adopts a radical "wafer-scale" approach with its Wafer-Scale Engine (WSE). Instead of cutting a silicon wafer into many chips, Cerebras uses almost the entire wafer as one massive chip (WSE-3). This design provides 44GB of on-chip SRAM, delivering memory bandwidth thousands of times higher than traditional HBM (e.g., 21 PB/s vs. Nvidia B200). For LLM inference, weights are streamed layer-by-layer from external MemoryX storage to the chip, avoiding HBM bottlenecks. This results in token generation speeds 1.5–5 times faster than Nvidia's B200 in some models and significant advantages in first-token latency and long-context tasks. Additionally, Cerebras's architecture offers much lower interconnect power consumption (0.15 pJ/bit vs. GPU's ~10 pJ/bit). However, Cerebras faces challenges: SRAM scaling has slowed with advanced nodes, limiting future capacity gains; the chip requires specialized liquid cooling and custom software stacks; and its external I/O bandwidth (150 GB/s) is low compared to NVLink, hindering multi-system scaling for very large models. Competition is intensifying. Major players are pursuing three paths: 1) Developing proprietary inference ASICs (e.g., Google TPU, Microsoft Maia), 2) Leveraging advanced packaging (e.g., TSMC's SoW) to democratize wafer-scale-like integration, potentially eroding Cerebras's process advantage within a few years, and 3) Exploring optical interconnects for ultimate bandwidth. Commercially, Cerebras is transitioning from a hardware vendor to a service provider, facing the immense challenge of building high-power, specialized data centers to meet large contracts (e.g., 250MW/year from 2026–2028). In conclusion, the AI inference era presents a fundamental architectural trade-off. Cerebras opts for extreme physical optimization for low-latency, single-task performance, while Nvidia prioritizes versatility and massive cluster throughput. The path forward remains uncertain, with technology and business models still evolving in the race toward advanced AI.

marsbit1 ч. назад

Crossing the 'Memory Wall': The Wafer-Level Revolution and Computing Power Routes in the AI Inference Era

marsbit1 ч. назад

Has Bitcoin's 'Rebound Ended', Officially Entering the Late Bear Market Phase?

**Title: Has Bitcoin's Rebound Ended, Entering the Late Bear Market Phase?** **Summary:** Bitcoin's price has declined by 13% this week, signaling a potential return to late-stage bear market conditions. The price fell to around $67k, positioned between the Realized Price and Realized Cap Weighted Average. For the first time since early 2022, the Short-Term Holder cost basis has dropped below this key average, confirming a hallmark of late-cycle bear markets. Profitability metrics have collapsed sharply. The 7-day average of the Realized Profit/Loss ratio plummeted from a local high of 3.16 to 0.29, mirroring the February panic sell-off. Critically, the 90-day average never breached the threshold of 2, indicating the recent rally to $82k was a bear market bounce, not a structural shift. Realized losses surged to $1.35 billion daily, with $770 million coming from Long-Term Holders selling at a loss. This accelerating redistribution of supply from weak to strong hands is a necessary but ongoing process for a market bottom. The rally stalled almost precisely at the aggregate cost basis (~$83k) of US spot Bitcoin ETF investors, turning that level into strong resistance and leaving the average ETF holder underwater again. Spot market flows have turned decisively negative, showing sellers are dominating order books despite the price drop. While a significant futures long liquidation event cleared over $400 million in leverage, providing a potential reset, sustained spot demand is yet to materialize. Options markets continue to price in higher future volatility (Implied Volatility) than recent price action (Realized Volatility) has shown, with a persistent skew towards put options, indicating ongoing demand for downside protection. In conclusion, multiple metrics point to a fragile market structure. Resistance at the ETF cost basis, accelerating realized losses, dominant spot selling, and cautious options pricing all suggest the bear market trend persists. A sustainable recovery likely requires a resurgence of spot demand, ETF holders returning to profit, and a clear reduction in selling pressure.

marsbit1 ч. назад

Has Bitcoin's 'Rebound Ended', Officially Entering the Late Bear Market Phase?

marsbit1 ч. назад

Торговля

Спот
Фьючерсы

Популярные статьи

Как купить ERA

Добро пожаловать на HTX.com! Мы сделали приобретение Caldera (ERA) простым и удобным. Следуйте нашему пошаговому руководству и отправляйтесь в свое крипто-путешествие.Шаг 1: Создайте аккаунт на HTXИспользуйте свой адрес электронной почты или номер телефона, чтобы зарегистрироваться и бесплатно создать аккаунт на HTX. Пройдите удобную регистрацию и откройте для себя весь функционал.Создать аккаунтШаг 2: Перейдите в Купить криптовалюту и выберите свой способ оплатыКредитная/Дебетовая Карта: Используйте свою карту Visa или Mastercard для мгновенной покупки Caldera (ERA).Баланс: Используйте средства с баланса вашего аккаунта HTX для простой торговли.Третьи Лица: Мы добавили популярные способы оплаты, такие как Google Pay и Apple Pay, для повышения удобства.P2P: Торгуйте напрямую с другими пользователями на HTX.Внебиржевая Торговля (OTC): Мы предлагаем индивидуальные услуги и конкурентоспособные обменные курсы для трейдеров.Шаг 3: Хранение Caldera (ERA)После приобретения вами Caldera (ERA) храните их в своем аккаунте на HTX. В качестве альтернативы вы можете отправить их куда-либо с помощью перевода в блокчейне или использовать для торговли с другими криптовалютами.Шаг 4: Торговля Caldera (ERA)С легкостью торгуйте Caldera (ERA) на спотовом рынке HTX. Просто зайдите в свой аккаунт, выберите торговую пару, совершайте сделки и следите за ними в режиме реального времени. Мы предлагаем удобный интерфейс как для начинающих, так и для опытных трейдеров.

726 просмотров всегоОпубликовано 2025.07.17Обновлено 2026.06.02

Как купить ERA

Обсуждения

Добро пожаловать в Сообщество HTX. Здесь вы сможете быть в курсе последних новостей о развитии платформы и получить доступ к профессиональной аналитической информации о рынке. Мнения пользователей о цене на ERA (ERA) представлены ниже.

活动图片