世界上最快的超級電腦 El Capitan 對區塊鏈技術不構成威脅

El Capitan 是一款由 AMD（納斯達克股票代碼：AMD）晶片驅動的超級計算機，已成為世界上速度最快的超級電腦。雖然速度快了 500 萬倍以上

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（納斯達克股票代碼：AMD）晶片驅動的超級計算機，已成為世界上最快的超級計算機。它比典型的家用電腦快 500 萬倍以上，但其開發人員表示，它不會對支撐區塊鏈技術的加密技術構成威脅。

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 由位於加州的聯邦研究機構勞倫斯利弗莫爾國家實驗室與 AMD、惠普（NYSE：HPQ）和能源部 (DOE) 合作開發。它在兩年一度的世界最快超級電腦 500 強排行榜上擊敗了衛冕冠軍 Frontier，最高性能達到 170 萬億次浮點運算和每秒 2.79 萬億次計算。

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.”

用外行的話來說，該項目背後的思想家之一 Jeremy Thomas 指出，“需要超過 100 萬台最新 iPhone 同時進行一項計算，才能相當於 El Capitan 一秒鐘的速度。”

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.

與許多其他超級電腦一樣，El Capitan 的巨大能力被用於模擬。目前，它被用來運行核爆模擬，以便更好地了解這些武器可能引發的破壞。

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，湯瑪斯駁斥了有關超級電腦將發展到足以威脅區塊鏈技術的擔憂，認為這種擔憂毫無根據。儘管 El Capitan 的功能強大得難以想像，但它仍然以二進位形式處理資料。它的超能力來自於任務並行化，它可以同時處理數百萬個任務。專家表示，這不太可能破解區塊鏈技術的密碼技術。

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.

量子計算機是完全不同的遊戲。與超級電腦不同，它們不受 0 和 1 二進制計算性質的限制，而是依賴量子位，量子位可以同時存在於多種狀態，也可以連結在一起以實現無限更快的處理。

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.

10月，上海大學的中國研究人員聲稱首次用量子電腦破解了經典加密技術。儘管有這樣的說法和其他類似的說法，大多數專家認為我們距離這些計算機構成重大威脅還有十多年的時間。

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.

儘管如此，公共和私人實體仍在投資後量子安全。蘋果（納斯達克股票代碼：AAPL）和谷歌（納斯達克股票代碼：GOOGL）已經發布了他們聲稱是量子證明的更新。隨著量子和人工智慧 (AI) 驅動的網路攻擊的威脅日益增加，一些政府也在量子安全技術上投資數百萬美元。

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.

在量子運算領域，Google推出了最先進的人工智慧系統，用於識別量子運算錯誤。它被稱為 AlphaQubit，在一些測試中的效能提升高達 30%，可以使量子電腦更接近現實世界的應用。

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 的人工智慧研究團隊和 Google Quantum AI 的量子團隊合作的成果。

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.

量子計算機的性能超越了傳統計算機。後者依賴位元（0 和 1），而量子電腦則使用量子位元，量子位元可以同時存在於多種狀態並連結在一起，以實現指數級更快、更複雜的處理。一些量子計算機，如Google的 Sycamore，在 200 秒內完成了傳統計算機需要 10,000 年才能完成的任務。

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，量子計算非常脆弱，可能會因最輕微的環境變化而受到干擾。這長期以來阻礙了其實際應用，使得識別和糾正量子錯誤成為該領域研究人員更關鍵的追求之一。

“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.

谷歌在英國科學雜誌《自然》上發表的論文中表示：“如果我們想讓量子計算機更加可靠，特別是在規模上，我們需要準確識別並糾正這些錯誤。”

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.

多年來，Google團隊一直致力於對其 Sycamore 量子電腦進行糾錯。 Sycamore 使用先進的方法來修正錯誤，例如從多個硬體量子位元創建單一邏輯量子位元。 AlphaQubit 是這項工作的延伸，本質上是一種為 Sycamore 和其他量子電腦尋找和糾正這些錯誤的新方法。

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.

根據 Google 團隊的說法，當參數面向準確度時，AlphaQubit 將糾錯率提高了 6%；在速度更快但準確度較低的測試中，糾錯率提高了 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.

該團隊得出的結論是，人工智慧和機器學習可能是識別和糾正量子錯誤的解決方案。 AlphaQubit 的人工智慧系統可從真實實驗數據中了解雜訊和洩漏錯誤，並能夠在現實世界的模擬中識別此類錯誤。

“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：“這種使用可用實驗信息的能力展示了機器學習在更廣泛地解決科學問題方面的優勢。”

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.

雖然 AlphaQubit 是量子運算的一大進步，但它只是基礎性的，在量子電腦成為科學實驗之外的有用工具之前，還需要進行更多的研究和開發。目前，這些計算機的錯誤率為千分之一；一些研究人員表示，他們需要將這一數字減少到萬億分之一才能實用。