雖然媒體一直緊盯哪個國家能開發出最先進人工智能系統，但另一項重要的競賽也在不斷升溫，就是誰能第一個造出量子計算機。

該領域近年來突飛猛進，2018年可能會出現重大突破。這是所謂的“量子霸權”競賽，研發完成后量子計算機不管處理任何任務性能都會明顯超過傳統超級計算機。

谷歌和IBM都是量子計算領域的領跑者，也都制定了實現目標的計劃。英特爾也加入競爭，上周拉斯維加斯國際消費電子展上發布了為量子計算研究設計的新型49量子比特神經形態芯片。

這項技術牽涉甚廣。量子計算機有可能為目前一些最難的數學和計算問題提供新角度，比如人體健康方面分析多組基因的相互作用，為化學品能態建模以及預測原子粒子的行為。互聯網的安全性可能會遭到削弱，因為量子計算機可以迅速破解用于保護IT基礎設施和網絡的密碼系統。

有一件事確定無疑，即量子計算時代很快就會到來，而且世界會出現極大變化。

簡單來說，量子計算機使用的技術單位是量子比特。普通半導體用一串1和0來表達信息，而量子比特代表的是量子性，計算時可同時作為1和0。也就是說，兩個量子比特就可以代表1-0、1-1、0-1和0-0四個數字序列，而且每增加一個量子比特，計算能力就會呈指數級增長。理論上，一臺量子計算機只要有50個量子比特的運算能力，就能超過當今性能最強大的超級計算機。

量子計算機來得也正是時候。摩爾定律預計，單位計算能力每18個月就會翻一番，而單位計算能力的價格會下降一半。雖然定律本身沒什么問題，但如今實現進步所需的資金已經遠遠超過以往。換句話說，每次為了提高速度，半導體公司和研究機構增加的研發開支越來越多。而另一方面，量子計算正在迅速崛起。

量子計算公司D-Wave Systems稱正在銷售的量子計算機有2000個量子比特。不過爭議一直存在。有些研究者發現該公司的計算機作用很大，但性能上一直未能超越普通計算機，而且只能用于解決某些問題，即優化方面的問題，優化是指在所有可行解決方案中找出最好選項。舉個例子，如果某個復雜模擬問題有多個可能的結果，D-Wave計算機可能就沒那么容易解決。此外，外界認為該公司的量子計算方式打敗超級計算機的希望并不大。

另一方面，谷歌、IBM以及眾多初創公司正努力打造的量子計算機可能會更靈活也更強大，因為能處理各種各樣的問題。幾年前，新型計算機通常擁有2-4個量子比特。過去一年中，各公司接連發布性能更強大的量子計算機。2017年11月IBM實現關鍵突破，宣布已造出有50個量子比特的計算機，也是科學家認為量子計算機超越傳統超算的水平。

壞消息呢？IBM這款計算機每次保持量子計算狀態的時間只有90微妙。實際上，量子計算時普遍存在于不穩定情況，必須采用強力冷卻手段才能維持工作；還得另行計算一遍，以便糾正早期量子計算機由于不穩定而出現的計算錯誤。不過，科學家正迅速改善不穩定的問題，希望五年內能造出可在室溫下正常工作的量子計算機。

下面解釋一下為什么量子計算與AI結合前景光明。隨著大規模應用AI初步產生重大影響，人們意識到基于半導體的傳統計算機限制了通過AI解決重大問題的能力。科學家預計，量子計算機不用脫離冷庫就能協助一些非常重要的運算。

量子計算有可能填補空缺，通過強大的運算能力解決重大挑戰。精準醫療、廉價能源以及超強新型材料都是量子計算可能實現突破的領域，因為量子計算機可以將體積壓縮至極小，卻能完成數以十億計的運算。谷歌的研究人員曾描繪過前景——他們用量子計算機模擬了氫分子的電子結構，這是化工設計從憑經驗測量和有根據的猜測變成準確的工程和模擬過程中關鍵步驟（也可用于研發新藥）。

雖然應用前景廣闊，但量子計算的危害也不容小覷。量子計算機可以輕松破解目前大多數加密模式（雖然安全專家已經在制作量子比特無法破解的加密代碼）。舉例來說，如果俄羅斯或中國等國家在量子計算領域占據優勢，完全有可能從事更隱秘的黑客活動以及破解加密通信等。

在政府、大公司、創業企業和大學實驗室里，聰明的工程師們正為量子霸權爭分奪秒地研發。最后的勝負結果也確實可能改變全球勢力格局。（財富中文網）

維維克·瓦德哈是卡耐基梅隆大學工程學院杰出研究員。亞歷克斯·索克埃爾是一位作家、演說家，曾在Mozilla擔任營銷副總裁。兩人合作撰寫了《無人駕駛汽車中的司機：技術選擇怎樣塑造未來》（The Driver in the Driverless Car: How Our Technology Choices Will Create the Future）一書。

譯者：Charlie

審校：夏林

While much of the media attention has been focused on the race among nations to develop the most powerful artificial intelligence systems, an equally crucial race has been heating up: the race to build the first working quantum computers.

As progress in the field accelerates at an exponential rate, 2018 should see an avalanche of breakthroughs. It is a race for so-called “quantum supremacy,” when a quantum computer demonstrably and markedly outperforms a classical supercomputer for any class of problems.

Booth Google (GOOG, +0.96%) and IBM (IBM, +2.82%), two leaders in quantum computing, have laid out plans to achieve this goal. Intel (INTC, +2.92%) also has a horse in the race, announcing a new 49 qubit neuromorphic chip designed for quantum computing research at the annual Consumer Electronics Show in Las Vegas last week.

The stakes are enormous. Quantum computers promise to set a new paradigm for solving some of the hardest math and computing problems today—problems such as analyzing the interactions of multiple genes in health outcomes, modeling the energy states of chemicals, and predicting the behavior of atomic particles. They also might make the Internet inherently insecure by quickly cracking modern cryptography used to lock our IT infrastructure and the web.

One thing is for sure: The era of quantum computing is coming on soon, and the world will never be the same.

Put simply, quantum computers use a unit of computing called a qubit. While regular semiconductors represent information as a series of 1s and 0s, qubits exhibit quantum properties and can compute as both a 1 and a 0 simultaneously. That means two qubits could represent the sequence 1-0, 1-1, 0-1, 0-0 at the same moment in time. This compute power increases exponentially with each qubit. A quantum computer with as few as 50 qubits could, in theory, pack more computing power than the most powerful supercomputers on earth today.

This comes at a timely juncture. Moore’s Law dictated that computing power per unit would double every 18 months while the price per computing unit would drop by half. While Moore’s Law has largely held true, the amount of money required to squeeze out these improvements is now significantly greater than it was in the past. In other words, semiconductor companies and researchers must spend more and more money in R&D to achieve each jump in speed. Quantum computing, on the other hand, is in rapid ascent.

One company, D-Wave Systems, is selling a quantum computer that it says has 2,000 qubits. However, D-Wave computers are controversial. While some researchers have found good uses for D-Wave machines, these quantum computers have not beaten classical computers and are only useful for certain classes of problems—optimization problems. Optimization problems involve finding the best possible solution from all feasible solutions. So, for example, complex simulation problems with multiple viable outcomes may not be as easily addressable with a D-Wave machine. The way D-Wave performs quantum computing, as well, is not considered to be the most promising for building a true supercomputer-killer.

Google, IBM, and a number of startups are working on quantum computers that promise to be more flexible and likely more powerful because they will work on a wider variety of problems. A few years ago, these flexible machines of two or four qubits were the norm. During the past year, company after company has announced more powerful quantum computers. In November 2017, IBM announced that it has built such a quantum machine that uses 50 qubits, breaking the critical barrier beyond which scientists believe quantum computers will shoot past traditional supercomputers.

The downside? The IBM machine can only maintain a quantum computing state for 90 microseconds at a time. This instability, in fact, is the general bane of quantum computing. The machines must be super-cooled to work, and a separate set of calculations must be run to correct for errors in calculations due to the general instability of these early systems. That said, scientists are making rapid improvements to the instability problem and hope to have a working quantum computer running at room temperature within five years.

And here’s where the confluence of quantum computing and AI looks so promising. As we are seeing the first major impacts of wide-scale artificial intelligence, we are also realizing that classic semiconductor-based computing limits our ability to solve the biggest problems that we had hoped artificial intelligence could tackle. They expect quantum computers to start performing very useful calculations well before they’re ready to leave the freezer.

Quantum computing promises to step into that breach and provide the rocket fuel needed to solve these grand challenges. Precisely targeted medical treatments, radically cheaper energy production, and new types of super-strong materials are all breakthroughs that quantum computing could make possible by performing billions and billions of calculations simultaneously in a relatively small package. Google researchers demonstrated the promise when they used quantum computing to simulate the electron structure of a hydrogen molecule, a key step toward moving chemical design from empirical measurement and educated guesses to more proper engineering and simulation. (This will also work for drug discovery.)

The perils of quantum computing are also real. Quantum computers will be able to easily crack most forms of encryption in use today (although security experts are already at work on creating codes that are not crackable by qubit attack). Should Russia or China, for example, gain quantum computing dominance—which is entirely possible—they could use their advantage for even more sophisticated hacking and decrypting of encoded communications.

Between governments, big companies, startups, and university labs, some of the brightest engineering minds are rushing toward quantum supremacy. This literally could shift the global balance of power.

Vivek Wadhwa is a distinguished fellow at Carnegie Mellon University’s College of Engineering and Alex Salkever is an author, public speaker, and former vice president of marketing at Mozilla. Together they authored The Driver in the Driverless Car: How Our Technology Choices Will Create the Future.