TED演講者：Andrew Ng / Andrew Ng

演講標題：How AI could empower any business / AI 如何助力所有企業(yè)

內(nèi)容概要：Expensive to build and often needing highly skilled engineers to maintain, artificial intelligence systems generally only pay off for large tech companies with vast amounts of data. But what if your local pizza shop could use AI to predict which flavor would sell best each day of the week? Andrew Ng shares a vision for democratizing access to AI, empowering any business to make decisions that will increase their profit and productivity. Learn how we could build a richer society – ...

人工智能系統(tǒng)造價昂貴，需要技術(shù)高超的工程師來維護，通常只有擁有大量數(shù)據(jù)的大型科技公司可以不做 AI 的賠本買賣。但是如果你當?shù)氐呐_店也能用上 AI 預測每天哪個口味的披薩賣得最好，會怎么樣？吳恩達（Andrew Ng）給我們分享了讓每個人用上 AI 的暢想，讓每個企業(yè)做出提升收入和生產(chǎn)力的決定。來聽聽我們該如何創(chuàng)造一個更富有的社會，你需要做的僅僅是提供一些數(shù)據(jù)。

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【1】When I think about the rise of AI, I'm reminded by the rise of literacy.

當我想到 AI （人工智能）的崛起之時, 我聯(lián)想了讀寫能力的崛起。

【2】A few hundred years ago, many people in society thought that maybe not everyone needed to be able to read and write.

幾百年前, 社會上的很多人覺得 也許不是每個人都得會讀會寫。

【3】Back then, many people were tending fields or herding sheep, so maybe there was less need for written communication.

那時候, 很多人從事農(nóng)業(yè)或者牧羊, 對書面交流的需求沒有那么多。

【4】And all that was needed was for the high priests and priestesses and monks to be able to read the Holy Book, and the rest of us could just go to the temple or church or the holy building and sit and listen to the high priest and priestesses read to us.

只有主教和僧侶 需要讀得懂《圣經(jīng)》和最高經(jīng)典, 其他人只要去寺廟、教堂 或者圣所 坐等主教讀給我們聽就行了。

【5】Fortunately, it was since figured out that we can build a much richer society if lots of people can read and write.

幸運的是,人們后來發(fā)現(xiàn) 如果很多人能讀能寫, 我們的社會會富裕得多。

【6】Today, AI is in the hands of the high priests and priestesses.

如今,AI 被掌握在 “主教”手中。

【7】These are the highly skilled AI engineers, many of whom work in the big tech companies.

這些主教就是 那些技術(shù)高超的 AI 工程師, 其中很多就職于科技巨頭公司。

【8】And most people have access only to the AI that they build for them.

很多人只能接觸到 為他們設(shè)計的 AI。

【9】I think that we can build a much richer society if we can enable everyone to help to write the future.

我認為,如果我們能讓 每個人參與譜寫未來, 我們就能創(chuàng)造一個更富裕的社會。

【10】But why is AI largely concentrated in the big tech companies?

但是為什么大部分 AI 技術(shù) 都集中在科技巨頭手中呢？

【11】Because many of these AI projects have been expensive to build.

因為開發(fā)這些 AI 項目太貴了。

【12】They may require dozens of highly skilled engineers, and they may cost millions or tens of millions of dollars to build an AI system.

這些項目需要一大群 技術(shù)高超的工程師, 要開發(fā)一個 AI 系統(tǒng) 可能要花上幾百萬幾千萬美元。

【13】And the large tech companies, particularly the ones with hundreds of millions or even billions of users, have been better than anyone else at making these investments pay off because, for them, a one-size-fits-all AI system, such as one that improves web search

這些大型科技公司, 尤其是手握幾億 幾十億用戶的公司, 最擅長套回這些投入, 因為對于它們來說, 一個普適的 AI 系統(tǒng), 比如優(yōu)化搜索引擎

【14】or that recommends better products for online shopping, can be applied to [these] very large numbers of users to generate a massive amount of revenue.

或者為網(wǎng)購推薦更佳商品的系統(tǒng), 可以直接適用于龐大的用戶群體, 產(chǎn)生巨額收益。

【15】But this recipe for AI does not work once you go outside the tech and internet sectors to other places where, for the most part, there are hardly any projects that apply to 100 million people or that generate comparable economics.

但是一旦你走出科技互聯(lián)網(wǎng)行業(yè), 去向別的領(lǐng)域, 這個 AI 的秘方可能就不會奏效, 因為在大多數(shù)情況下, 幾乎沒有一個項目 可以覆蓋一億人, 或產(chǎn)生相當?shù)慕?jīng)濟效益。

【16】Let me illustrate an example.

我來舉一個例子。

【17】Many weekends, I drive a few minutes from my house to a local pizza store to buy a slice of Hawaiian pizza from the gentleman that owns this pizza store.

我總會在周末從家里開車去 當?shù)匾患遗_店 向店主買一塊夏威夷披薩。

【18】And his pizza is great, but he always has a lot of cold pizzas sitting around, and every weekend some different flavor of pizza is out of stock.

他的披薩很不錯, 但是總是有一大堆披薩滯銷到冷掉, 每個周末都會 有幾個口味的披薩缺貨。

【19】But when I watch him operate his store, I get excited, because by selling pizza, he is generating data.

但是當我看著他 運營他的小店的時候, 我激動萬分, 因為在他賣披薩的過程中, 也產(chǎn)生了數(shù)據(jù)。

【20】And this is data that he can take advantage of if he had access to AI.

如果他能用上 AI, 就可以從這些數(shù)據(jù)中獲益。

【21】AI systems are good at spotting patterns when given access to the right data, and perhaps an AI system could spot if Mediterranean pizzas sell really well on a Friday night, maybe it could suggest to him to make more of it on a Friday afternoon.

如果輸入了合適的數(shù)據(jù), AI 系統(tǒng)就會很善于識別規(guī)律, 也許能有一個 AI 系統(tǒng)識別出 周五晚上地中海披薩 賣得特別好, 也許這就能告訴他 周五下午多做一點地中海披薩。

【22】Now you might say to me, "Hey, Andrew, this is a small pizza store.

你有可能想這么對我說: “嘿,安德魯（Andrew）,

【23】What's the big deal?"

有什么了不起的？”

【24】And I say, to the gentleman that owns this pizza store, something that could help him improve his revenues by a few thousand dollars a year, that will be a huge deal to him.

而我想說,對于店主來說, 如果有什么可以幫他每年 多賺幾千美元, 那就很了不起了。

【25】I know that there is a lot of hype about AI's need for massive data sets, and having more data does help.

我知道,人們普遍認為 AI 需要大量數(shù)據(jù)集, 有了更多數(shù)據(jù)確實會有幫助。

【26】But contrary to the hype, AI can often work just fine even on modest amounts of data, such as the data generated by a single pizza store.

但是如果沒有大量數(shù)據(jù), AI 通常也可以在 只有少量數(shù)據(jù)的情況下正常運作, 比如一家披薩店產(chǎn)生的數(shù)據(jù)。

【27】So the real problem is not that there isn’t enough data from the pizza store.

真正的問題不是 披薩店沒有足夠的數(shù)據(jù)。

【28】The real problem is that the small pizza store could never serve enough customers to justify the cost of hiring an AI team.

真正的問題是 這小小的披薩店 沒有足夠的客源 平衡雇傭一組 AI 人員的支出。

【29】I know that in the United States there are about half a million independent restaurants.

我知道美國 有大約 50 萬家獨立餐廳。

【30】And collectively, these restaurants do serve tens of millions of customers.

這些餐廳總計服務(wù)了幾億顧客。

【31】But every restaurant is different with a different menu, different customers, different ways of recording sales that no one-size-fits-all AI would work for all of them.

但是每一家餐廳都是不同的, 有著不同的菜單, 不同的顧客, 不同的記賬方式, 沒有一個通用的 AI 系統(tǒng) 可以適用于全部的餐廳。

【32】What would it be like if we could enable small businesses and especially local businesses to use AI?

如果我們可以讓小型企業(yè) 尤其是本土企業(yè)都能用上 AI, 會怎么樣呢？

【33】Let's take a look at what it might look like at a company that makes and sells T-shirts.

我們來看看 AI 應(yīng)用于一家 制造、銷售 T 恤的公司 會是什么樣的情形。

【34】I would love if an accountant working for the T-shirt company can use AI for demand forecasting.

如果這家 T 恤公司的會計 可以用 AI 預測需求, 那就會很不錯。

【35】Say, figure out what funny memes to prints on T-shirts that would drive sales, by looking at what's trending on social media.

比如,通過研究 社交媒體上的潮流, 鎖定一些印在 T 恤上增加銷量的 好玩表情包。

【36】Or for product placement, why can’t a front-of-store manager take pictures of what the store looks like and show it to an AI and have an AI recommend where to place products to improve sales?

就上架策略而言, 門店經(jīng)理可以拍下店鋪情況, 提交給 AI, 讓 AI 推薦商品的擺放位置, 提高銷量。

【37】Supply chain.

供應(yīng)鏈。

【38】Can an AI recommend to a buyer whether or not they should pay 20 dollars per yard for a piece of fabric now, or if they should keep looking because they might be able to find it cheaper elsewhere?

AI 是不是可以推薦 買家是否應(yīng)該 以 20 美元一碼的 價格購入一塊布料, 還是應(yīng)該貨比三家, 因為別家的價格 有可能會更低廉呢？

【39】Or quality control.

質(zhì)量管理。

【40】A quality inspector should be able to use AI to automatically scan pictures of the fabric they use to make T-shirts to check if there are any tears or discolorations in the cloth.

一名質(zhì)檢員 應(yīng)該能夠使用 AI 自動掃描 T 恤的面料照片, 檢查布料是否有裂縫或褪色。

【41】Today, large tech companies routinely use AI to solve problems like these and to great effect.

如今,AI 已經(jīng)成為大型科技公司 處理此類問題的常規(guī)手段, 成果顯著。

【42】But a typical T-shirt company or a typical auto mechanic or retailer or school or local farm will be using AI for exactly zero of these applications today.

但是現(xiàn)在沒有一家普通的 T 恤公司、普通的汽修店、 零售店、學校、本地農(nóng)場 會用 AI 運營。

【43】Every T-shirt maker is sufficiently different from every other T-shirt maker that there is no one-size-fits-all AI that will work for all of them.

每一家 T 恤制造商的情況 都是截然不同的, 沒有一個通用的 AI 系統(tǒng) 可以適用于全部商家。

【44】And in fact, once you go outside the internet and tech sectors in other industries, even large companies such as the pharmaceutical companies, the car makers, the hospitals, also struggle with this.

其實,如果不看互聯(lián)網(wǎng)和科技領(lǐng)域, 去看一些別的領(lǐng)域, 就算是一些大公司, 比如醫(yī)藥公司、 汽車制造商、醫(yī)院, 都會飽受這個問題的困擾。

【45】This is the long-tail problem of AI.

這就是 AI 的長尾效應(yīng)。

【46】If you were to take all current and potential AI projects and sort them in decreasing order of value and plot them, you get a graph that looks like this.

你可以把所有 已有和潛在的 AI 項目 以價值降序排列后作圖, 就會得到這樣一張圖。

【47】Maybe the single most valuable AI system is something that decides what ads to show people on the internet.

也許最有價值的 AI 系統(tǒng) 決定了在網(wǎng)上 給人們展示什么廣告。

【48】Maybe the second most valuable is a web search engine, maybe the third most valuable is an online shopping product recommendation system.

也許第二有價值的系統(tǒng) 是網(wǎng)絡(luò)搜索引擎, 第三有價值的系統(tǒng)是 網(wǎng)購商品推薦系統(tǒng)。

【49】But when you go to the right of this curve, you then get projects like T-shirt product placement or T-shirt demand forecasting or pizzeria demand forecasting.

但是如果你看向曲線的右側(cè), 就會看到像 T 恤商品陳列、 T 恤需求預測和披薩店需求預測 這樣的項目。

【50】And each of these is a unique project that needs to be custom-built.

每一個這樣的項目 都需要定制。

【51】Even T-shirt demand forecasting, if it depends on trending memes on social media, is a very different project than pizzeria demand forecasting, if that depends on the pizzeria sales data.

就算是 T 恤需求預測, 如果它由社交媒體上的 流行表情包決定, 也與披薩店需求預測 是兩種涇渭分明的項目, 披薩店的預測由銷售數(shù)據(jù)決定。

【52】So today there are millions of projects sitting on the tail of this distribution that no one is working on, but whose aggregate value is massive.

如今成千上萬的項目 就處于這個無人問津的分布長尾上, 但是它們的合計價值是不可小覷的。

【53】So how can we enable small businesses and individuals to build AI systems that matter to them?

我們該如何讓小型企業(yè)和個人 有能力搭建對他們 十分重要的 AI 系統(tǒng)呢？

【54】For most of the last few decades, if you wanted to build an AI system, this is what you have to do.

在過去的幾十年中, 如果你想搭建一個 AI 系統(tǒng), 你需要做這些事。

【55】You have to write pages and pages of code.

你需要寫長篇累牘的代碼。

【56】And while I would love for everyone to learn to code, and in fact, online education and also offline education are helping more people than ever learn to code, unfortunately, not everyone has the time to do this.

雖然我覺得人人都該學寫代碼, 線上和線下教育也確實 讓學習編程的人數(shù)達到了高峰, 不幸的是, 不是人人都有時間學習編程。

【57】But there is an emerging new way to build AI systems that will let more people participate.

但是,我們現(xiàn)在 有了一個全新的方式, 創(chuàng)造 AI 系統(tǒng), 讓更多人參與編程。

【58】Just as pen and paper, which are a vastly superior technology to stone tablet and chisel, were instrumental to widespread literacy, there are emerging new AI development platforms

就像紙筆 是比石板和鑿子 先進得多的科技, 在普及讀寫的過程中功不可沒, 現(xiàn)在也有一些 新的 AI 開發(fā)平臺

【59】that shift the focus from asking you to write lots of code to asking you to focus on providing data.

不再讓你寫一大堆代碼, 而是只讓你提供數(shù)據(jù)。

【60】And this turns out to be much easier for a lot of people to do.

這對大規(guī)模人群來說更容易實現(xiàn)。

【61】Today, there are multiple companies working on platforms like these.

現(xiàn)在有很多公司在做這樣的平臺。

【62】Let me illustrate a few of the concepts using one that my team has been building.

我的團隊也在做這類平臺, 我來給大家介紹其中一個。

【63】Take the example of an inspector wanting AI to help detect defects in fabric.

舉個例子,檢測員 需要 AI 的幫助 檢測布料瑕疵。

【64】An inspector can take pictures of the fabric and upload it to a platform like this, and they can go in to show the AI what tears in the fabric look like by drawing rectangles.

檢測員可以拍下布料的照片, 上傳到這樣的平臺上, 然后他們可以用矩形做標記, 告訴 AI 布料裂縫長什么樣。

【65】And they can also go in to show the AI what discoloration on the fabric looks like by drawing rectangles.

他們也可以通過標記矩形, 告訴 AI 布料褪色長什么樣。

【66】So these pictures, together with the green and pink rectangles that the inspector's drawn, are data created by the inspector to explain to AI how to find tears and discoloration.

這些圖片 與檢測員標記的綠色和粉色矩形框 就是檢測員創(chuàng)建的數(shù)據(jù), 告訴 AI 如何檢測裂縫和褪色。

【67】After the AI examines this data, we may find that it has seen enough pictures of tears, but not yet enough pictures of discolorations.

AI 檢查了數(shù)據(jù)之后, 我們會發(fā)現(xiàn), AI 已經(jīng)讀取了足夠的裂縫圖片, 但是沒有足夠的褪色圖片。

【68】This is akin to if a junior inspector had learned to reliably spot tears, but still needs to further hone their judgment about discolorations.

這就類似于一個初級檢測員 已經(jīng)學會了如何準確地識別裂縫, 但是還得再磨練一下對褪色的判斷。

【69】So the inspector can go back and take more pictures of discolorations to show to the AI, to help it deepen this understanding.

這個檢測員可以回去 再拍幾張褪色的照片, 提交給 AI, 加深它對褪色的理解。

【70】By adjusting the data you give to the AI, you can help the AI get smarter.

通過調(diào)整輸入 AI 的數(shù)據(jù), 你可以讓 AI 變得更聰明。

【71】So an inspector using an accessible platform like this can, in a few hours to a few days, and with purchasing a suitable camera set up, be able to build a custom AI system to detect defects, tears and discolorations in all the fabric being used to make T-shirts throughout the factory.

檢測員使用這樣容易操作的平臺, 在幾小時至幾天內(nèi), 再采購一套合適的攝影設(shè)備, 就能在搭建起一個 定制化 AI 系統(tǒng), 檢測工廠中所有 T 恤面料上的 瑕疵、裂縫和褪色情況。

【72】And once again, you may say, "Hey, Andrew, this is one factory.

你可能又想說: “嘿,安德魯,這就是一家工廠,

【73】Why is this a big deal?"

有什么了不起的？”

【74】And I say to you, this is a big deal to that inspector whose life this makes easier and equally, this type of technology can empower a baker to use AI to check for the quality of the cakes they're making,

我想告訴你, 對那個減負的檢測員來說, 這很了不起, 同樣,這項技術(shù)可以讓 一名烘焙師使用 AI 檢查手中蛋糕的質(zhì)量,

【75】or an organic farmer to check the quality of the vegetables, or a furniture maker to check the quality of the wood they're using.

讓一名有機農(nóng)場主 檢查蔬菜的質(zhì)量, 讓一個家具制造商 檢查木材原料的質(zhì)量。

【76】Platforms like these will probably still need a few more years before they're easy enough to use for every pizzeria owner.

這類平臺也許還需要一些時間 將操作難易度調(diào)節(jié)至 適用于每一個披薩店店主。

【77】But many of these platforms are coming along, and some of them are getting to be quite useful to someone that is tech savvy today, with just a bit of training.

但是很多平臺都在進步, 有些平臺只需要少量培訓, 就已經(jīng)對如今懂技術(shù)的人來說 非常有幫助了。

【78】But what this means is that, rather than relying on the high priests and priestesses to write AI systems for everyone else, we can start to empower every accountant, every store manager, every buyer and every quality inspector to build their own AI systems.

這也就意味著, 我們不需要再依賴于主教 為所有人編寫 AI 系統(tǒng), 我們的每位會計、 每位門店經(jīng)理、 每位買家、每位質(zhì)檢員都有能力 搭建自己的 AI 系統(tǒng)。

【79】I hope that the pizzeria owner and many other small business owners like him will also take advantage of this technology because AI is creating tremendous wealth and will continue to create tremendous wealth.

我希望披薩店店主 和其他像他這樣的小型企業(yè)主 都可以用上這項技術(shù), 因為 AI 創(chuàng)造著巨大財富, 也將在未來持續(xù)創(chuàng)造巨大財富。

【80】And it's only by democratizing access to AI that we can ensure that this wealth is spread far and wide across society.

只有讓人人都有機會用上 AI, 我們才能將這樣的財富 播撒到社會的每個角落。

【81】Hundreds of years ago.

幾百年前。

【82】I think hardly anyone understood the impact that widespread literacy will have.

我覺得幾乎沒有人懂得 普及讀寫的重要性。

【83】Today, I think hardly anyone understands the impact that democratizing access to AI will have.

我認為現(xiàn)在幾乎沒有人懂得 讓每個人有機會 用上 AI 的重要性。

【84】Building AI systems has been out of reach for most people, but that does not have to be the case.

大多數(shù)人沒有機會 搭建 AI 系統(tǒng), 但是未來不一定會是如此。

【85】In the coming era for AI, we’ll empower everyone to build AI systems for themselves, and I think that will be incredibly exciting future.

在接下來的 AI 時代中, 我們會讓每一個人有能力 為自己搭建 AI 系統(tǒng), 我覺得這就是我們 振奮人心的未來。

【86】Thank you very much.

謝謝。

【87】(Applause)