譯科技 | 人工智能＋區(qū)塊鏈：雙倍的炒作還是雙倍的價值？

來源：Forbes 時間：2019-10-30 15:10:28 作者：Ron Schmelzer

AI and Blockchain： Double the Hype or Double the Value？

數(shù)據(jù)觀丨王婕（譯）

　　譯者按：過去的幾天，是“區(qū)塊鏈”成功“出圈”，引起極大關(guān)注和廣泛討論的幾天。習近平總書記明確要求把區(qū)塊鏈作為核心技術(shù)自主創(chuàng)新的重要突破口和主攻方向的講話，無疑成為了推動國內(nèi)區(qū)塊鏈行業(yè)快速發(fā)展的強心劑。

　　不過在積極擁抱區(qū)塊鏈的同時，不少專業(yè)、行業(yè)內(nèi)人士也表示，區(qū)塊鏈不是用來“炒”的，應凈化市場的浮躁。誠如他們所言，在冷靜之后，我們?nèi)孕桕P(guān)注的是真切的行業(yè)發(fā)展，是實實在在的應用落地。下面這篇文章，對于關(guān)注區(qū)塊鏈行業(yè)應用、關(guān)注區(qū)塊鏈技術(shù)與其他新興技術(shù)融合的人們來說也許能提供一些新的思路。

　　Artificial Intelligence（AI）as a market is full of hype，with vendors，customers，and press all speaking breathlessly about the capabilities for AI in general and their offerings specifically. Likewise，blockchain is also a widely hyped market，with technology providers and customers claiming all sorts of capabilities that may or may not be possible. Combining AI and blockchain then must be double the hype？On the other hand，AI is providing real，tangible value in many myriad ways we talk about every day. Likewise，blockchain is starting to show value across a range of applications and industry. So，perhaps combining AI and blockchain will also show twice the value combined together.

　　人工智能（AI）作為一個充滿炒作的市場，供應商、消費者和媒體都在高談闊論人工智能的大體功能和它們的具體產(chǎn)品。無獨有偶，區(qū)塊鏈也是一個被廣泛炒作的市場，技術(shù)供應商和其客戶都聲稱區(qū)塊鏈具有各種各樣的功能，無論它們存在與否。那么，人工智能與區(qū)塊鏈的融合是不是就自然而然地成為了雙重炒作？而從另一方面來看，人工智能正在以我們每天談論的無數(shù)種方式提供真實的、有形的價值。同樣的，區(qū)塊鏈也正在通過一系列應用程序及行業(yè)應用彰顯其價值。因此，將AI和區(qū)塊鏈相結(jié)合也許反而會得到雙重效果。

　　The role of blockchain in the context of AI區(qū)塊鏈在人工智能環(huán)境中的作用

　　Blockchain is a decentralized，distributed ledger of transactions that has elements of transparency，trust，verifiability，and something called smart contracts. Decentralized and distributed means that information that is stored across the network in such a way that each end point has access to the data without requiring access to a central server. The network is also distributed because the transactions happen at each end point without requiring centralized coordination. A ledger is a record of transactions. Blockchain records a ledger of interactions between two separate parties whether it be a financial exchange or even a chain of custody showing when things have changed hands over time.

　　區(qū)塊鏈是一個分散的、分布式的交易分類賬本，它包含透明性、可信任、可驗證性和智能合約等特性。分散和分布式意味著信息以這樣一種方式存儲在網(wǎng)絡上后，其中的每個節(jié)點都可以訪問數(shù)據(jù)，而不需要獲得中心服務器的許可。網(wǎng)絡也是分布式的，因為交易發(fā)生在每個終端，不需要集中協(xié)調(diào)。分類賬本是交易的記錄。區(qū)塊鏈記錄了兩個獨立的交易方之間的互動記錄，無論是金融交易所，還是監(jiān)管鏈，都顯示了隨著時間的推移，事情何時發(fā)生了變化。

　　Since every block in the blockchain contains a different piece of information that is encrypted or encoded， the blockchain can help guarantee trust and verifiability of data. The concept of the chain and block in blockchain is that each block has its own information and that information contains a link to the block before it， which develop the chain and provides a verifiable chain of custody. No individual actor can change the information in a block without invalidating the entire chain of information in a particular block and thus messing up the chain. Since the chain is distributed in myriad of other places and between other parties， to make changes to the chain， a consensus of all the parties would need to agree to the changes being made.

　　由于區(qū)塊鏈中的每個區(qū)塊都包含不同的經(jīng)過加密或編碼的信息，因此區(qū)塊鏈可以幫助確保數(shù)據(jù)的可信任性和可驗證性。區(qū)塊鏈中的“鏈”和“區(qū)塊”的概念是，每一個“區(qū)塊”都有自己的信息，這些信息包含了與其前面的“區(qū)塊”的鏈接，這些鏈接延伸“鏈”并形成了可驗證的監(jiān)管鏈。任何單個參與者都不可能在不使特定“區(qū)塊”中的整個信息鏈失效的情況下更改“區(qū)塊”中的信息，從而破壞這個“鏈”。由于該鏈分布在無數(shù)其他地方，并且在其他各方之間，一旦要對該鏈進行更改，就需要所有各方的一致同意。

　　Adding to the concept of the blockchain are smart contracts， which are decentralized pieces of code that can be triggered when a specific chain of actions has been met. In this way， when you have two parties wanting to execute a secure， trusted transaction without the use of an intermediary this is what blockchain ideally would be used for.

　　談到區(qū)塊鏈概念，就勢必會談到智能合約。它是分散的代碼片段，可以在滿足特定的操作鏈時觸發(fā)。通過這種方式，當你有兩個參與方希望執(zhí)行安全、可信的交易而不需要使用中介時，這將成為區(qū)塊鏈的理想用途。

　　So how can blockchain help with AI？ The first benefit is that you can share machine learning models among all parties without an intermediary. A good example is with facial recognition software. If one device knows what a person looks like and uploads it to the chain， other devices hooked up also know what that person looks like. When other devices upload their own facial recognition data， the other devices will gain the ability to use that for the facial recognition model. Since this happens on the blockchain， there is no central control over facial recognition， and as such no one company owns or stores the data. This approach also allows for everyone to learn faster and collaboratively through the use of integrated AI with blockchain.

　　那么區(qū)塊鏈該如何賦能人工智能？第一個好處就是你可以在無中介的情況下，在所有各方之間共享機器學習模型。面部識別軟件就是一個很好的例子：如果一個設備知道一個人的相貌并將其上鏈，那么其他連接的設備也能知道這個人的相貌。當其他設備上傳自己的面部識別數(shù)據(jù)時，其他設備將獲得將其用于面部識別模型的能力。由于這發(fā)生在區(qū)塊鏈上，沒有對面部識別的中央控制，因此沒有一家公司能夠擁有或存儲這些數(shù)據(jù)。這種方法還允許每個人都能通過使用集成的人工智能和區(qū)塊鏈來更快地參與學習和協(xié)作。

　　AI systems can also use blockchain to facilitate the sharing of data used across multiple models. A great example is the use of machine learning models for product recommendations in online retail. If an online store knows the preferences of one shopper， and then that customer goes to a different store website， these two sites can be connected through a blockchain to share trusted personalization information. This could potentially become a place of competition for smaller ecommerce sites that want to share with each other personalization information. Instead of each company gathering their own personalization data， they can share it amongst each other in a blockchain， providing competition to sites like Amazon and Walmart who have already developed their own data systems to gather this information about their customers. The benefit for this to the customer is that in exchange for sharing their information， they can get everything from better pricing to customized shopping experiences. This could also prevent data breaches if all information and payment systems are stored and shared through a blockchain rather than a centralized data server.

　　人工智能系統(tǒng)還可以通過使用區(qū)塊鏈來促進跨多個模型的數(shù)據(jù)共享。一個很好的例子是在在線零售中使用機器學習模型進行產(chǎn)品推薦。如果在線商店知道某個購物者的偏好，之后若該客戶轉(zhuǎn)到了另一個商店的網(wǎng)站，則可以通過區(qū)塊鏈連接這兩個站點，以共享可信的個性化信息。這可能會成為那些希望彼此間共享個性化信息的小型電子商務網(wǎng)站的必爭之地。不同于每家公司收集他們自己的個性化數(shù)據(jù)，他們可以在區(qū)塊鏈中互相分享這些數(shù)據(jù)，這無疑加劇了亞馬遜和沃爾瑪這樣的網(wǎng)站之間的競爭，尤其是當這些網(wǎng)站已經(jīng)開發(fā)了自己的數(shù)據(jù)系統(tǒng)來收集客戶的這些信息。而這對客戶的好處是，作為信息被分享的交換，他們可以從中得到更好的價格、定制化的購物體驗等服務。如果所有信息和支付系統(tǒng)都通過區(qū)塊鏈存儲和共享而不是集中的數(shù)據(jù)服務器，這還可以防止數(shù)據(jù)被泄露。

　　How blockchain can benefit AI區(qū)塊鏈如何賦能人工智能

　　Not only can blockchains be used to share models and data， but blockchains can help serve a role as a “master brain” in a manner shared across multiple AI systems. If we can put all of these shared learning benefits and blockchain and AI together， the possibility may also be there to combine all of these things that can learn from their surroundings and then share that learning with all the AI systems on the network. A major benefit would be that no one owns it and there’s no government control over the bot or the shared brain. It could potentially be unbiased because of the sheer amount of information coming in from different areas and different angles.

　　區(qū)塊鏈不僅可以被用來共享模型和數(shù)據(jù)，還可以以一種跨多個人工智能系統(tǒng)共享的方式，幫助扮演“智多星”的角色。如果我們能夠?qū)⑺泄蚕韺W習的優(yōu)勢和區(qū)塊鏈、人工智能結(jié)合起來，那么就能將機器學習結(jié)合起來，然后使這些學習結(jié)果與網(wǎng)絡上所有的人工智能系統(tǒng)共享。這樣一來的好處就是沒有人能獨握它，即使是政府也無法控制機器人或共享的大腦，它可以是不偏不倚的，因為大量的信息都來自不同的領(lǐng)域和不同的角度。

　　Another application is addressing the challenge of explainable AI.One of the more significant problems with deep learning is that there isn’t a clear idea about what inputs result in what output and how that affected the whole sequence. If something goes wrong in a deep learning neural network， we don’t have a clear idea of how to identify the problem and correct it. This is the problem of neural networks in effect being a “black box” without any real transparency or explainability. However， if we use blockchains， we can record how individual actions result in a final decision in a non-reputable manner， which allows us to go back and see where things went wrong and then fix the problem. The blockchain would be used to record events， such as autonomous vehicle decisions and actions in a way that will not be modified later. This can also increase trust since the blockchain element is unbiased and is just for storage and analysis， anyone can go in and see what has happened.

　　另一個應用是解決可解釋AI的挑戰(zhàn)。深度學習領(lǐng)域的一個更重要的問題是，對于什么輸入導致什么輸出，以及它們?nèi)绾斡绊懻麄€序列尚沒有一個清晰的概念。如果在深度學習神經(jīng)網(wǎng)絡中出現(xiàn)了什么問題，我們就無法知道如何識別和糾正這些問題。這實際上就是神經(jīng)網(wǎng)絡的“黑盒子”問題，毫無真正的透明性或可解釋性可言。然而，如果我們使用區(qū)塊鏈，我們就可以記錄個人行為如何以一種不規(guī)范的方式導致最終決定，并可以回頭看看哪里出了問題，然后解決它。區(qū)塊鏈將被用來記錄事件，且在之后不會被修改，例如自動駕駛汽車的決策和行動；同時這也可以增加信任，因為區(qū)塊鏈元素是客觀的，只是用于存儲和分析，任何人都可以進入其中查看發(fā)生了什么。

　　Finally， AI systems can be used to improve blockchains in general. Machine learning systems can keep an eye on what is happening in the blockchain. It can look for patterns and anomalies in the types of data being stored and actions being performed on a particular server and be used to alert users when something may be happening. The systems can look for normal behavior and flag what seems to be unusual. The AI systems can help keep blockchain more secure， more reliable， and more efficient.

　　最后，人工智能系統(tǒng)通?？梢杂脕砀倪M區(qū)塊鏈。機器學習系統(tǒng)可以持續(xù)關(guān)注區(qū)塊鏈中發(fā)生的事情、查找存儲數(shù)據(jù)類型中的模式和異常，以及觀察在特定服務器上執(zhí)行的操作，并用于在可能發(fā)生緊急事件時向用戶發(fā)出警報。同時，機器學習系統(tǒng)還可以尋找正常的行為，并標記出什么是不尋常的。人工智能系統(tǒng)可以幫助區(qū)塊鏈更安全、更可靠、更高效。

　　While it’s quite possible that the worlds of AI and blockchain are full of hype， there are actual， tangible， realistic ways in which the two emerging technologies can be used in ways that benefit each other and provide real outcomes for those looking to implement the technologies today in their environments.

　　雖然AI與區(qū)塊鏈融合的世界很有可能充滿了不切實際的炒作，但也的確存在著實際、真切且現(xiàn)實的方法，可以使這兩個新興技術(shù)實現(xiàn)彼此受益，并為那些希望在其工作平臺中實施這些技術(shù)的人提供真實的成效。

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　　注：《譯科技 | 人工智能＋區(qū)塊鏈：雙倍的炒作還是雙倍的價值？》來源于Forbes（點擊查看原文）。本文系數(shù)據(jù)觀原創(chuàng)編譯，譯者數(shù)據(jù)觀/王婕，轉(zhuǎn)載請務必注明譯者和來源。

責任編輯：張薇