How Amazon Is Delivering Packages Faster With The Help Of Generative AI

Summary

Amazon's Northern California warehouse, spanning 1 million square feet, exemplifies the integration of generative AI in logistics, with hundreds of robots and employees working in tandem. This tech-driven approach enhances package sorting and delivery, reducing shipping times and environmental impact. Amazon's extensive data collection enables precise demand forecasting and efficient inventory management, promising faster delivery times. However, concerns about job displacement and the carbon footprint of AI operations linger.

Takeaways

• 🏭 Amazon's fulfillment centers use a combination of human labor and AI-driven robots to sort and ship packages efficiently.
• 🤖 Generative AI plays a crucial role in Amazon's operations, from product handling with robotic arms to managing fleet congestion with autonomous drives.
• 📈 The use of AI and robotics has allowed Amazon to accelerate package delivery times, with same-day delivery becoming more common.
• 📊 Amazon's early online retail experience gives it a significant advantage in leveraging massive data sets for AI, improving predictions and logistics.
• 🔍 Generative AI helps Amazon in better predicting customer orders, leading to more efficient inventory management and delivery routes.
• 🚚 Amazon has significantly increased its delivery network and uses AI to optimize delivery routes, reducing time and distance traveled.
• 🔋 The environmental impact of AI is a concern, with data centers consuming substantial electricity and water for cooling, potentially offsetting sustainability gains.
• 🤝 Amazon emphasizes that AI and robots are designed to work alongside human workers, creating new roles and opportunities.
• 💡 AI is also used to enhance workplace safety and ergonomics, such as by placing frequently sold items at waist height to reduce employee strain.
• 🌐 Amazon's investment in AI and robotics is extensive, with the aim of improving efficiency, sustainability, and ultimately, profitability.

Q & A

How is Amazon utilizing generative AI in its fulfillment centers?

Amazon is using generative AI to manage robotic systems, like the Robin arms and Pegasus drive units, which are responsible for sorting and moving products. AI also optimizes fleet routes, forecasts demand, and enhances safety by making ergonomic improvements in product handling.

What are some benefits of using generative AI in Amazon’s operations?

Generative AI helps Amazon improve efficiency, reduce package delivery times, and enhance sustainability by optimizing inventory placement and reducing the distance packages need to travel. It also helps identify damaged products, minimizing waste and returns.

How does Amazon's use of AI contribute to faster delivery speeds?

AI enables better demand forecasting and supply chain optimization, helping Amazon predict what items are needed, where, and when. Robots powered by AI can prioritize same-day or next-day deliveries, reducing delays and improving speed.

What role do robots play in Amazon's fulfillment centers?

Robots like Robin arms and Pegasus drive units handle tasks like sorting packages by neighborhood and moving products to the right spots in warehouses. These robots reduce the physical strain on workers and improve efficiency in order processing.

What challenges does Amazon face in balancing automation with human labor?

Amazon faces the challenge of integrating automation in a way that complements human labor rather than fully replacing it. While robots handle many tasks, Amazon emphasizes creating new job roles in areas like maintenance and training workers for more technical positions.

How is Amazon addressing workplace safety with AI?

Amazon uses AI to improve worker safety by reducing the need for physical strain. For example, fast-selling products are placed at waist height to avoid excessive reaching or bending. AI also helps monitor safety risks, like preventing collisions with autonomous robots.

What environmental concerns are associated with Amazon’s AI infrastructure?

The large-scale use of AI requires significant energy consumption for running data centers, which raises concerns about the environmental impact. Amazon has pledged to reduce its carbon footprint, but running AI workloads can hinder progress toward its net-zero carbon goal.

How does Amazon’s generative AI help in reducing package waste?

AI helps Amazon identify damaged products before they are shipped, reducing returns and preventing waste. It also optimizes packaging choices, further cutting down on materials used and damaged goods.

What innovations has Amazon made in last-mile delivery through AI?

Amazon is using over 20 machine learning models to optimize last-mile delivery routes, helping drivers avoid traffic and take more efficient paths. This reduces delivery times and lessens the pressure on drivers to meet tight schedules.

What are Amazon’s privacy measures when using AI for personalized shopping experiences?

Amazon aggregates shopping behavior by region rather than tracking individual users directly. AI-generated product recommendations and reviews are based on broader data sets, though there are concerns about user privacy, and opt-out options may be considered in the future.

Outlines

00:00

🤖 Amazon's Integration of Generative AI in Warehouse Operations

Amazon's fulfillment centers utilize generative AI to enhance package sorting and delivery efficiency. The Northern California warehouse, spanning 1 million square feet, employs both human labor and hundreds of robots to manage the logistics. Generative AI plays a pivotal role in tasks such as product perception, grasping, and movement using Robin arms, as well as managing fleet congestion with Pegasus robotic drives. Amazon has been able to accelerate delivery times from two-day to same-day shipping, largely due to improved algorithms and AI-enabled robotics. The company's early start as an online retailer has provided it with extensive data crucial for AI development, leading to better predictions of customer orders and more efficient delivery routes. However, concerns about the potential negative impacts, such as job displacement and environmental costs due to increased energy and water usage for data centers, are also discussed. Despite these concerns, Amazon asserts that AI contributes to cost and carbon footprint reduction through more efficient planning.

05:03

🚚 Rapid Delivery Expansion and Its Impact on Labor and Sustainability

Amazon has significantly increased its delivery speed, with 60% of Prime customer deliveries in March being same-day or next-day. This rapid expansion is attributed to a combination of engineering, workforce, processes, and technology, with generative AI being a significant factor, especially for new products with little or no sales history. The physical labor required for such speed is substantial, but Amazon claims that the use of robots can alleviate this burden, improving ergonomics and reducing the need for extensive walking by workers. The company has faced criticism over workplace safety and injuries, but argues that AI can help improve these conditions. Amazon's investment in robotics, starting with the acquisition of Kiva Systems in 2012, has led to the deployment of over 750,000 robots, enhancing prioritization and efficiency in delivery. The next generation of drive units, Proteus, and the Robin arms, which have handled around 2 billion packages, demonstrate the significant advancements in automation. Amazon also explores the use of humanoid robots like Digit and partnerships with AI startups to expand the capabilities of robots. The challenge for Amazon is to balance automation with human labor, creating new roles and upskilling employees, while maintaining its responsibility to shareholders.

10:06

🌍 The Role of AI in Enhancing Amazon's Sustainability and Efficiency

Amazon employs AI to improve sustainability by optimizing inventory management, reducing packaging, and minimizing damaged items. The company's AI can predict regional inventory needs and packaging choices, and it is three times more effective than humans at identifying damaged products. Amazon's vast data collection allows it to use computer vision and generative AI to detect and sideline potentially damaged packages before shipping. Despite the environmental concerns related to the carbon footprint of training and running AI, Amazon continues to invest in AI technologies, including its own AI-focused microchips and tools like Amazon Q and Bedrock. The company's commitment to AI is also evident in its investment in AI startup Anthropic and the development of AI-powered tools for developers. Amazon aims to use AI to reduce the time and distance products travel, which is beneficial for both speed and sustainability. The company also uses AI to enhance the efficiency of the last-mile delivery process, with machine learning models optimizing delivery routes and new electric vans equipped with AI-enabled cameras and routing systems.

15:08

🛒 Generative AI's Influence on Amazon's Personalized Shopping Experience

Amazon is leveraging generative AI to create hyper-personalized shopping experiences by analyzing aggregate sales history and geographic data to predict customer behavior. The company uses AI to generate product recommendations, write targeted product listings, and even create AI-generated review highlights to assist shoppers in making informed decisions. In 2023, Amazon launched Rufus, a conversational shopping assistant powered by generative AI, to streamline product recommendations further. While there are privacy concerns regarding the use of customer data for personalized recommendations, Amazon emphasizes that it focuses on aggregate behavior rather than individual customer data. The company is committed to integrating generative AI into all aspects of its operations to enhance speed, efficiency, and profitability, with the goal of improving the overall customer experience.

Keywords

💡Fulfillment Centers

Fulfillment centers are the warehouses operated by Amazon where products are stored, picked, packed, and shipped to customers. In the context of the video, fulfillment centers are integral to Amazon's logistics network, playing a crucial role in the speed and efficiency of package delivery. The script mentions that these centers ship packages to a sorting building, highlighting their role in the initial stage of the delivery process.

💡Generative AI

Generative AI refers to artificial intelligence systems that can create new content, such as text, images, or even code, based on existing data. In the video, generative AI is portrayed as a key technology that underpins Amazon's operations, from perceiving and grasping products with robotic arms to managing fleet congestion. It is central to Amazon's strategy for improving efficiency and speed in package delivery, as it helps in predicting customer orders and optimizing logistics.

💡Robotic Drives

Robotic drives, like Amazon's Pegasus, are autonomous vehicles used within the warehouse to transport goods. They are mentioned in the script as a part of Amazon's advanced technology that contributes to the sorting and movement of packages within the warehouse. These drives are an example of how Amazon leverages AI and robotics to enhance the efficiency of its operations.

💡Same-day Delivery

Same-day delivery is a service where products are delivered to the customer on the same day the order is placed. The script highlights Amazon's progress in offering same-day delivery, which has been made possible by improvements in algorithms and AI-enabled robots. This service is a testament to Amazon's commitment to speed and customer satisfaction.

💡Data Centers

Data centers are facilities that house computer servers and associated components, such as network equipment and storage systems. In the video, the script discusses the environmental impact of running data centers, particularly in terms of electricity and water usage for cooling. These centers are essential for training and running AI models, which are critical for Amazon's operations.

💡Ergonomics

Ergonomics is the study of designing equipment and devices that fit the human body and its movements. In the context of the video, ergonomics is mentioned in relation to how Amazon uses AI to improve working conditions for employees, such as placing frequently sold products at waist height to reduce reaching and bending.

💡AI Transformer Models

AI transformer models are a type of deep learning architecture that is particularly good at handling sequential data, such as natural language. The script notes that Amazon has integrated these models into its robotics, which has contributed to faster shipping times by improving the robots' ability to handle and sort packages.

💡Automation

Automation refers to the use of technology to create systems that can operate automatically. The video discusses Amazon's shift towards automation, particularly in its warehouses, where robots have replaced some human labor. This has implications for efficiency and labor, as the company aims to balance the use of robots with human workers.

💡Sustainability

Sustainability in the video refers to Amazon's efforts to reduce its environmental impact. The script mentions how AI helps in cutting costs and carbon footprint through more efficient planning and operations. For example, by placing products closer to customers in advance, Amazon can reduce the distance packages need to travel, which is beneficial for both speed and sustainability.

💡Machine Learning Models

Machine learning models are algorithms that learn and improve from experience without being explicitly programmed. In the video, Amazon uses more than 20 machine learning models to determine the most efficient routes for delivery drivers. This application of AI helps in optimizing the 'last mile' delivery process, reducing time and potentially improving driver safety.

💡Privacy

Privacy in the context of the video refers to customer concerns about the collection and use of their data by Amazon. The script touches on how Amazon uses generative AI to create personalized product recommendations based on shopping behavior. It raises the question of whether consumers are comfortable with this level of data use and whether Amazon should provide options for customers to opt out of such personalized experiences.

Highlights

Amazon's fulfillment centers use a combination of human labor and AI-driven robots to sort and ship packages.

Generative AI is integral to Amazon's operations, enhancing package handling and managing fleet congestion.

Amazon has been able to reduce delivery times from two-day to same-day, thanks to improved algorithms and AI-enabled robots.

The 1,000,000 square foot warehouse in Northern California exemplifies Amazon's use of technology in logistics.

Amazon's online start gives it a significant advantage in the data needed for generative AI.

Generative AI helps Amazon predict customer orders more accurately, leading to more efficient inventory management.

The use of AI in Amazon's logistics has increased the number of same-day deliveries.

Amazon's AI investments have led to the deployment of hundreds of thousands of robots in its facilities.

The potential downside of generative AI includes job displacement and environmental impacts.

Amazon claims that AI helps reduce costs and carbon footprint through more efficient planning.

AI allows Amazon to optimize product placement, reducing shipping distances and improving sustainability.

Amazon's head of transportation technology discusses the company's plans for AI integration in operations.

Amazon Prime's launch in 2005 introduced two-day shipping, which was revolutionary at the time.

Amazon's data collection and AI capabilities have been key differentiators since its early days as an online retailer.

Amazon's AI and robotics advancements have led to a significant increase in delivery speeds and efficiency.

Amazon's use of AI in robotics has improved the ergonomics and safety for warehouse workers.

The company has faced challenges with workplace injuries, but AI is being used to improve workplace safety.

Amazon's AI-driven robots, like Proteus and Robin arms, are becoming more autonomous and efficient.

Amazon is investing in AI to create new job roles and upskill its workforce.

AI is used to optimize inventory placement, reducing the distance products travel before being shipped.

Amazon's AI is also used to improve packaging choices and reduce damaged items.

The company is working towards net-zero carbon by 2040, with AI playing a role in sustainability efforts.

Amazon's investment in AI startups and its own AI tools aim to improve operational efficiency and profits.

AI is being used to optimize delivery routes and reduce the time and distance for the last mile of delivery.

Amazon's use of AI-generated review highlights and conversational shopping assistants aims to enhance the customer experience.

Amazon is committed to integrating generative AI into all aspects of its operations for increased speed and efficiency.

Transcripts

So fulfillment centers ship into this building.

This building sorts those packages.

Then they flow out to our delivery stations.

Inside this 1,000,000 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.

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.

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.

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

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.

Absolutely. Amazon has been better at it than probably

every other retailer out there.

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.

But not all the change that could come from generative

AI is positive.

In the event that they were able to leverage generative

AI and fully automate the fulfillment center, I think

that would be problematic.

The other downside that we don't talk about enough is

the negative impact on the environment: the costs of

running data centers, the use of electricity, the use

of water for cooling.

Still, Amazon says AI helps cut costs and its carbon

footprint thanks to more efficient planning.

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 traveled, better

sustainability.

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.

When Amazon Prime launched in 2005, two-day shipping

was virtually unheard of.

And although it's now standard and free for millions

of items if you're a Prime member, it's a grueling

logistical lift.

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

They're loading packages, with employees, onto Pegasus

drive units. Those Pegasus drive units are then

sorting packages by neighborhood.

Steve Armato started at Amazon as a software engineer

before Prime, in 2001.

A lot of the things you see today, those weren't there

in 2001.

We had five fulfillment centers back then.

Now we have hundreds.

The delivery vans that you see in the neighborhood,

none of that was there.

Traditional retailers like Walmart and Target were

selling online, but they hadn't started making

promises of speed.

Back then, you know, mail order when Amazon started,

you'd be lucky if you could get something in 2 to 3

weeks. And, you know, Amazon would still promise like

a week and they would yet get it to you in a few days.

So that was amazing.

So how did Amazon pull it off?

The short answer is data.

Long before generative AI became all the rage with the

release of ChatGPT in 2022, general AI was a huge

differentiator for Amazon.

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.

We've been working on AI over 25 years.For employees,

a lot of it is around ergonomics and safety.

For customers, it's around vast selection, great

speeds.

Exploiting technology to drive e-commerce sales.

That's essentially what Amazon has done since '97.

Since the beginning.

They are, I would say, hands down the most data heavy

and data savvy company.

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.

Amazon is decades younger than its major retail

competitors, but its stock value and footprint have

grown incredibly fast.

Hundreds of warehouses, more than 1.5 million U.S.

employees and more speed.

In 2014, amazon launched Prime Now with some

deliveries arriving in an hour or less.

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.

By 2019, one-day shipping was the norm.

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.

By 2022, it was rolling AI transformer models into its

robotics. All that made shipping times even faster.

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.

Could you have gotten to that 60% number without

generative AI?

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.

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.

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

But all this speed comes at a huge cost, in actual cap

ex, but also human labor, a burden that can be

reduced, Amazon says, with the use of robots.

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. And so that's that's great for

ergonomics. It's great for less walking.

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.

Amazon has appealed the citations and said the report

ignores progress it's made, and it says AI can help.

One algorithmic improvement is to take our faster

selling products and place those on the shelves at

waist height. That's your ergonomic power zone.

So less reaching, less bending.

Amazon's big shift to automation started in 2012 with

the purchase of Kiva Systems for $775 million.

Now, Amazon has deployed at least 750,000 robots, more

than double the number it had in 2021.

So generative AI helps with prioritization.

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.

Amazon's next generation of drive units, called

Proteus, are fully autonomous.

They're actually outside of this fenced area, moving

things around. They're using generative AI and

computer vision to avoid obstacles and find the right

place to stop, the right place to park.

And then there's Robin arms, which Amazon says have

handled some 2 billion packages so far.

Would these 20 Robin arms be able to do what they're

doing without generative AI?

I think that we would see that they would require a lot

more training. And so generative AI has been really a

step function improvement in being able to infer from

our vast product catalogue about how to handle a given

product, even if I haven't seen that product before.

And although it's only in a couple of warehouses for

now, there's a humanoid robot called Digit that can

grasp and handle items in a similar way to how people

can. 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.

Of course, this brings up the big question, could

Amazon one day replace all warehouse workers if AI

helps robots get too capable?

There's kind of a balancing act for Amazon.

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?

Amazon says the robots work with people and they're

creating new roles.

We're investing over $1.2 billion to upskill more than

300,000 employees by end of next year.

One study found that each robot adopted in

manufacturing replaced about three workers.

Other research shows that companies that deploy more

robots add more jobs overall.

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. And so each of those creates new categories of

jobs, some of which have higher earnings potential as

well.

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.

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.

To do this, amazon has always used algorithms to

predict how much of what inventory is needed, when

and where.

Every product has like a regional nuance.

We recently regionalized our entire national network.

And by doing a regional network, that means that

products are more likely to ship from fulfillment

centers close to you.

What's new with generative AI is the ability to predict

where to place brand new items.

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. So when we place a product in the right place

ahead of time before you click buy, it's traveling

less distance, which is a win for speed and

sustainability.

Amazon also says AI is helping sustainability with a

specific model that makes better choices about which

packaging to use, and by reducing the number of

damaged items that get sent to and returned by

customers. Amazon says its AI is three times better

than humans at identifying damaged products.

We ship billions of packages.

We have the data about those packages.

So we're able to use computer vision together with

generative AI and that vast 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 a customer.

But training and running 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.

By 2027, AI servers are projected to use up as much

power every year as a small country.

And Amazon Web Services has data centers filled with

servers running AI workloads, although this also gives

it an edge over other e-commerce players because it

can train its AI in-house.

Amazon has also invested $4 billion in AI startup

anthropic, which makes chatbot Claude a competitor to

OpenAI's ChatGPT.

And Amazon makes its own AI-focused microchips and its

own generative AI tools for developers, which are used

in operations.

We use tools like Amazon Q, Amazon Bedrock.

That allows us to evaluate different models against

the, you know, what does good look like?

So what are the metrics for success of this business

application?

One big metric for success that shareholders are

watching: if Amazon's huge investment in AI will

translate to profits.

I have yet to see huge lift in anybody's retail

business due to generative AI, including Amazon.

I think that a lot of their biggest impact has

happened because of the earlier investments, not

necessarily some of these more recent investments.

I've seen a lot of hype, but no actual numbers.

One area Amazon is hoping AI will translate to true

savings is the most expensive part of the delivery

process. Getting that package the last mile to your

door. Amazon is now using more than 20 machine

learning models to figure out the most efficient

routes for its delivery drivers.

If there is more congestion on a road or if a road is

closed, AI is able to help us determine whether that

diversion is still there or take that different route.

In 2021, CNBC talked to Amazon drivers about the

pressures and pitfalls of the job, from dog bites to

urinating in bottles to save time.

People are running through stop signs, running through

yellow lights. Everybody I knew was buckling their

seat belt behind their backs, because the time it took

just to buckle your seat belt, unbuckle your seat belt

every time, was enough time to get you behind

schedule.

The hope is, with better routes and vehicle

coordination, drivers will feel less pressure to cut

corners or skip breaks.

It should enhance the driver experience, but it will

still be challenging.

In 2022, Amazon also rolled out new fully electric

Rivian vans and now has 15,000 of them across the U.S.

They're equipped with large screens where the new

mapping and routing is displayed, as well as

AI-enabled cameras that watch the road, sides of the

vehicle and the driver.

There's no camera recording if the driver is not

driving and there's a privacy mode.

Another area where privacy often comes up is around the

huge amount of data it collects on shopping behavior.

Now, with generative AI, that data can be used to

generate better hyper-personalized product

recommendations to a shopper, thanks to new developer

tools like Amazon Personalize.

What do you say to people when they're concerned about

their privacy? Or that it feels creepy that Amazon

predicts their shopping behavior so closely?

Well, we're looking at aggregate sales history.

We're looking at geographic regions and their

behavior. If a particular customer were in San

Francisco, it's not about that one customer.

It's about what the aggregate behavior in that area

is.

Sellers can also use gen AI to write more targeted

product listings, or to generate images of their

products in different seasonal and lifestyle settings.

For shoppers, last year Amazon.com started populating

with AI generated review highlights.

Any product that you look at is going to have reviews,

hundreds or even thousands.

What I love about AI review summarization is it gives

you just a couple of quick bullet points, and so

that's helping me make a more informed buying

decision.

And in February, Amazon launched a new gen AI powered

conversational shopping assistant called Rufus, to

further streamline those product recommendations.

Some consumers may be put off by product

recommendations that are based on their purchase

history. Now Amazon may have to, if they don't already

implement, an opt out, some sort of feature where a

consumer could say, you know, please don't look at my

purchase history when giving me recommendations.

Despite concerns, Amazon is committed to injecting

generative AI into every possible step of operations

to boost speed, efficiency and eventually, it hopes,

its bottom line.

If you can reduce packaging, is that a good thing?

Yes. If you can reduce the amount of time and the

amount of miles you have to travel to get from point A

to point B, is that a good thing?

Yes. These are all good ideas, you know, kind of

definitely feel free to show us the receipts at any

time.