世界上最快的超级计算机 El Capitan 对区块链技术不构成威胁

El Capitan 是一款由 AMD（纳斯达克股票代码：AMD）芯片驱动的超级计算机，已成为世界上速度最快的超级计算机。虽然速度快了 500 万倍以上

El Capitan, a supercomputer powered by Advanced Micro Devices Inc (NASDAQ:AMD) chips, has become the world’s fastest supercomputer. It is over 5 million times faster than a typical home computer, but its developers say it poses no threat to the cryptography techniques that underpin blockchain technology.

El Capitan 是一款由 Advanced Micro Devices Inc（纳斯达克股票代码：AMD）芯片驱动的超级计算机，已成为世界上速度最快的超级计算机。它比典型的家用计算机快 500 万倍以上，但其开发人员表示，它不会对支撑区块链技术的加密技术构成威胁。

El Capitan was developed by the Lawrence Livermore National Laboratory, a federal research facility based in California, in partnership with AMD, HP (NYSE:HPQ), and the Department of Energy (DOE). It toppled reigning champion Frontier on the biannual Top 500 list of the world’s fastest supercomputers, hitting a maximum performance of 1.7 million teraflops and 2.79 quadrillion calculations per second.

El Capitan 由位于加利福尼亚州的联邦研究机构劳伦斯利弗莫尔国家实验室与 AMD、惠普（纽约证券交易所代码：HPQ）和能源部 (DOE) 合作开发。它在两年一度的世界最快超级计算机 500 强排行榜上击败了卫冕冠军 Frontier，最高性能达到 170 万万亿次浮点运算和每秒 2.79 万亿次计算。

In layman’s terms, Jeremy Thomas, one of the minds behind the project, noted that “it would take more than a million of the latest iPhones working on one calculation at the same time to equal what El Capitan can do in one second.”

用外行的话来说，该项目背后的思想家之一 Jeremy Thomas 指出，“需要超过 100 万台最新 iPhone 同时进行一项计算，才能相当于 El Capitan 一秒钟的速度。”

Like many other supercomputers, El Capitan's immense power is being channeled to simulations. Currently, it is being used to run simulations for nuclear blasts to better understand the devastation that these weapons could set off.

与许多其他超级计算机一样，El Capitan 的巨大能力被用于模拟。目前，它被用来运行核爆炸模拟，以更好地了解这些武器可能引发的破坏。

However, Thomas dismissed fears that supercomputers would advance enough to threaten blockchain technology as unfounded. El Capitan still processes data in binary form, despite being unimaginably powerful. Its superpower comes from task parallelization, where it handles millions of tasks simultaneously. Experts say this is unlikely to crack blockchain technology's cryptographic techniques.

然而，托马斯驳斥了有关超级计算机将发展到足以威胁区块链技术的担忧，认为这种担忧毫无根据。尽管 El Capitan 的功能强大得难以想象，但它仍然以二进制形式处理数据。它的超能力来自于任务并行化，它可以同时处理数百万个任务。专家表示，这不太可能破解区块链技术的密码技术。

Quantum computers are a whole different ballgame. Unlike supercomputers, they are not limited by the 0s-and-1s binary nature of computing, relying instead on qubits, which can exist in multiple states at once or be linked together for infinitely faster processing.

量子计算机是完全不同的游戏。与超级计算机不同，它们不受 0 和 1 二进制计算性质的限制，而是依赖于量子位，量子位可以同时存在于多种状态，也可以链接在一起以实现无限更快的处理。

In October, Chinese researchers from Shanghai University claimed to have cracked classical encryption techniques with a quantum computer for the first time. Despite this and other similar claims, most experts believe we’re still over a decade away from these computers posing a substantial threat.

十月，上海大学的中国研究人员声称首次用量子计算机破解了经典加密技术。尽管有这样的说法和其他类似的说法，大多数专家认为我们距离这些计算机构成重大威胁还有十多年的时间。

Still, public and private entities are investing in post-quantum security. Apple (NASDAQ:AAPL) and Google (NASDAQ:GOOGL) have already released updates that they claim are quantum-proof. Several governments are also investing millions of dollars in quantum security technologies as the threat of quantum- and artificial intelligence (AI)-powered cyberattacks rises daily.

尽管如此，公共和私人实体仍在投资后量子安全。苹果（纳斯达克股票代码：AAPL）和谷歌（纳斯达克股票代码：GOOGL）已经发布了他们声称是量子证明的更新。随着量子和人工智能 (AI) 驱动的网络攻击的威胁日益增加，一些政府也在量子安全技术上投资数百万美元。

In the quantum computing field, Google has introduced the most advanced AI-powered system for identifying quantum computing errors. Known as AlphaQubit, it clocked up to a 30% improvement in some tests and could bring quantum computers closer to real-world applications.

在量子计算领域，谷歌推出了最先进的人工智能系统，用于识别量子计算错误。它被称为 AlphaQubit，在一些测试中的性能提升高达 30%，可以使量子计算机更接近现实世界的应用。

AlphaQubit is the result of a collaboration between a team of AI researchers from Google DeepMind and a quantum team from Google Quantum AI.

AlphaQubit 是 Google DeepMind 的人工智能研究团队和 Google Quantum AI 的量子团队合作的成果。

Quantum computers perform leaps and bounds above classical computers. While the latter relies on bits (0s and 1s), quantum computers use qubits, which can exist in multiple states simultaneously and be linked together for exponentially faster and more complex processing. Some quantum computers, like Google’s Sycamore, have completed a task in under 200 seconds that would have taken a classical computer 10,000 years.

量子计算机的性能超越了传统计算机。后者依赖于位（0 和 1），而量子计算机则使用量子位，量子位可以同时存在于多种状态并链接在一起，以实现指数级更快、更复杂的处理。一些量子计算机，如谷歌的 Sycamore，在 200 秒内完成了传统计算机需要 10,000 年才能完成的任务。

However, quantum computing is incredibly fragile and can be disrupted by the slightest environmental changes. This has long hampered its use for practical purposes, making identifying and correcting quantum errors one of the more critical pursuits for researchers in the field.

然而，量子计算非常脆弱，可能会因最轻微的环境变化而受到干扰。这长期以来阻碍了其实际应用，使得识别和纠正量子错误成为该领域研究人员更关键的追求之一。

“If we want to make quantum computers more reliable, especially at scale, we need to accurately identify and correct these errors,” Google says in its paper, published in the British scientific journal Nature.

谷歌在英国科学杂志《自然》上发表的论文中表示：“如果我们想让量子计算机更加可靠，特别是在规模上，我们需要准确识别并纠正这些错误。”

The Google team has been working on error correction for its Sycamore quantum computer for years. Sycamore uses advanced methods to correct errors, such as creating single logical qubits from multiple hardware qubits. AlphaQubit is an extension of this work and is essentially a new way to find and correct these errors for Sycamore and other quantum computers.

多年来，谷歌团队一直致力于对其 Sycamore 量子计算机进行纠错。 Sycamore 使用先进的方法来纠正错误，例如从多个硬件量子位创建单个逻辑量子位。 AlphaQubit 是这项工作的延伸，本质上是一种为 Sycamore 和其他量子计算机查找和纠正这些错误的新方法。

According to the Google team, AlphaQubit improved error correction by 6% when the parameters were geared toward accuracy and by 30% in faster, albeit less accurate, tests.

根据 Google 团队的说法，当参数面向准确度时，AlphaQubit 将纠错率提高了 6%；在速度更快但准确度较低的测试中，纠错率提高了 30%。

The team concludes that AI and machine learning could be the solution to identifying and correcting quantum errors. AlphaQubit's AI-powered system learned about noise and leakage errors from real experimental data and was able to identify such errors in real-world simulations.

该团队得出的结论是，人工智能和机器学习可能是识别和纠正量子错误的解决方案。 AlphaQubit 的人工智能系统从真实实验数据中了解噪声和泄漏错误，并能够在现实世界的模拟中识别此类错误。

“This ability to use available experimental information showcases a strength of machine learning for solving scientific problems more generally,” Google says.

谷歌表示：“这种使用可用实验信息的能力展示了机器学习在更广泛地解决科学问题方面的优势。”

While a big step in quantum computing, AlphaQubit is only foundational, and much more research and development will be needed before quantum computers become useful tools beyond scientific experiments. Currently, these computers have an error rate of one in a thousand; according to some researchers, they need to reduce this to one in a trillion to become practical.

虽然 AlphaQubit 是量子计算的一大进步，但它只是基础性的，在量子计算机成为科学实验之外的有用工具之前，还需要进行更多的研究和开发。目前，这些计算机的错误率为千分之一；一些研究人员表示，他们需要将这一数字减少到万亿分之一才能实用。