IBM заявила о прорыве в создании квантовых компьютеров

cryptonews.ru2025-11-24 tarihinde yayınlandı2025-11-24 tarihinde güncellendi

Компания IBM представила новый процессор и экспериментальный чип для отказоустойчивых вычислений. Фирма также изложила планы по достижению квантового превосходства к 2026 году.

«Создание действительно полезных квантовых вычислений требует решения множества фундаментальных задач. Мы уверены, что только IBM обладает всем необходимым, чтобы одновременно развивать и масштабировать квантовые технологии: от программного и аппаратного обеспечения до производства и коррекции ошибок», — заявил директор IBM Research Джей Гамбетта.

По словам разработчиков, новый Nighthawk — самый продвинутый сегодня квантовый процессор. Среди ключевых характеристик:

  • 120 кубитов, соединенных улучшенными настраиваемыми связями с ближайшими соседями. Число соединений увеличено на 20% по сравнению с предыдущей моделью Heron;
  • возможность запускать квантовые схемы на 30% сложнее, чем раньше, без роста числа ошибок;
  • архитектура позволяет решать задачи, требующие до 5000 двухкубитных операций — базовых элементов квантовых вычислений, основанных на феномене запутанности.

IBM ожидает, что производительность процессоров Nighthawk будет последовательно расти: к концу 2026 года они смогут обрабатывать до 7500 квантовых операций, в 2027 году — до 10 000, а к 2028 году — до 15 000 операций.

Процессор Nighthawk. Источник: IBM.

Первые системы Nighthawk поступят в продажу к концу 2025 года.

Еще одно обновление затронуло флагманское ПО Qiskit. В новой версии разработчики получили расширенный контроль над квантовыми схемами: реализованы динамические контуры, повышающие точность вычислений на 24% при работе с более чем 100 кубитами.

Дополнительно IBM внедрила в Qiskit усовершенствованную систему выполнения задач и C-API интерфейс, что в сочетании с HPC-ускорением позволяет снизить стоимость обработки квантовых ошибок более чем в 100 раз при сохранении точности результатов.

К 2027 году фирма планирует добавить вычислительные библиотеки для машинного обучения и оптимизации, чтобы помочь исследователям моделировать физические и химические системы.

IBM спроектирует отказоустойчивый квантовый компьютер

Отказоустойчивость

Компания также выпустила Loon — экспериментальный процессор, который объединяет ключевые аппаратные компоненты для отказоустойчивых квантовых вычислений. Такие системы способны выявлять и устранять сбои в режиме реального времени.

Как заявили разработчики, компания достигла десятикратного ускорения в исправлении ошибок, научившись выполнять коррекцию менее чем за 480 наносекунд. Рубеж прошли на год раньше запланированного срока.

После перевода производства на новую фабрику в Нью-Йорке IBM удалось удвоить темпы разработки чипов, говорится в пресс-релизе.

В компании уверены: достижения знаменуют устойчивый прогресс в создании масштабируемых квантовых систем и создают основу для практического применения квантовых вычислений в обозримом будущем.

IBM обещает представить первый в мире крупномасштабный отказоустойчивый квантовый компьютер к 2029 году.

Ранее о достижении «верифицируемого квантового превосходства» с помощью нового алгоритма Quantum Echoes заявила корпорация Google.

Квантовые вычисления и биткоин

Создание квантовых компьютеров пока находится на ранней стадии. Для взлома эллиптической криптографии биткоина потребовалась бы система на примерно 2000 логических кубитов.

С учетом необходимой коррекции ошибок это эквивалентно десяткам миллионов физических кубитов.

Для сравнения: новый процессор Quantum Nighthawk от IBM содержит 120 кубитов и ориентирован на выполнение сложных вычислений при сохранении низкого уровня ошибок. Пока его возможности все еще на порядок ниже требуемых для взлома криптографии первой криптовалюты.

Однако способность квантовых компьютеров взломать шифрование цифровых активов на базе механизма консенсуса Proof-of-Work стала одной из самых обсуждаемых тем в криптоиндустрии.

Согласно прогнозу проекта Quantum Doomsday Clock, квантовые вычисления станут действительно опасными уже через два года. Но многие исследователи с этим мнением не согласны.

Например, профессор Мичиганского университета Кристофер Пейкерт считает, что в ближайшие несколько лет реальной угрозы нет.

Другие призывают действовать уже сейчас. Среди них — основатель фонда Capriole Чарльз Эдвардс.

If Bitcoin doesn't solve Quantum in the next year, Gold will keep outperforming it forever. This risk is starting to be a drag on BTC. https://t.co/eWp6rsH1BC

— Charles Edwards (@caprioleio) October 15, 2025

«Если мы не решим проблему квантовых вычислений до следующего года, золото и дальше будет опережать биткоин», — писал он в октябре.

Напомним, в июле группа разработчиков нашла способ защитить сеть первой криптовалюты от потенциальных угроз со стороны квантовых компьютеров.

Собиратель секретов. Почему квантовые компьютеры угрожают приватности биткоина

İlgili Okumalar

Behind the AI Scorecards Lies a Chinese 'Question Setter'

Behind the AI scorecards that dominate industry discussions—benchmarks like MMLU-Pro, MMMU, and MMMU-Pro—stands a Chinese-Canadian researcher: Wenhu Chen. As an assistant professor at the University of Waterloo and founder of the TIGER Lab, Chen has become a key "exam-setter" for evaluating large language and multimodal models. Chen first gained broader recognition with MMLU-Pro, a more challenging and stable update to the popular MMLU benchmark. As top models like OpenAI’s o3 began achieving near-perfect scores on the original MMLU, it became difficult to distinguish their true capabilities. MMLU-Pro introduced more complex reasoning questions, expanded answer choices, and filtered out ambiguous or simple items, effectively reintroducing differentiation among state-of-the-art models. His work on MMMU addressed the evaluation of multimodal models, requiring them to integrate visual information (like charts, diagrams, or tables) with textual knowledge across diverse academic subjects. Even the strongest models initially scored only around 56-59%, highlighting significant room for improvement in genuine multimodal reasoning. MMMU-Pro further refined this by preventing models from bypassing visual cues. Chen’s research focus has long been on complex information understanding and reasoning. His background—including a PhD at UC Santa Barbara, research at Google/DeepMind on Gemini, and now a role in Meta’s superintelligence lab—provides deep insight into model development and their potential weaknesses. His TIGER Lab also builds models (e.g., for video understanding and generation), ensuring his evaluation benchmarks are grounded in practical challenges. While AI headlines often spotlight company leaders and product launches, Chen’s work exemplifies the critical, behind-the-scenes contributions of researchers crafting the rigorous standards that define and drive progress in AI capabilities.

marsbit26 dk önce

Behind the AI Scorecards Lies a Chinese 'Question Setter'

marsbit26 dk önce

STRC Unpegged by 11%, Can Strategy's Perpetual Motion Machine Keep Turning?

STRC, the perpetual preferred stock of MicroStrategy, is experiencing a persistent de-pegging from its target par value of $100, with the discount recently widening to over 11%. This de-anchoring challenges the core design of STRC, which was intended as a stable, income-oriented security operating near $100. As a crucial funding engine for MicroStrategy's Bitcoin acquisition strategy, STRC's price reflects market confidence in the company's entire capital model. The company's "capital flywheel" relies on issuing STRC at or above $100 via an At-the-Market (ATM) program to raise cash for buying Bitcoin, thereby boosting company equity and theoretically supporting STRC's value. A monthly adjustable dividend mechanism was designed to maintain this peg. Despite raising the dividend to 11.5% and increasing payment frequency, the de-pegging persists. Market concerns extend beyond technical factors like leveraged arbitrage unwinding. Analysts point to MicroStrategy's limited cash reserves relative to its ~$1.7 billion annual dividend obligation for preferred shares. While the company counters that its vast Bitcoin holdings could cover decades of payments, this argument hinges on the potential need to sell Bitcoin—a shift from its longstanding "hodl" narrative. The company's recent sale of a small amount of BTC, framed as a test, amplified these liquidity and strategy concerns. If STRC remains discounted, impairing MicroStrategy's ability to raise cheap capital, fears may grow that the company could sell more Bitcoin to meet obligations. This scenario could transform MicroStrategy from a major market buyer into a potential seller, posing significant downside risk for Bitcoin. The re-pegging of STRC is thus a key indicator for the health of MicroStrategy's capital structure and its market impact.

Odaily星球日报39 dk önce

STRC Unpegged by 11%, Can Strategy's Perpetual Motion Machine Keep Turning?

Odaily星球日报39 dk önce

Silicon Valley's Most Sought-After New Role Has Emerged

Silicon Valley's New Most Wanted Job: The Rise of the Forward Deployment Engineer The AI industry is witnessing a significant shift. The focus has moved from developing cutting-edge models to deploying them effectively within enterprises. This has made the "Forward Deployment Engineer" (FDE) a critical and highly sought-after role at major firms like OpenAI, Anthropic, and Google. For the past three years, the industry prioritized model scientists. However, companies are now facing a harsh reality: purchasing powerful AI tools does not guarantee productivity gains or organizational change. The biggest hurdle is not the technology itself, but integrating it into complex legacy systems, workflows, and corporate cultures. This includes challenges like data silos, compliance requirements, and internal resistance. The FDE role, pioneered by Palantir Technologies, addresses this "last-mile" problem. FDEs are deployed on-site with clients for extended periods. Their job is to deeply understand the client's specific organizational structure, processes, and pain points, then tailor and implement the AI solution accordingly. They combine skills in technology, project management, and organizational change. A clear signal of this trend emerged in May 2026 when three AI giants made major moves. Anthropic launched a $1.5B joint venture for enterprise deployment. OpenAI formed an independent deployment subsidiary, DeployCo, with over $4B in commitments and acquired a deployment consultancy. Google Cloud's CEO publicly announced a large-scale recruitment drive for FDEs. This shift represents a fundamental change in the software business model: from selling tools to selling guaranteed outcomes. FDEs are the agents of this change, responsible for delivering a working system within the production environment, not just a demo. Real-world cases, such as challenges at Goldman Sachs (compliance barriers) and Target (internal cultural resistance), illustrate that the primary obstacles to AI adoption are organizational, not technical. An FDE's value lies in navigating these human and procedural complexities to facilitate a successful "AI migration." In essence, as core AI technology becomes more accessible and affordable, the true premium is shifting to the human expertise required to understand organizations and drive change—making the FDE role pivotal for the next phase of the AI revolution.

marsbit40 dk önce

Silicon Valley's Most Sought-After New Role Has Emerged

marsbit40 dk önce

When the World Cup Collides with Agents: From Web2 to Web3, How Are Wallets Evolving into Agentic Wallets?

World Cup as a Catalyst for Agentic Wallets: From Web2 to Web3 This article explores how the World Cup provides a real-world scenario for observing the evolution of digital wallets from simple asset managers towards "Agentic Wallets"—intelligent, AI-powered interfaces. Using the example of prediction markets like Polymarket, it illustrates how AI Agents can lower the barrier to Web3 interaction. Instead of navigating complex DApps, users can express intent in natural language (e.g., "I think Portugal will win") within platforms like Discord or web pages. The Agent then interprets this intent, finds the relevant market, and seamlessly guides the user through the on-chain transaction via their wallet. The core shift is from wallets as mere "function menus" for signing transactions to "intent interpreters" that understand user goals. The article highlights parallel developments in traditional finance, such as Mastercard's "Agent Pay" and WeChat Pay's AI tests, which focus on granting AI controlled, authorized, and auditable payment capabilities. This underscores a broader trend of AI entering the financial layer. However, the article emphasizes that the primary challenge for Agentic Wallets in Web3 is not automation but establishing clear security boundaries. Unlike traditional systems with chargebacks, on-chain transactions are often irreversible. Therefore, future wallets must ensure users retain ultimate control and comprehension. They need to transparently communicate an Agent's permissions, spending limits, authorized durations, and provide easy ways to pause or revoke access. The World Cup experiments represent early steps toward wallets that are not just applications but ubiquitous, intelligent interfaces that simplify Web3 while keeping users securely in control.

marsbit2 saat önce

When the World Cup Collides with Agents: From Web2 to Web3, How Are Wallets Evolving into Agentic Wallets?

marsbit2 saat önce

Options Don't Work in DeFi? Vitalik Might Not Agree

For years, the prevailing view has been that options struggle to gain traction in DeFi due to complexity, fragmented liquidity, and lack of natural demand compared to products like perpetual futures. However, a recent algorithmic stablecoin design proposed by Vitalik Buterin presents a different perspective, using options not as a standalone trading product, but as foundational infrastructure for other financial instruments. In this design, one unit of ETH is split into two components: a "stable" side (P) that retains value up to a specified strike price, and an "upside" side (N) that captures all appreciation above that strike. Combined, they always equal one ETH, eliminating debt, margin, and liquidation risks inherent in typical collateralized debt position (CDP) stablecoins. The stable component essentially mimics the payoff of a covered call option. To function as a stablecoin, this structure requires continuously rolling deep in-the-money calls, which introduces challenges like rollover slippage, predictable transaction flow vulnerable to front-running, and persistent liquidity needs. A core hurdle is finding consistent buyers for the leveraged ETH upside exposure (N). While it offers leverage without funding rates or liquidation, it must compete with simpler alternatives like direct call options or perpetuals. The system's scalability depends on a sustained demand for this specific form of leverage. The author draws parallels to their experience with Rysk, where earlier versions of DeFi options protocols struggled. The breakthrough came with Rysk V12, which aligns incentives: asset holders generate yield by selling covered calls against their holdings, while market makers efficiently acquire the desired option exposure. This demonstrates that options can find product-market fit when embedded as a risk distribution and pricing engine within structured products, stablecoins, or yield-generating assets, rather than marketed as a complex direct trading instrument. Vitalik's proposal reinforces this architectural approach—using fully collateralized, non-custodial, and physically settled options as a fundamental building block. The real opportunity for options in DeFi may lie not in becoming the next perpetual swap, but in powering the next generation of on-chain financial products.

marsbit2 saat önce

Options Don't Work in DeFi? Vitalik Might Not Agree

marsbit2 saat önce

İşlemler

Spot
Futures
活动图片