Name: 亞馬遜如何在生成式人工智能的幫助下更快地送達包裹 (How Amazon Is Delivering Packages Faster With The Help Of Generative AI)
Uploaded: 2024-09-18T03:16:22.000Z
Duration: 15 min 47 s

So fulfillment centers ship into this building, this building sorts those packages, then they flow out to our delivery stations.

是以，履約中心向這棟大樓發貨，這棟大樓對這些包裹進行分揀，然後它們流向我們的配送站。

基礎被動語態

Inside this one million square foot warehouse in Northern California, Amazon packages are handled by hundreds of people and hundreds of robots, all increasingly driven by tech's biggest craze.

在北加州這個佔地一百萬平方英尺的倉庫裡，亞馬遜的包裹由數百人和數百個機器人處理，而這一切都越來越受到科技最大熱潮的推動。

分詞構句

Generative AI underpins everything we're doing here with perceiving, grasping and moving products with the Robin arms to managing fleet congestion with our Pegasus robotic drives.

生成式人工智能為我們在這裡所做的一切提供了支持，包括使用羅賓臂感知、抓取和移動產品，以及使用飛馬機器人驅動器管理車隊擁堵情況。

For years, Amazon has sped up package delivery, two day, one day, and now more and more, same day, made possible by more workers, but also by rapidly improving algorithms and AI enabled robots.

多年來，亞馬遜一直在加快包裹送達速度，兩天、一天，現在越來越多的是當天送達，這得益於更多的工人，也得益於快速改進的算法和人工智能機器人。

What you see here is, I like to call it our dance floor.

你們現在看到的，我稱之為我們的舞池。

And thanks to being an online retailer from the start, Amazon has a big advantage when it comes to the massive data needed for generative AI.

由於從一開始就是在線零售商，亞馬遜在獲取生成式人工智能所需的海量數據方面擁有巨大優勢。

Absolutely, Amazon has been better at it than probably every other retailer out there.

當然，亞馬遜在這方面可能比其他所有零售商都做得好。

Think better predictions of exactly what you're going to order from where and when, hundreds of thousands of robots and more efficient delivery routes.

您可以更好地預測您將在何時何地訂購什麼產品，還可以使用成千上萬的機器人和更高效的送貨路線。

But not all the change that could come from generative AI is positive.

但是，生成式人工智能可能帶來的變化並非都是積極的。

In the event that they were able to leverage generative AI and fully automate the fulfillment center, I think that would be problematic.

如果他們能夠利用生成式人工智能，實現履約中心的完全自動化，我認為這將是個問題。

The other downside that we don't talk about enough is the negative impact on the environment, the cost of running data centers, the use of electricity, the use of water for cooling.

另一個我們談論得不夠多的不利因素是對環境的負面影響、數據中心的運行成本、電力使用和冷卻用水。

Still, Amazon says AI helps cut costs and its carbon footprint, thanks to more efficient planning.

不過，亞馬遜表示，人工智能有助於降低成本和碳足跡，這要歸功於更高效的規劃。

It seems subtle, but at this scale, getting like just one more product in the right spot means that it's shipping less distance when you order it, better speed, lower distance travel, better sustainability.

這看起來很微妙，但在這種規模下，只要在正確的位置多放一個產品，就意味著你訂購時的運輸距離更短，速度更快，運輸距離更短，可持續性更好。

CNBC visited Amazon's largest California sort center and a same-day warehouse nearby to see firsthand how it's putting AI to work at every step of operations, and sat down with Amazon's head of transportation technology to find out just how far the e-commerce giant plans to take it.

CNBC 參觀了亞馬遜在加利福尼亞州最大的分揀中心和附近的一個當日達倉庫，親眼目睹了亞馬遜如何將人工智能應用到營運的每一個環節，並與亞馬遜的運輸技術主管進行了座談，以瞭解這家電子商務巨頭計劃將人工智能發展到何種程度。

When Amazon Prime launched in 2005, two-day shipping was virtually unheard of.

亞馬遜 Prime 於 2005 年推出時，兩日送達服務幾乎聞所未聞。

And although it's now standard and free for millions of items if you're a Prime member, it's a grueling logistical lift.

雖然現在只要您是 Prime 會員，就可以免費購買數百萬件商品，但這是一項艱鉅的物流工作。

Along here you see Robin Arms, which are robotic arms.

沿著這裡，你可以看到羅賓臂，這是一種機械臂。

They're loading packages with employees onto Pegasus drive units.

他們正在把裝有員工的包裹裝上飛馬驅動裝置。

Those Pegasus drive units are then sorting packages by neighborhood.

然後，這些 Pegasus 驅動裝置將按街區對包裹進行分類。

Steve Armato started at Amazon as a software engineer before Prime in 2001.

Steve Armato 於 2001 年進入亞馬遜，在 Prime 之前擔任軟件工程師。

A lot of things you see today, they always weren't there in 2001.

你今天看到的很多東西，在 2001 年都不存在。

We had five fulfillment centers back then, now we have hundreds.

當時我們有五個履約中心，現在我們有數百個。

The delivery vans that you see in the neighborhood, none of that was there.

你在附近看到的送貨車，都不在那裡。

Traditional retailers like Walmart and Target were selling online, but they hadn't started making promises of speed.

沃爾瑪和塔吉特等傳統零售商已經開始在網上銷售，但他們還沒有開始承諾速度。

Back then, mail order, when Amazon started, you'd be lucky if you could get something in two to three weeks.

那時候，郵購，亞馬遜剛起步的時候，你能在兩到三週內拿到東西就已經很幸運了。

And Amazon would still promise a week and they would get it to you in a few days.

亞馬遜仍然會承諾一個星期，他們會在幾天內給你。

那麼，亞馬遜是如何做到的呢？

Long before generative AI became all the rage with the release of ChatGBT in 2022, general AI was a huge differentiator for Amazon.

早在 2022 年 ChatGBT 發佈，生成式人工智能風靡全球之前，通用人工智能就已成為亞馬遜的一大差異化優勢。

As an early online-only retailer, Amazon had a unique ability to collect mass aggregate data on shopping behavior and use it to create algorithms to maximize sales and speedy logistics.

作為早期的在線零售商，亞馬遜擁有獨特的能力，可以收集大量的購物行為彙總數據，並利用這些數據創建算法，最大限度地提高銷售額和物流速度。

我們研究人工智能已經超過 25 年了。

For employees, a lot of it is around ergonomics and safety.

對於員工來說，這在很大程度上與人體工程學和安全有關。

For customers, it's around vast selection, great speeds.

對於客戶來說，這意味著更多的選擇和更快的速度。

Exploiting technology to drive e-commerce sales, that's essentially what Amazon's done since 1997, since the beginning.

利用技術推動電子商務銷售，這基本上就是亞馬遜自 1997 年以來一直在做的事情。

They are, I would say, hands down the most data-heavy and data-savvy company.

我可以說，他們是數據量最大、最精通數據的公司。

It's not that Walmart and Target and Costco and others don't have their own reams of data, but they're looking at things a little bit differently, and they have much older systems.

沃爾瑪、塔吉特、好市多和其他公司並不是沒有自己的大量數據，但他們看問題的角度有點不同，而且他們的系統要老得多。

Amazon is decades younger than its major retail competitors, but its stock value and footprint have grown incredibly fast.

與主要零售競爭對手相比，亞馬遜年輕了幾十年，但其股票價值和業務範圍的增長速度卻快得令人難以置信。

Hundreds of warehouses, more than 1.5 million U.S. employees, and more speed.

數以百計的倉庫、150 多萬美國員工以及更快的速度。

In 2014, Amazon launched PrimeNow, with some deliveries arriving in an hour or less.

2014 年，亞馬遜推出了 PrimeNow，一些送貨服務可在一小時或更短時間內到達。

Then in 2018, Amazon vastly increased its driver network with the launch of its Delivery Service Partner program, where it contracts driving out to some 4,400 small delivery businesses that employ 390,000 drivers.

隨後在 2018 年，亞馬遜推出了 "配送服務合作伙伴 "計劃，將配送業務外包給約 4400 家小型配送企業，這些企業僱傭了 39 萬名司機，從而大幅增加了司機網絡。

到 2019 年，一天發貨已成為常態。

Then in 2020, Amazon began using transformer architecture, the backbones of what we know of today as generative AI, to develop models for demand forecasting and supply chain optimization.

2020 年，亞馬遜開始使用變壓器架構，也就是我們今天所說的生成式人工智能的骨幹，來開發需求預測和供應鏈優化模型。

By 2022, it was rolling AI transformer models into its robotics.

到 2022 年，該公司已將人工智能變壓器模型應用到機器人技術中。

All that made shipping times even faster.

所有這一切使得運輸時間變得更快。

Today, drivers are delivering 20 million packages per day across 20 countries, and in the first quarter of 2024, more than 2 billion items arrived the same or next day. 60% of our deliveries for Prime customers in March were same day or next day, so there are a lot of those fast orders for our top 60 metropolitan areas.

如今，司機每天要在 20 個國家和地區送達 2000 萬個包裹，在 2024 年第一季度，超過 20 億件商品在當天或次日送達。三月份，我們為 Prime 客戶提供的配送服務中有 60% 是當天或次日送達的，是以，在我們排名前 60 位的大都市地區，有很多這樣的快速訂單。

Could you have gotten to that 60% number without generative AI?

如果沒有生成式人工智能，你能達到 60% 這個數字嗎？

Well, I think we've been working on this for decades to get to this speed, and it's a combination of engineering, people, processes, and technology.

我認為，為了達到這樣的速度，我們已經努力了幾十年，這是工程、人員、流程和技術的結合。

Generative AI is a big unlock for us, particularly for new products, where we have sparse or no history for that sales history for that product.

對我們來說，生成式人工智能是一個很大的突破口，尤其是對於新產品，因為我們對該產品的銷售歷史知之甚少或一無所知。

It's going to come faster because of generative AI.

因為有了生成式人工智能，這一切會來得更快。

But all this speed comes at a huge cost, in actual capex, but also human labor, a burden that can be reduced, Amazon says, with the use of robots.

但亞馬遜表示，所有這些速度都需要巨大的成本，包括實際資本支出和人力成本，而使用機器人可以減輕這一負擔。

Before robotics, pickers would need to walk distances between aisles to pick products, kind of like a library, and now it's being brought to you more like self-service.

在採用機器人技術之前，揀貨員需要在貨架之間走一段距離才能揀到貨品，有點像圖書館，而現在則更像是自助服務。

And so that's great for ergonomics, it's great for less walking.

是以，這對人體工程學非常有利，可以減少步行。

Amazon has faced scrutiny in recent years over its workplace injury record, with federal citations for safety violations and a year-long Senate probe that found Prime Day was a major cause of worker injuries.

近年來，亞馬遜的工傷記錄一直受到嚴格審查，它曾因違反安全規定而受到聯邦通報批評，參議院長達一年的調查也發現 Prime Day 是造成工人工傷的主要原因。

Amazon has appealed the citations and said the report ignores progress it's made, and it says AI can help.

亞馬遜已對引文提出上訴，並表示該報告忽視了它所取得的進展，而且它說人工智能可以提供幫助。

One algorithmic improvement is to take our faster-selling products and place those on the shelves at waist height.

算法上的一個改進是，把我們銷售較快的產品放在貨架上，並把它們放在腰部的高度。

That's your ergonomic power zone, so less reaching, less bending.

這是你的人體工程學動力區，所以少伸手，少彎腰。

Amazon's big shift to automation started in 2012 with the purchase of Kiva systems for $775 million.

2012 年，亞馬遜以 7.75 億美元收購了 Kiva 系統，開始向自動化領域大步邁進。

Now Amazon has deployed at least 750,000 robots, more than double the number it had in 2021.

現在，亞馬遜已經部署了至少 75 萬個機器人，是 2021 年的兩倍多。

So generative AI helps with prioritization.

是以，生成式人工智能有助於確定優先級。

So some of the two-day deliveries might stand aside and let the robot with a next-day delivery go on its mission first and take a straight line to its destination.

是以，一些兩日送貨的機器人可能會靠邊站，讓次日送貨的機器人先執行任務，走直線到達目的地。

Amazon's next generation of drive units, called Proteus, are fully autonomous.

亞馬遜的下一代驅動裝置名為 Proteus，是完全自主的。

They're actually outside of this fenced area, moving things around.

他們實際上就在圍欄外，正在搬東西。

They're using generative AI and computer vision to avoid obstacles and find the right place to stop, the right place to park.

它們使用生成式人工智能和計算機視覺來避開障礙物，找到正確的停車位置和停車地點。

And then there's Robin Arms, which Amazon says have handled some 2 billion packages so far.

還有 Robin Arms，亞馬遜稱其迄今已處理了約 20 億個包裹。

Would these 20 Robin Arms be able to do what they're doing without generative AI?

如果沒有生成式人工智能，這 20 臺 "羅賓臂 "能完成現在的工作嗎？

I think that we would see that they would require a lot more training.

我認為，我們會看到他們需要更多的培訓。

And so generative AI has been really a step-function improvement in being able to infer from our vast product catalog about how to handle a given product, even if I haven't seen that product before.

是以，生成式人工智能在從我們龐大的產品目錄中推斷如何處理給定產品方面確實有了質的飛躍，即使我以前從未見過該產品。

And although it's only in a couple warehouses for now, there's a humanoid robot called Digit that can grasp and handle items in a similar way to how people can.

雖然目前只在幾個倉庫中使用，但有一種名為 Digit 的仿人機器人可以像人一樣抓取和處理物品。

And Amazon has a new deal with AI startup Covariant, hiring its founders and licensing its models that help robots handle a wider range of physical objects.

亞馬遜與人工智能初創公司 Covariant 簽訂了一項新協議，聘請其創始人並授權使用其模型，幫助機器人處理更廣泛的實物。

Of course, this brings up the big question.

當然，這也帶來了一個大問題。

Could Amazon one day replace all warehouse workers if AI helps robots get too capable?

如果人工智能幫助機器人變得過於能幹，亞馬遜是否有一天會取代所有倉庫工人？

There's kind of a balancing act for Amazon.

對亞馬遜來說，這是一種平衡行為。

How can they implement automation to improve efficiency and manage labor expenses, but how can they do it in a way that complements their use of humans and doesn't replace them?

他們如何實現自動化以提高效率和管理勞動力支出，但又如何做到與人力使用相輔相成，而不是取而代之？

Amazon says the robots work with people and they're creating new roles.

亞馬遜表示，機器人與人一起工作，它們正在創造新的角色。

We're investing over $1.2 billion to upskill more than 300,000 employees by the end of next year.

到明年年底，我們將投資超過 12 億美元，對 30 多萬名員工進行技能培訓。

One study found that each robot adopted in manufacturing replaced about three workers.

一項研究發現，製造業每採用一個機器人，就能取代約三名工人。

Other research shows that companies that deploy more robots add more jobs overall.

其他研究表明，部署更多機器人的公司總體上會增加更多工作崗位。

So someone needs to maintain this if it breaks down, or if something does get dropped on the dance floor, we have a process and special training to go clean that up.

是以，如果出現故障或有東西掉在舞池裡，需要有人來維護，我們有一套程序和專門的培訓來清理。

And so each of those creates new categories of jobs, some of which have higher earnings potential as well.

是以，每一項工作都會創造出新的工作類別，其中一些工作的收入潛力也更高。

The truth is, at the end of the day, Amazon's responsibility is not to employ, you know, kind of a million Americans, even though it does.

事實上，歸根結底，亞馬遜的責任並不在於僱傭一百萬美國人，儘管它確實僱傭了。

Their responsibility is to their shareholders.

Another big way to please shareholders is to cut down on the huge amount of time and money it takes to get inventory from sellers to customers.

取悅股東的另一個重要方法是減少從賣家到客戶的庫存所需的大量時間和金錢。

To do this, Amazon has always used algorithms to predict how much of what inventory is needed, when and where.

為此，亞馬遜一直使用算法來預測何時何地需要多少庫存。

Every product has like a regional nuance.

每種產品都有不同的地方特色。

We recently regionalized our entire national network.

我們最近對整個全國網絡進行了區域化。

And by doing a regional network, that means that products are more likely to ship from fulfillment centers close to you.

通過區域網絡，這意味著產品更有可能從您附近的履行中心發貨。

What's new with generative AI is the ability to predict where to place brand new items.

生成式人工智能的新功能是預測全新物品的擺放位置。

So we're able to use generative AI to create a link between products we have seen before, where we do have a sales history, and a new product we haven't seen before yet and get it in the right place the first time.

是以，我們能夠使用生成式人工智能，在我們以前見過的、有銷售記錄的產品和我們以前沒見過的新產品之間建立聯繫，並在第一時間將其放在正確的位置。

So when we place a product in the right place ahead of time, before you click buy, it's which is a win for speed and sustainability.

是以，當我們在您點擊購買之前，提前將產品放在正確的位置，這對速度和可持續性來說都是雙贏。

Amazon also says AI is helping sustainability with a specific model that makes better choices about which packaging to use.

亞馬遜還表示，人工智能正在通過一個特定模型幫助實現可持續發展，該模型可以更好地選擇使用哪種包裝。

And by reducing the number of damaged items that get sent to and returned by customers.

此外，還能減少客戶寄回和退回的損壞物品數量。

Amazon says its AI is three times better than humans at identifying damaged products.

亞馬遜稱，其人工智能在識別受損產品方面的能力是人類的三倍。

So we're able to use computer vision together with generative AI and that vast amount of product and package data to then detect damages and being able to sideline a package if we think it might be damaged before we ship it to customers.

是以，我們能夠利用計算機視覺、生成式人工智能以及海量的產品和包裝數據來檢測損壞情況，並在向客戶發貨之前，如果我們認為包裝可能損壞，就能夠將其擱置一邊。

But training and running gen AI is itself a carbon intensive process, a fact that could make it hard for Amazon to achieve its 2019 climate pledge to reach net zero carbon by 2040.

但訓練和運行基因人工智能本身就是一個碳密集型過程，這可能使亞馬遜難以實現其 2019 年的氣候承諾，即到 2040 年實現淨零碳排放。

By 2027, AI servers are projected to use up as much power every year as a small And Amazon Web Services has data centers filled with servers running AI workloads.

預計到 2027 年，人工智能服務器每年消耗的電量將相當於一個小型企業每年消耗的電量，而亞馬遜網絡服務公司的數據中心已佈滿了運行人工智能工作負載的服務器。

Although this also gives it an edge over other e-commerce players because it can train its AI in-house.

儘管這也讓它比其他電子商務公司更具優勢，因為它可以在公司內部訓練人工智能。

Amazon's also invested $4 billion in AI startup Anthropic, which makes chatbot Claude a competitor to OpenAI's chat GPT.

亞馬遜還向人工智能初創公司 Anthropic 投資了 40 億美元，該公司生產的哈拉機器人 Claude 是 OpenAI 哈拉 GPT 的競爭對手。