
Amazon's empire rests on its low-key approach to AI - seagullz
https://www.economist.com/business/2019/04/13/amazons-empire-rests-on-its-low-key-approach-to-ai
======
mi100hael
_> AMAZON’S SIX-PAGE memos are famous. Executives must write one every year,
laying out their business plan. Less well known is that these missives must
always answer one question in particular: how are you planning to use machine
learning? Responses like “not much” are, according to Amazon managers,
discouraged._

I think company culture & talent make a big difference here. At most companies
this would run the risk of poorly shoe-horning ML into a bunch of applications
and making everything needlessly complex & expensive without seeing improved
results (same goes for blockchain).

~~~
maxxxxx
There is also the story of Amazon mandating that all internal systems
communicate with each other through APIs. I think leadership at Amazon has
good technical knowledge so they can develop these strategies and see them
through.

In my company nobody with a "C*O" title (including CIO and CTO) has any clue
about tech so they are very susceptible to snake oil salesmen telling them
things like "we must do ML". So they tell some random person to "implement AI"
but nobody has any clear objectives or can make a judgement whether things go
in the right direction. In most cases these things end up as expensive
disasters. I am waiting for the "Blockchain Excellence Initiative" with a lot
of presentations and shiny newsletters.

~~~
omarchowdhury
How can someone become a CTO without having any clue about tech?

~~~
rogerkirkness
In a big enough company where software isn't the product that just means they
know the tech that applies to that company. The CIO is probably a fearful late
career IT politician and the CTO could have spent 40 years progressively
learning more about washing machines or planes.

~~~
maxxxxx
That's pretty much it. There is also a widespread belief that software
development is "IT" which means that an initiative to implement cloud systems
gets led by people who have experience with desktop deployments or firewall
setup. There is a lot of politics around budgets so the IT department won't
let go of that power.

~~~
pdelgallego
I read in Werners Vogels blog (amazon CTO), that there are four types of CTOs
[1] based on Berray and Sampath paper. [2]

* Infrastructure Manager

* Technology Visionary and Operations Manager

* External Facing Technologist

* Big Thinker

[1]
[https://www.allthingsdistributed.com/2007/07/the_different_c...](https://www.allthingsdistributed.com/2007/07/the_different_cto_roles.html)

[2]
[http://www.brixtonspa.com/Career/The_Role_of_the_CTO_4Models...](http://www.brixtonspa.com/Career/The_Role_of_the_CTO_4Models.pdf)

~~~
jessaustin
That list is not exhaustive. One might also encounter "Peter Principle
Beneficiary".

------
gordon_freeman
I think a lot of people just don't realize that Machine Learning can be as
simple as a linear regression with 2 variables. The hype and myth around ML
are such that some employers just assume that they need to hire rockstar data
scientists to do ML but in reality, a junior level data analyst or even a non-
technical employee can do simple ML model in Excel spreadsheet assuming he/she
has some background in Stats 101.

~~~
steve19
Yes but that is the easy part. The hard part is knowing what can be solved
with ML, gathering the training data, validating the model and then explaining
what the model does.

Acually fitting the model is not the hard part.

But yes, not all ML is deep learning and most ML problems should NOT use deep
learning.

~~~
mr_toad
> Acually fitting the model is not the hard part.

Ideally you shouldn’t be fitting the model yourself. The idea behind ML is to
use brute force computation.

If you’re fitting the model by hand, you’re a Statistician.

~~~
Analog24
Statisticians do not fit models by hand, they "fit" models in the same way
machine learning pratictioners "train" models. "Fitting" in statistics lingo
is completely synonymous with "training" in ML lingo. Statisticians were the
original ML practitioners.

~~~
steve19
I will second this. I use the two words interchangeably. I would probably use
the word fit when talking about liner regression and train when talking about
a more complex ML model that requires more computation. I really don't
remember the last time I fitted a regression model by hand, it would have
probably been in a college exam.

------
dave84
And yet I still get emails from Amazon trying to sell me products I just
bought.

Bought a hygrometer earlier in the week, delivered yesterday, email today
about hygrometers.

Maybe they have data showing that converts well.

~~~
areoform
Actually, they do! This is a frequent misunderstanding, but buyer's remorse is
a common thing and a lot of folks return the items that they've bought because
they're unsatisfied with it. Even if it is 5% of all customers, the numbers
will add up really fast for Amazon.

It's quite clever if you look at it from an aggregate perspective. They're
casting a wider, second net to catch the fish who slip through.

------
agentofoblivion
This year, our internal ML conference ran out of tickets within 90 minutes of
opening registration. There is a whole helluva lot of ML research and
applications going on.

~~~
akhilcacharya
Tell me about it!

\- sincerely, someone that didn’t register in time

------
mxwsn
[https://outline.com/34PN5W](https://outline.com/34PN5W)

------
BrandonWatson
I ran Kindle software Product Management for 3 years. Left in 2014

AMA about the memo process or OP1/OP2 process.

~~~
waldohatesyou
Did you ever feel like it was a waste of time or do you feel it genuinely
added value to the company to engage in that exercise?

~~~
waldohatesyou
Sorry for the double post, accidentally hit reply twice on mobile client.

~~~
jessriedel
You can delete the comment within the first two hours, I think. Certainly can
be edited.

------
secabeen
Amazon is also pushing hard on gathering data. They've offered free photo
storage for prime users for some time; earlier this week, they offered me a
$15 gift card just to install and setup auto-upload of pictures from my cell
phone.

------
hellllllllooo
I thought Amazon's empire rests on AWS which actually funds the company
allowing them to make a sustained loss on their retail business despite
attempts to automate with robotics and ML.

~~~
ajkjk
It's basically the opposite? The retail business funds all the other projects.
That's starting to shift, but only recently.

~~~
hellllllllooo
[https://www.fool.com/investing/2019/04/07/how-amazon-
costco-...](https://www.fool.com/investing/2019/04/07/how-amazon-costco-and-
alphabet-really-make-their-m.aspx)

[https://www.businessinsider.com/amazon-web-services-cloud-
on...](https://www.businessinsider.com/amazon-web-services-cloud-online-
shopping-profits-chart-2017-5)

AWS makes all the money, everything else is marginal.

> Amazon Web Services, which accounted for about 89% of Amazon's $1 billion
> total operating profit this past quarter. That's despite AWS accounting for
> just 10% of the company's overall revenue during the same time frame.

> But despite all of this, Amazon generates just a fraction of its net
> earnings from e-commerce. Instead, Amazon's bread and butter is its cloud
> computing segment, Amazon Web Services (AWS).

------
victor106
Anyone has a link to the full article?

~~~
jonawesomegreen
[https://outline.com/34PN5W](https://outline.com/34PN5W)

~~~
dymk
"Screw ad supported services, if only they provided a way to pay for their
content, then I would totally just do that"

\-- HN

~~~
disgruntledphd2
It adds up fast. I spend 100 euro on all my news subscriptions (and i still
don't have the NYT or the WP). I can totally appreciate that others may not
subscribe as much, or to the same set of services.

Spotify for news would be super good, though.

~~~
dna_polymerase
> Spotify for news would be super good, though.

Apple News+ [0]

[0]: [https://support.apple.com/en-us/HT209513](https://support.apple.com/en-
us/HT209513)

~~~
disgruntledphd2
Yeah, I appreciate the thought, but I have no intention of getting invested in
the Apple ecosystem.

------
east2west
I guess this is making a virtue out of necessity. Amazon is clearly behind
other tech companies in deep learning, so they are calling it "low-key." I
used to work on the retail side, and their prediction process is pretty bland.
They use an off-the-shelf neural networks, but they don't know how to do
modeling, so forecasts are inconsistent. I am sure they will try to
incrementally solve the problem, but proper modeling is foundational to
predictions so I think it will be a long time before it is resolved. Like I
said, it is about average in industry.

