The Future of Manufacturing 2016

THE FUTURE of
MANUFACTURING
May 10-12, 2016. Boston, MA, USA.

2 THE FUTURE OF MANUFACTURING 2016
For more information: contacto@inpeople.biz | ciel@iae.edu.ar
ABUNDANCE IN
THE EXPONENTIAL
INDUSTRIAL ERA / Pag 3
EXPONENTIALS:
MACHINE LEARNING & AI
/ Pag 9
EXPONENTIALS: SMART
NETWORKS & IOT
/ Pag 13
EXPONENTIALS: BIG DATA
/ Pag 19
EXPONENTIALS: ENERGY
(DISTRIBUTED & SMART)
/ Pag 25
HACKING ATOMS: THE
FUTURE OF ADDITIVE
MANUFACTURING
/ Pag 31
THE BIG SHIFT: THEN,
NOW AND TOMORROW
/ Pag 35
VISIONS FROM THE NEAR
FUTURE / Pag 41
BECOMING AN
EXPONENTIAL
MANUFACTURER / Pag 45
BRINGING “CHANGE IN A
DAY” TO OUR FACTORY
FLOORS / Pag 49
SUPPLY CHAIN
INNOVATION: THE SILENT
EXPONENTIAL / Pag 55
HOW DOES ENERGY
OF CROWDS CHANGE
MANUFACTURING?
/ Pag 59
THE FUTURE OF
COLLABORATIVE
PRODUCTION / Pag 63
GARAGE OF THE FUTURE
/ Pag 67
HOW MAKERS ARE
TRANSFORMING
MANUFACTURING
/ Pag 69
WHAT’S THE FUTURE OF
EMPLOYMENT? / Tag 73
STRATEGIC RELATIONS &
SU / Pag 77
EXTRA-TERRESTRIAL
MANUFACTURING
/ Pag 79

3THE FUTURE OF MANUFACTURING 2016
ABUNDANCE IN
THE EXPONENTIAL
INDUSTRIAL ERA
Peter Diamandis. Co-Founder, Singularity University & CEO, XPrize.
Consider this event the place that
you come, to get a sense of what is
going from deceptive to disruptive in
the manufacturing field right now.
According to Peter, this decade,
and the next one will be the most
extraordinary times ever in human
history.
Our brains, the way our brains are
wired, the way we think, evolved in
a very different time, they evolved
hundreds of thousands and millions
of years ago back when the world
was local and linear. Because of that
the way we think is local and linear.
But today we’re living in a world that’s
global and exponential, things aren’t
changing century to century. Things
are not local, something happens in
China or India, and micro seconds
later they appear somewhere else,
and this is fundamentally different
than ever before.
Peter then follows: “We’re here
to talk about all these next two days
it’s computers, network, sensors, AI,
robotics, 3d printing, synthetic biology,
all of these technologies are doubling
in power year after year”.
The difference is either going to
be disruptive stress or disruptive
opportunity. Because if you’re the CEO
of a company that’s been doing it the
same old way and manufacturing for
the last hundred and fifty years, where
proud family company been doing it
the same way, guess what, it’s going
to be swept of stress. If you’re the CEO
of a new 3d printing technology, it
could be disruptive opportunity.
The story of Kodak: In 1996 was at
the top of its game of twenty-billion-
dollar corporation, hundred and forty
thousand employees. Kodak, 20 years
earlier had invented the digital camera.
A guy named Steven Sasson had put
together something he walked into
the boardroom of Kodak with this
large clunky device that takes 0.1
megapixel images in black and white
recording tape drive. And of course the
Kodak Board says “this is a toy for kids
with Kodak we make beautiful high-
resolution images and besides, we are
in the paper and chemicals business”
… and they promptly ignored it. At the
same decade 2012 Kodak files for
bankruptcy put out of business by
the very technology that they had
invented. They had the first actual
property, the first mover advantage,
but they forgot what business they
were truly in.
This is one of the questions during
these exponential times: What
business am I truly in and how am I
serving my customers?
Because the way you serve your
customers, and how do you remain
agile is going to be one of the key
takeaways you need to be thinking
about.
In the same year that Kodak goes
bankrupt, 2012, another company
also the digital images business, gets
acquired by Facebook for a billion
dollars: Instagram. But they’ve got 13
employees.
Peter says he believes they’re
going to be a lot of “Kodak moments”
in manufacturing world. How we
build our houses, how we build our
PETER
DIAMANDIS
Greek–American
engineer, physician,[1]
and entrepreneur
best known for
being the founder
and chairman of the
X Prize Foundation,
the co-founder and
executive chairman of
Singularity University
and the co-author
of the New York
Times bestsellers
Abundance: The
Future Is Better Than
You Think and BOLD:
How to Go Big, Create
Wealth, and Impact
the World.
He is also the former CEO
and co-founder of the Zero
Gravity Corporation, the co-
founder and vice chairman
of Space Adventures Ltd.,
the founder and chairman
of the Rocket Racing
League, the co-founder
of the International Space
University, the co-founder
of Planetary Resources,
founder of Students
for the Exploration and
Development of Space, and
vice-chairman & co-founder
of Human Longevity, Inc.

fittings, how we build our cars, how
we build everything. In the same day
that Twitter goes public, Blockbuster
goes bankrupt and you know the stats
from the old school of business, that
the next 10 years 40% of fortune 500
companies will no longer exist, only
backed up by this stat from Yale which
says if you start a company in 1920s,
the rate of change was rather slow.
Today you get in an S&P 500, you’re
on it for 15 years. And what we’re also
seeing, and this is the challenge, is
young entrepreneurs going from
“I’ve got an idea” to running a billion-
dollar company faster than ever
before.
Chad Hurley starts YouTube on his
credit cards, and sells it to Google for
1.6 billion dollars 18 months later. You
could not have conceived of a couple
of guys really building a company,
never buying a car being worth sixty-
seven billion dollars inside of five and
a half years (UBER).
We as humans are linear thinkers,
Peter says, but that’s not the world that
we’re building. It is an exponential
where the power of the technologies
doubling leads to unexpected results.
It’s going to get any company that’s
not really surfing on top of the tsunami
crushed by the tsunami. It’s the reality
of the world that were living in today.
“I spent 10 years across the Charles
River MIT and at Harvard med school
getting the best degrees I could, but
at the end of the day you become the
world’s expert in a very narrow net [...]
“says Peter.
Here in SU, they are not trying
to make an expert any one of
these technologies, but it’s about
consistently giving you an overview of
where these technologies are today
and where they’re likely to go. Our
brains aren’t wired that way, the best
we can do is make short term linear
projections. And so what SU is about
is creating a venue like Exponential
Manufacturing one for you to come
back and get an update, “this is the
world today and then a year from now
this is what is now possible, and then
this is what’s not possible because
that’s the only way we can do serial
approximation to the kind of growth
were having”.
SU runs programs for graduate
students, they have thousands of
graduate students around the world,
they run programs with Deloitte &
XPrize, and so on.
Now all of this exponential growth at
least the computational realm is riding
on top what we call Moore’s Law. In
1958 Gordon Moore partner with a
few individuals to start Intel. In 1965
seven years later he writes a paper
and says “we’ve noticed something
the number of transistors that are
able to fit on an integrated circuit has
approximately doubled every 12 to 18
months for the last seven years and
it’s likely continue”. And that statement
that it’s likely continue has continued

for 50 years slow down a little bit from
12 months to 18 months 24 months
but it’s been a constant force of nature.
Intel’s first commercial product the
intel 4004, 2300 transistors about a
dollar each. 40 years later the 2012
Nvidia graphical process unit is now
7.1 billion transistors and millions of
a penny each. A hundred-billion-fold
improvement, which is extraordinary
but guess what, it doesn’t stop here it
continues on beyond this.
In 1956 this was a hard drive,
five megabytes a hundred twenty
thousand dollars. Now we probably all
noticed when this occurred right when
2005 it’s hard to eight megabytes for
99 dollars, but did we notice when
it was all of a sudden 120 gigabytes
for 99 dollars, a thousand-fold price
improvement right on schedule on
Moore’s Law.
So the question is, can this growth
go on forever? The answer is a yes
and a no. What we see now is called
the deceptive phase of exponential
growth, in the beginning you see very
slow phase, then explodes and uses
all available resources, and lastly it
falls off. We see this all over the place
and all kinds of technologies. But the
challenge is that it doesn’t stay that
waybecauseofthelawofaccelerating
returns, we use one technology to
build the next technology, and then
use that one to build the next one.
The very first computers were relay
based, and then we went to vacuum,
then we went to transistors, integrated
circuits and we built them and they
look like a continuous process and
so it is continuous exponential
curve. Moore’s law will run out but
something else will supplant it.
Dial-up, it wasn’t so long ago we
became spoiled by your DSL, and then
by cable modems and by fiber optics
and this continues on and on and over
again.
Peter then continues giving
examples about the exponential curve
and it’ behavior throughout the years.
“As I teach this, and this is to you as
the CEOs in the room I want to give
you a conversational vocabulary that
we use at Singular University called
the 6 D’s of Exponentials. As anything
becomes digitized enters a period of
deceptive growth, that it becomes
disruptive that dematerializes, it
demonetizes and it democratizes
products and services. And let me
break this down for you, because I think
it’s this is the road map I use and I think
about it every company I’ve started.
In 17 companies. I’m constantly
looking at how do I’d dematerialize,
demonetize and democratize my
products and services. Because if I’m
not doing it, someone is doing it to
me.”
It’s really hard for the human brain to
tell us where exponential growth were
ten steps away from hundred percent.
We all know about the 3d printing, but
how many of you have heard about
3d printing five years ago? How about
10 years ago? About 20 years ago?
About 30 years ago? It’s a 33-year-old
technology. Chuck Hall involved event
of stereo lithography 33 years ago, it’s
just been in deceptive growth for a
long period of time. And now it starts
hitting the knee of the curve and then
all of a sudden it becomes disruptive.
The next D is Dematerialization and
it’s the notion that 20 years later all of

these things fit in your pocket. My own
cellphone carries a GPS or HD camera,
video camera, flashlight or any of this
stuff it all fits in my pocket and so the
question is: which of your products
or services are you dematerializing?
Guess what, Airbnb is dematerializing
hotels and Uber is dematerializing
cars. So we are dematerializing things
over and over again that’s how you
take in the sharing economy unused
assets and repurpose them very
effectively.
When you make them digital the
marginal cost of replication and
distribution is effectively zero and
they are demonetized.
Uber is democratizing taxi fleet,
Skype long distance, Amazon
bookstores, Google research/libraries,
Airbnb hotel chains and Craigslist
decimated the newspapers. Took
the money out of the classifieds
put it back into the pockets of the
consumers. As the leaderships of your
company which of your products
and services are you dematerializing
and demonetizing? All of a sudden
you can reach a billion people in
Africa. If I wanted to reach a billion
people in Africa. That manufacturing
industry especially through digital
manufacturing is going to enter a
period of rapid dematerialization,
demonetization and democratization.
How are you part of that? All this
is being driven by the exponential
curve. We’re using faster computers
to build faster computers, to build
faster computers. In 2010 the average
thousand-dollar computer from
best buy was calculating a hundred
billion calculations per second,
more computational power the
US government had the sixties and
seventies getting us to the moon.
What we’re talking about here?
Is the notion that faster, cheaper
computing power, which is almost a
force of nature, is driving a whole slew
of technologies.
Peter then goes on his speech with:
“Here in Exponential Manufacturing,
we will be talking about sensons,
networks, 3D printing, AI, Robotics,
and so on... and any one of us could
become an expert in one of these
areas, maybe two. But that’s not the
game we’re playing here. It’s the fact
that these areas are really combining
an unexpected convergent
mechanisms and consequences. It’s
the coordination of AI and sensors and
3d printing coming together it’s really
about”.
Arthur C. Clarke said any technology
far enough advanced looks like
magic. Artificial Intelligence is going
to be magic especially in the digital
manufacturing world. One of the
implications of all these exponential
technologies is a book called
“Abundance”.
Peter says he’s positive about the
future for two reasons:
1) He looks at the data
2) He doesn’t watch the news.
We evolved on the savannahs of
Africa hundreds of thousands and
millions of years ago back when the
world was a dangerous place. And
we evolved the piece of our brain the
temporal lobe called the amygdala
that takes everything that we see and
everything that we hear and process it
first looking for danger.
The fact is that the news media
takes advantage of this hard wiring in
our brain. Peter says that it’s not what
the news media is reporting isn’t true,
it’s that it’s not a fair and balanced
view of the world. We pay so much
more attention to negative news
and positive news. There’s no one
standing outside Logan this morning
going “there was no plane crash here
today”, no one standing outside local
school saying “no school shooting
here today”. You only hear about when
these devices get distributed around

the world every single problem, every
single hardship can be reported to you
in high definition your living room over
and over again. This dystopian view
of the world was brought to us by the
news media.
Peter then talks about subjects
discussed in his book “Abundance”: “I’d
like to close the last few minutes here
by giving you a sense that we truly
are living in the most extraordinary
times ever. In the manufacturing
industries critically important to that
the fact that I can get anything I
want at any time, almost any place
on the planet is unbelievable. I think
about technology is the force it takes
what used to be scarce and makes it
abundant and that’s what you do. You
take something that used to be scarce
and you make it abundant.”
“The Economist” reported that we’re
heading towards the end of poverty. It
was reporting that we are at a 25-year
low for famine on planet earth. We’re
heading towards a time where we’re
going to elevate take everybody out
of extreme poverty and truly give us a
world of abundance.
The number of democracies gone
from a handful in 1802 to nearly a
hundred today. Steven Pinker’s book
“the better angels of our nature”; in
which he says listen we’re living during
the most peaceful time ever in human
history. If you look at the world as a
whole this is the safest time ever to be
alive.
In the nineteen fifties over a hundred
countries on planet earth had more
than six children per family. Today
it’s plummeted. You make a country
better educated and healthier it drops.
“Worldwide life expectancy”: for
most human history, it was 26 years
old who was sort of like what an adult
male would achieve. “During these
next 10 years I truly believe we are
going to double the human life span
once again. Our goal is to make a
hundred years old the new 60. “says
Peter.
For all of human history while the
quality of life has gotten better on
almost every possible account of
luxury, of number of TV shows, of
foods, of materials, of what you could
buy we have the hours we worked.
Automotive accidents are in the
blue, and when we get autonomous
cars will go from 35,000 States down
to zero. 1.3 million around the world
down to zero. We will here Brad
Templeton speak about this here in
orange or red is airlines right we’ve
learned. It’s amazing how we made
transportation so extraordinarily safe.
“This is annual global death rates.
If you look at this in the forties fifties
all the sudden death rates from
epidemics from storms from floods
from earthquakes from droughts starts
to plummet. What happens? our ability
to predict these things get better and
our ability to actually get help was
needed instantly improves.”
It really is the impact of the
technologies that were speaking to
hear about. This is why the world is
changing. This is why we’re heading
towards this extraordinary age of
abundance.
The cost of launching the Company.
In 2000s, the average cost for start-up
was five million dollars. Then enter
open source, then enter AWS and

cloud, and now we’re down to 5,000
dollars. for 5,000 dollars you can
stand up an Internet company and
sell something. That’s a thousand-
fold reduction in cost.
“It isn’t that these amazing startups
creating these billion-dollar overnight
successes are smarter than anybody,
it’s just that there are a thousand
times more attempts on goal and
because of that you can still have 990
ninety failures and 10 unicorns coming
out of it”, Peter emphasizes.
Internet penetration, 1.8 billion
people connected in 2010, and the
low estimate for 2020 is five billion
connected people which means three
billion new consumers who have
never bought your stuff are coming
online. Are you selling to these three
billion new minds or not?
Zuckerberg, Google, Musk, Branson
and Paul Jacobs are working on
capabilities to connect every single
person on the planet. Imagine
eight billion people on planet earth
connected with a megabit per second
connection, with access to the world’s
information on google.
The ability to spin up a thousand
processor cores in AWS, the ability of
your cloud print whatever they want,
if you thought the rate of change was
fast you haven’t seen anything yet right
what are these people going to create
,where they go to event with a desire
to discover its tens of trillions of dollars,
and for the global manufacturing
Industry this is important these people
are going to build stuff, you’re going to
want stuff a pleasure. I thank you for
your time and for your energy. I wish
you an amazing experience here. I
hope you’ll come back year after year
to really learn to appreciate what we
do it single university.
***
Para profundizar recomendamos
VIDEO DE LA CHARLA
https://www.youtube.com/
watch?v=i6Gl_wQxi80
ARTÍCULOS
Stay Ahead of the Next Industrial
Revolution With Exponential
Manufacturing
http://singularityhub.
com/2016/03/16/stay-ahead-of-
the-next-industrial-revolution-
with-exponential-manufacturing/
The fourth industrial revolution –
this time it’s exponential!
http://www.softmachines.org/
wordpress/?p=1776
HERRAMIENTAS
Abundance Insider
http://diamandis.com/abundance-
insider

EXPONENTIALS:
MACHINE LEARNING & AI
Neil Jacobstein - AI & Robotics Co-Chair, SU & Former CEO,
Teknowledge Corporation
AI spent the first six decades of
its history flying below the radar
and now it has suddenly exploded
into public consciousness. The MIT
press published a seminal work and
artificial intelligence applications and
manufacturing 14 years ago.
Manufacturing is a data and
knowledge driven process, it’s all
about manipulating molecules and
we still can’t do atomically precise
manufacturing at scale in spite of that
historical trends and materials and
manufacturing or clear increasing
precision.
Decreasing costs, increasing
flexibility, increasing speed, in fact
accelerating speed and complexity is
now free.
Thanks to the advances in hardware,
in algorithms, in cheap sensors and
then access to data, things have really
changed so AI can now contribute
to manufacturing faster actions and
decisions:
• Product and material innovations
• Improved efficiency
• Higher accuracy
• Lower costs
• Increasing scale
It’s not just about improving
things on the manufacturing floor
but improving things throughout
the manufacturing enterprise from
design to customer service, sales and
administration and quality control.
General Electric has been using AI
in its manufacturing process for three
decades. They’re using big data to
make smarter turbines, to diagnose
problems in their train engines for
decades.
Business Wire just published a report
a few weeks ago on a collaboration
between robot manufacturers FANUC,
Rockwell Automation, Cisco and
Preferred Networks, an AI company.
They’re all about creating an advanced
analytics platform were improving
overall equipment efficiency on the
manufacturing floor.
Yale University has published a series
of articles on using machine learning
to provide integrated optimization of
semiconductor manufacturing.
General Electric is all also providing
a software fabric to go over traditional
manufacturing floors to provide
increases in prediction responsiveness
and connectivity to take a standard
manufacturing floor of old-style
equipment and turn it into a software
configurable manufacturing engine.
IBM has graduated Watson from
playing jeopardy games and working
in medicine to Watson explorer for
manufacturing a single portal for
integrating all of the information from
the manufacturing enterprise.
Search IBM Watson blog just a few
weeks ago looking for the article on
how content analytics, text analytics
and NLP (natural language processing)
has helped auto manufacturers
identify potential product liability
just by looking at Twitter feeds and
customer feedback.
There’s been an increasing pace of
AI investment and acquisition from
2011 through 2015, over
three billion dollars and VC funds
were invested in cognitive technology.
NEIL JACOBSTEIN
Consultant on
AI research and
development projects
for: DARPA, NSF, NASA,
NIH, EPA, DOE, the U.S.
Army and Air Force,
GM, Ford, Boeing,
Applied Materials,
NIST, and other
agencies.
Neil Jacobstein chairs
the Artificial Intelligence
and Robotics Track at
Singularity University on
the NASA Research Park
campus in Mountain View
California. Neil is a former
President of Singularity
University.

During the same period over a
hundred of AI related companies
either merged or were acquired by the
typical players:
Alphabet, IBM, Facebook, Amazon,
Apple
People often described AI as a
game-changing technology but it’s
actually much more than that. AI is
disrupting the entire field that we are
operating on!
The achievement where Alpha GO
won against the World Champion on
GofourgamestooneisaledtheKorean
government to promise three billion
dollars for an AI R&D program aimed
at manufacturing.The underlying
technology behind that Alpha GO
player was a pioneering technology
that combined convolutional neural
networks (you can think of that as a
fancy word for pattern recognition
agent) with reinforcement learning
that reinforces that agent for a high
score in an arbitrary Atari game.
These systems were developed by
DeepMind Technologies in the UK,
demonstrated for the first time in 2013.
The system started from zero
knowledge of any of these Atari games
and they outperformed all previous
approaches machine learning
approaches and did amazingly well
they discovered strategies on their
own. After a hundred and twenty
minutes of training Deep Mind Tech
machine learning system begins
playing at a kind of mediocre human
level. But then after two hundred and
forty minutes of training the system
tunnels up the left hand side of the
screen and plays from the back court
where the game has no defenses that
is a real breakthrough in AI.
Just a month after that 2013 demo
then google acquired Deepmind
Technologies for more than 500
million dollars.
What is AI? People often want
definitions… It’s pattern recognition
techniques to solve practical business
and technical problems. Software
agents that can utilize resources
efficiently.
Most of the work that goes on in AI
and robotics is not going to result in
the sort of science fiction scenarios
but if anybody tells you that the long-
term consequences of the AI will be
all good or all bad, they are cherry
picking the data…
AI comes with trade-offs, yes!

Faster, cheaper, better problem
solving but also job disruption, human
identity change and risk amplification…
and sometimes risk reduction.
The AI community is taking risks
seriously; I was recently invited to
a Conference on the future of AI in
Puerto Rico where I joined with 50 AI
researchers. We sat around for 3 days
and talked about the research agenda
needed over the next few decades to
keep AI doing beneficial things for us.
Elon Musk worked with people
from Y Combinator to create a new
organization called Open AI to pursue
advanced AI in the open so that
everybody has access, not just big
companies. They’re investing 1 billion
dollars and some great researchers in
that endeavor. They’ve already put out
their first product: the Open AI Gym
to evaluate different reinforcement
learning algorithms
The human brain evolved under
very different circumstances and the
ones that we have today it hasn’t had
a major upgrade and over 50,000
years. Compare to your laptop or
your cell phone upgrade in last five
years…
We’re going to have to augment our
cognition both in everyday life and on
the factory floor. We’re going to use
statistical and deep machine learning
task and domain-specific knowledge
engineering marshalling the data
and biologically inspired computing
architectures like deep learning.
Deep learning is the champion
algorithm in machine learning has
been winning all the contests and one
of the things it does is hierarchical
pattern recognition. It can start with
pixels and then go to edges and then
it begins to recognize object parts
at the next layer of the hierarchy
and finally objects and you can add
arbitrary numbers of layers, 152 or
300 or 1.000 and get amazing feature
discrimination.
DARPA (Defense Advanced
Research Projects Agency) has a
new program called probabilistic
programming for advancing machine
learning and what that’s about is
opening up the black box of machine
learning algorithms and getting them
to play well with others particularly
relevant for the manufacturing floor
where we want to be able to use
simulation and optimization and get
all these algorithms to play together.
AI it’s not just better, faster, cheaper…
it’s different AI allows us to expand the
range of the possible in the form of
practical business and manufacturing
problem solving.
Create an application oriented
AI toolbox! Download the Machine
Intelligence Landscape infographic,
is just lots of different examples of
machine learning companies and
techniques, all classified into different
bins.
There’s a company called
Newtonian that you might want to
track, they have a machine learning
product called Eureka. A company
called Río Tinto was working on
powdered metal steel and they
were having trouble in their quality
control. They used Eureka to analyze
many different variables involved in
the powdered metal manufacturing
process and it turned out that one of
the variables that they just threw in
there for kicks turned out to be the
really important one causing their
quality control problems.
If you don’t have the bench
strength in your own company, you
can extend your bench strength by
putting out your data in the public
and putting up some prizemoney at
Kaggle and the world’s greatest data
science teams will compete for the
solution to your problem.
Another way to increase your bench
strength is to use a company called
x / 5 that curates a marketplace of
qualified data scientists they came out
of the Harvard Innovation lab and they

allow you to just put out your problem
without revealing your data and then
pick a qualified data scientist to work
with you.
Let’s talk about some work
implications Oxford Business School
had a study in 2013 of the next 10 to
20 years of the American job market
and they can noted that 47% of the
most routine jobs in America would
be vulnerable to automation over the
next few decades. They updated their
work over the last few weeks. They put
out a new report called Technology
at Work where they looked at the
entire world and they concluded that
developing countries have an even
bigger problem, they have more
people involved in routine work both
in factories and in administrative jobs,
their risk is even higher!
That suggests we’re going to need to
team with AI strength that way we’ll get
best-in-class performance at least for
some deaths pure biases and decision-
making superfast operational velocity
will be able to team with a partner that
works seven days a week 24 hours a
day, no vacation or sick leave required,
no healthcare insurance but limited
empathy, language understanding
and social grace.
The winning formula for working
with AI and robots for that matter
humans plus a is plus good business
process that’s more powerful than
AI alone. We’re going to be able to
combine that power to increase our
productivity remarkably. We’re going
to build very very smart systems.
We’re going to reverse engineer
the human neocortex, make vast
artificial neocortex and make our
factory floor super smart.
How to think outside the box?
There is no box, remember that AI
is going to change the balance of
power between big companies and
small startups.
Some operational
recommendations to transform
manufacturing products and services:
• To team humans plus AI best-in-
class business process is a winning
formula.
• Utilize the power of machine and
deep learning, try all the free tools
that are out there, they’re surprisingly
powerful.
• Leverage AI platforms and your
manufacturing operations, not just in
your customer facing products and
services.
• Outsourced and increase your
bench strength with Kaggle and other
crowd services and be proactive about
security ethics and product liability.
***
ARTÍCULOS
Manufacturing Automation
Leaders Collaborate: Optimizing
Industrial Production Through
Analytics
http://www.businesswire.com/
news/home/20160418006725/
en/Manufacturing-Automation-
Leaders-Collaborate-Optimizing-
Industrial-Production
How content analytics helps
manufacturers improve product
safety and save lives
https://www.ibm.com/blogs/
watson/2016/04/content-
analytics-helps-manufacturers-
improve-product-safety-save-
lives/
The Current State of Machine
Intelligence
http://www.bloomberg.com/
company/announcements/
current-state-machine-
intelligence/
HERRAMIENTAS
www.kaggle.com
http://www.nutonian.com/
products/eureqa/

EXPONENTIALS: SMART
NETWORKS & IOT
Brad Templeton, Director of the EFF, Founder of ClariNet
This text will give you a couple of the
key ways that recent developments in
computing affecting manufacturing.
Having been on the internet for a
long time we can identify what we
think are the ingredients that allowed
it to foment an exponential revolution.
One is the arrival of open platforms
as a way of doing business. You’ve
heard about open source software,
where everyone builds takes what
they build and contributed back to the
world. This idea is actually spreading
now in the hardware. Arduino, is
computer board and is open source
hardware, which is to say that the
design of the hardware has been
released and it’s free for anyone to
modify and anyone to make, and that’s
made it one of the most successful
computers when it comes to making
a small computer for prototyping.
It may actually make sense just as
people in the software world learned
to take the designs for your hardware
and let other people manufacture
and improve it, because no matter
what company you are, no matter
how smart your people are, most of
the smart people in the world work
for someone else Bill Joy said, and
only this system which allows people
to collaborate, has let small projects
come and take over the world.
Another concept is the stupid
network. Back in the nineteen eighties
the phone companies were selling
something called the intelligent
network, the idea of the intelligent
network was they built a new
generation of phone switches and
those phone switches could give you
all the new phone features of the day,
call waiting, call forwarding, you got
them on the phone that was already
on your desk. But the phone didn’t
change because the intelligence was
in the network, the internet turned
that upside down and said let’s
make the network stupid and the
edges smart, all of the smarts of the
internet, this thing that changed the
world so much are not in the internet,
they´re in your phone, in your laptop,
in your tablet, in the web server
you’re talking to. This idea of stupid
infrastructure and smart edges is one
of the Internet’s greatest contributions.
Every industry in the manufacturing
industries have to understand that
they have to virtualize and become
software platforms. In fact, all go
further and say that if you are not a
software company, if you don’t think
of the value that your company owns
as residing in large part in the software
that you develop you may soon not
be a company in the 21st century.
You need this flexibility for a very
important reason, no one have a
crystal ball. Here’s the problem, you
need to make your plans for 20-25 not
with the knowledge of 2016, the way
you’re thinking of doing now, but with
the knowledge of 20-23, it’s going to
compete with a small competitor who
made their plan with the knowledge of
20 23. Now the only way you can face
that competitor in the modern world,
no matter what business you’re in is
if you have the flexibility to change
everything you do because most of it
lies in software.
The sort of platform you have to
BRAD
TEMPLETON
Founder and
designer of the
software for ClariNet
Communications
Corp., the first
internet-based
content company,
then sold it
to Newsedge
Corporation in 1997.
He has taught at Singularity
University, a new multi-
discliplanary school
of rapidly changing
technology since its
founding, and chairs the
track on Computers and
Networks. He built a system
to reinvent the phone call
that you haven’t seen yet.
He writes and researches
the future of automated
transportation at Robocars.
com and is a consultant to
the team building these
cars at Google.

be even when you make physical
goods, even when you’re in the
manufacturing business must be
based on software. Airbnb can rewrite
their software and completely change
what their company is while other
big companies cannot. This is how
you must be if you want to compete
with the young companies who are
coming after you.
About networks, there’s a lot going
on but one development to point out
was done by the Google X lab where
they are putting up balloons in the
stratosphere twenty thousand meters
up above the airplanes, the balloons
just float they don’t have motors but
they can change their altitude, they
can go up and down and when they
do they can find winds at different
speeds and different directions and
they can map these winds and keep
the balloons up for a hundred days
and that allows them to blanket
economically an entire continent with
balloons, providing radio connectivity
to everyone at a low price. There are
three billion people in the world who
are connected to the network today,
but four billion are not and those
four billion will be. Their lives will be
changed, they will have everything
that we have seen, all the changes
in our lives and more importantly
to manufacturers, they will become
their customers, they will have the
ability to see and order products and
understand that other people are
using them and changing their lives.
Another thing to mention is
telepresence robots. In manufacturing
field one thing that’s really interesting
is several manufacturing facilities in
places like China are actually putting
in these telepresence robots which
are allowing their customers to
come and instantaneously visit the
manufacturing lines at any time of
day look at what’s going on, zoom in
on things, inspect what’s going on. It’s
going to become much more possible
to interact more closely with remote
manufacturer and remote for supplier
facilities as you move on in the world.
Another technology that’s going
to make a big change is augmented
reality and we’ve seen some of
this already with things like Google
glass. The company Magic Leap has
received 1.4 billion dollars in private
investment to make augmented reality
glasses. Now that’s the largest private
investment in history. This technology
will not only allow the telepresence
to get better, but also will improve
exactly how people remotely maintain
and control things.
Internet of thing. There is no thing
such as Internet of thing, it´s just
marketing, instead we can mention
three trends and three technologies
making thousands of applications
which are indeed connecting
everything and will in fact create
billions and billions of connected
devices. The three technologies are
sensors, computing, and networks,
and the three trends are getting
cheaper, smaller, and lower power.
In sensors, if you bought a phone
recently you’re seeing all the new
generations of sensors that are
showing up, in computing that’s been
going on with Moore’s law for a long
time but we’ve mentioned a couple
of these small board computers
which are what everybody uses
today when they want to prototype
an experiment with new computing,
such as the $35 Raspberry Pi, and the
new Raspberry Pi will cost just five
dollars. This computer would have
made it on the supercomputer lists in
the late nineteen eighties and now it
is available for less than the price of a
cup of coffee. A full board computer
cost less than a latte and the computer
is going to get cheaper and the latte is
probably going to get more expensive.
This is the trend to look for things
getting so cheap that we can do new
things with them we never would have

conceived as economical before.
In networking there are so many
standards, there’s a lot of hype around
this, we said it was a marketing phrase
and has generated hype so, people
need to understand that this doesn’t
refer to the smart fridge that figures
that when your milk has expired, turns
out your nose still works reasonably
well for solving that problem, it’s not
your washer and dryer having a long
conversation with your thermostat, it’s
not video conferencing for your dogs.
On the other hand think about shoe
tags, they cost less than ten bucks,
they’re the size of a watch battery,
they last for a year on that battery
and you can do basic computing and
networking in them at this low price
and small size and long lifetime.
Industrial applications are
actually where the money is already
being made, sensors that measure
everything that goes into a tank and
what’s going to a tank, understand that
every industrial process, every process
in your factories and so on will in the
coming decade be instrumented. It´s
possible to know where everything
is and what everything is doing
and it’s going to be inexpensive.
Manufacturers need to plan for that
because if they don’t their competitor
will be planning for it and they will
have a more effective process line,
more effective industrial activity.
The biggest dollar value in fact will
be in the supply chain for the early
days.
When it comes to trying to make
a big change look for things that
actually affect people’s lives, the Apple
Watch so far the jury is a bit out on
that, the Fitbit got a big IPO but a lot
of people stopped wearing it after a
while. When it comes to these health
applications are still looking for the
killer app, but we need to think for
example in someone who is actually
sick and need to take pills, a pill bottle
cap which can tell whether you’ve
taken the pills off and taking the cap
off and when you’ve taken the pills
that can be told to his doctor or to
him and that could mean a real thing.
What’s important to remember here

is people are starting to think about
technology that’s so cheap they can
put in a pill bottle cap or even put in
a light bulb, there are lightbulb wich
changes color as the day goes on,
again, when technology is so cheap
that computers and networking are
showing up in lightbulbs and pill bottle
caps, in cups of coffee, that’s what’s
going to change business and how
things instrument into the future.
Here’s a piece of advice trying and
integrating all this chip technology
into your processes, Google did
something amazing when they were
building their company, they were
trying to build servers and they didn´t
have a lot of money, so instead of
the conventional wisdom of buying
the top grade equipment and the
enterprise grade disk drives and servers
they did something else, they bought
the absolute cheapest equipment
they could get their hands on, they
put them on racks on wooden boards
with bricks holding them up, that’s
how they built their server rooms, but
they designed it to expect that these
cheap components would fail, by
the way the expensive components
also fail just less often. So they said it
doesn’t matter whether or not it fails
or how often it fails if we design it for
the redundancy to survive. When good
equipment in Google server rooms
fails nothing happens, it doesn’t even
hiccup, if Google goes down that’s
on the front page of the newspapers
that’s how reliable their servers are,
and all that happens is a guy goes out
once a week with the truck with little
hand truck any slots in the new disk
drives and the new boards that need
replacing because the system.
This is the lesson when things
get really cheap don’t try and then
use it to get really high reliability
stuff that’s still not perfect, use the
cheap stuff and more than one of it,
be redundant so that it can fail and
so that you survived those failures
without a hiccup.
That is how you will provide the
best processes to your customers and
it’s an interesting lesson Google has
taught us.
Cisco forecast that all of these small
technologies will in fact generate
close to 14 trillion - 15 trillion dollars
in value over the next 10 years, a lot
of it from these non-sexy clipart things
like supply chain management, asset
utilization, employee productivity,
they are important to many of the
companies but some of it from the
innovation space. Today the devices in
our lives, all the things that we carry
in our pockets and that we have in
our spaces and build are not nearly as
aware as they should be of where we
are and what we’re doing and we can
fix that if we make our environment a
little bit more connected so that our
devices make our lives frictionless,
that’s what really will change our lives.
One of the world’s largest
manufacturing industries, the
1.7 trillion-dollar automobile
manufacturing industry part of the
five trillion-dollar personal ground
transportation industry is about to
get completely upended by the self-
driving car.
Is going at it mostly to think about
saving lives, 1.2 million people are
killed around the world in car accidents
and that is one of the world’s greatest
diseases if it were a disease, and we
have the potential to change that
and change it around the world, and
so this is what’s driving people to go
forward but the consequences to
everything else are going to be huge,
and in fact that entire automobile
manufacturing industry is up for grabs
and other industries can be as they
are digitized, which is why you need
to learn a little bit about this one,
the energy industry believe it or not
is also changed because as people
move towards buying cars by the ride
instead of buying cars as cars, buying

the manufactured product as a service
instead of as a manufactured product.
Suddenly all the buying decisions
about it change, people don’t go to a
car dealer looking for the car they’re
going on for five years, they pick up
their phone looking for the car they’re
going to use for 10 minutes, the way
they do with Uber, and suddenly
they don’t care about the energy, the
brand, the suppliers, all the old rules
of that giant manufacturing industry
are upended when it becomes digital.
We can see two different approaches
between the companies applying
this, the car companies are taking a
traditional manufacturers approach,
they’re taking the cars they make
and they’re adding computers to
them hoping to improve them and
make them drive themselves. It’s
an evolutionary approach but the
non-car companies, the high-tech
companies, they’re taking computers
and sticking wheels under them to
see what happens. A revolutionary
approach that works at the innovation
pace of the computer industry for very
different results.
There are going to be a lot of
winners and losers in this space
but the winners will not be the
manufacturing companies but rather
the people who own the customer
and provide that service, and this will
happen in cars and it will happen in
every industry soon if they do not
become aware of the way it becomes
digitized.
The big change here is that in the
car the engine is no longer the most
important part of it, the computer is
and while the engine and the other
parts of the car aren´t on the Moore’s
law curve, that computer and software
are, and everything we said above
suddenly applied to an industrial
industry that has no idea of how to
deal with it.
One last thing that will change all

sorts of goods is the ability to build
delivery robots rather than self-driving
cars. A company in Europe have built
robots which run on the sidewalks,
they’re going to be able to bring you
anything in 30 minutes, not just a pizza,
for example You´ll be able to order five
pairs of shoes, try them on throw for
back in the robot and send it back,
that hold that retail store experience in
your home will suddenly allow us to
consider what the meaning of retailing
is and even what the meaning of
ownership of manufactured goods is,
because if you can get anything in 30
minutes as this technology promises
for under a dollar do you need to own
things? There are many things in your
life that you may decide you don’t
need to own when goods move as
quickly as data.
So big changes coming from
robots from computers and from the
digitization of all the products you
make and the transportation that
carries them and so watch out for the
future very much.
***
VIDEO DE LA CHARLA
watch?v=HORuh5tnAuU
ARTÍCULOS
Siri-creator shows off first public
demo of Viv, ‘the intelligent
interface for everything’
https://techcrunch.
com/2016/05/09/siri-creator-
shows-off-first-public-demo-of-
viv-the-intelligent-interface-for-
everything/
Here’s the first demo of Viv, the
next-generation AI assistant built
by Siri creator
https://techcrunch.
com/2016/10/05/samsung-
acquires-viv-a-next-gen-ai-
assistant-built-by-creators-of-
apples-siri/
Crazy ideas, inventions and essays
from Brad Templeton
http://ideas.4brad.com/
HERRAMIENTAS
https://www.playpiper.com/
https://www. grabcad.com/
https://www.magicleap.com/#/
home
https://www.raspberrypi.org/
products/

EXPONENTIALS: BIG
DATA
Cack Wilhelm. Principle, Scale Venture Partners.
We often think about big data is
this proper noun, capital B big and
capital D data. When in fact it’s really
just an adjective: Big describing
something, Data that’s been around
since the dawn of time. You’ve heard
from experts all morning, you’ve
heard about robotics and 3d printing,
machine learning, artificial intelligence
and put it in context, we can think of
these as inputs and outputs. Robotics,
3d printing, these are creators of data.
These are things that are creating data
that’s making the data quote big.
On the other hand you have
machine learning and artificial
intelligence, these are the logical
extension of having all the data. Now
that we have the data, how can we
get one step closer to intelligence?
Think of this first wave of data as
the rise of oracle, relational databases,
structured data. Second wave, roughly
advent of Hadoop, distributed systems
the ability to store unstructured data.
Today, we’re constantly bombarded
with the idea of data. Everyone has
statistics on what happens in an
Internet minute. The one thing worth
of highlight in manufacturing, this is
generally true for all industries, but
for manufacturing specifically the
data historian has been collecting
large scale time series data for many
decades much longer that Pinterest
and Twitter have been collecting
favorites and collecting likes.
That was all step back looking at the
past, looking into the future everything
is up into the right, take sensors for
example: In addition to all of the
devices things that have already been
connected to the internet Gartner
expects that every single day 5.5
million additional devices and quote
things will be connected to the
Internet. Likewise, platforms, we had
the rise of pcs followed by the internet
followed by social networks, and
most recently smartphones. In the
CACK WILHELM
Cack joined Scale
Venture Partners in
2014 and focuses on
investments in next-
generation enterprise
software companies,
with a particular
emphasis on the cloud
infrastructure, big
data, DevOps, and
security sectors.
Cack’s efforts have led
to Scale investments in
mobile database company
Realm and cloud analytics
infrastructure company
Treasure Data.

same amount of time the adoption of
smartphones was ten times biger that
of PCs.
Lastly, we all know what happens
in an Internet minute, number of
tweets, number of YouTube videos
downloaded number of emails
sent. What’s more interesting in
this context and especially as an
enterprise investor is what’s the
amount of data that streaming off an
airplane, off other industrial systems,
off wind turbines, etc
In the old world we would all agree
that Fiat, Chrysler, Honda these are
all asset intensive businesses. Fast
forward, Uber owns 0 vehicles and
they command the supposed private
value of 50 billion.
Fiat and Honda are real asset
intensive and Uber is data as an asset
intensive. Data can no longer be
ignored. Uber is the classic canonical
text book case of network effects. As
the number of drivers rise, the number
of participants rises on the platform,
a number of things happen. Drivers
don’t wait as long between rides,
passengers don’t want it along to hail a
cab or the today’s equivalent of a cab.
Prices are optimized, bad actors are
weeded out and as a result you reach
this natural equal equilibrium between
supply and demand. This is going to
be true across markets for Uber.
Secondly Ubers canonical case of
moving to a service model. Instead
of selling you the car, Uber sells you
a ride inside a car and as a result
they’re able to really effectively match
the value generated with the value
received on the other end. Now Uber
is not doing this for the good and for
the love of passengers and drivers.
As a result, Uber is collecting the
superset of data. Every single ride over
collects a little bit more data by the
second and as a result they’re able to
finally tuned their models, they better
improve prices, better optimized for
supply and demand. Uber ends up
with a computational advantage.
The winner in this space will be the
one with the most data. The reason
being that yield man that ride sharing
is a very complex yield management
equation and it’s one that’s dynamic
and always changing there’s nothing
static about it.
Another great example: Nokia,
we all think of it as a hardware
Company classic competitive strategic
advantages they had scoped, they
had great supply chain, R&D and beat
R&D Budget. Apple had less than
ten percent market share and they
had something that hadn’t yet been
recognized and that was a platform.
As you can see here the value of Apple
is not the hardware along.
That value of Apple is a
combination of the hardware, which
we all know in this room is very hard,
to take raw material supply chain
is very complex. In addition, the
differentiated software. The Apple
App Store brings together producers
and consumers in a very high value
exchange of which Apple takes a
cut of each and every one of those
transactions. Unlike many hardware
products where you buy it once,
you never interact with the producer
again. With Apple it’s very likely that all
of us continue to interact with Apple.
We may buy music, we may read
movies and subscribe to Apple Music,
these are all marginal cost near zero
and Apple able to drive a lot of this
premium. The iPhone in total to date
has generated more than six hundred
billion dollars in revenue, arguably one
of the most successful products ever.
Data volumes are increasing, they
are accelerating and it’s only going to
get worse. It is expected that by 2020
almost ten percent, maybe more, of
data will be generated at the edge. So
you can think of it as we are drowning
on data and it’s this perfect storm
of factors. Take cloud for example,
Amazon web services, a developer

can spin up compute and storage in a
matter of seconds and you can build a
company with less than five thousand
dollars. Connectivity, sensors, battery
life and all things are miniaturizing
(e.g. Raspberry Pi). You’re able to put
sensors into more and more things.
Lastly, data silos creating all of this data,
but unfortunately creating the perfect
storm of factors mentioned before. As
a result, we have this fallacy that more
information is going to give us more
intelligence, more money we spend
on software startups in San Francisco
are going to all of a sudden bring us
the insight.
Automation has been around
in manufacturing for many years,
however, there are more cases where
automation can truly be harnessed.
Machine learning is meant to be overly
complex and that’s unapproachable. In
the general case, machine learning is
trying to take the burden from humans
to machines to do the advanced
computation, the experimentation
and the model training without
constant oversight from humans. It´s
the scientific method on steroids.
Every company is starting to
move in the direction of becoming
a software Company. JPMorgan
rumored to have to employ more
software engineers than Google
which is hard to fathom. Jamie Dimon
is very outspoken in his search to
becoming a software Company and
utilizing more and more algorithms.
Likewise, Capital One, we think of their
products is being credit cards, there
CIOs are thinking that his products
are software and data.
Disrupting commerce is way easier,
disrupting manufacturing turns out
really hard. You can’t replace an
airplane with software. You can make
a better airplane; you can do so faster
you can do so differently but you can’t
in fact replace it.
Turns out Honda and Fiat still has
to sell cars to Uber, to Uber then
drive us around as passengers. In the

autonomous car case, we still need
the cars. Drivers may be optional,
but we still will need the cars to get
around. American Airlines has to buy
airplanes. They may be able to better
service those airplanes, they may be
able to predict maintenance better
with the use of data. But they still have
to deliver those airplanes.
You can really think of the way
machine learning is going to impact
industry and in two different ways:
(1) the way of improving the
process of making things
(2) the second improving actual
products themselves
On the first, “automating the
process”, Rio Tinto (mining giant in
Australia), use autonomous trucks to
transport iron. That is improving their
process, granted it’s in the natural
resources sector not manufacturing
but same idea. Amazon right now
in their warehouse floor, machines
robots are running around putting
packages together to deliver the end
product to our doorstep more quickly
more effectively.
On the second piece, “improving
the product”, think about how software
has played into the rise of Tesla. Tesla
instead of delivering your car, you
driving off and never improving the
car again, can just update a few code
snippets, push it to the car, and you
have an improved car over the air
with no visit back to the dealer.
Predictive maintenance, is a far cry
from this dawn of Singularity.
Automating the process of
manufacturing as opposed to
automating the end product. Design,
creation and modeling, are tightening
up and moving to a virtual world with
the help of digital. The iteration cycle
is happening faster. For example if
you visit to the San Francisco recycling
plant, it’s actually a sight to behold.
Humans working alongside machines,
conveyor belt going every which
direction, robotic arms trying to pull
off the big cardboard boxes, etc. There
is a lot of innovation happening in this
space.
What’s most interesting we have
all the use cases, in fact there are so
many brains applying themselves
to coming up with companies in
the space and trying to take these
use cases make some optional,
operational and deliver them to all
of you. Maana for example just raise
26 million dollars last week from a
combination of some extremely good
corporate VC’s, focused on creating
an enterprise knowledge graph and
focused exclusively on manufacturing
and Natural Resources. Site machine,
canonical example in manufacturing,
again west coast based, they’re trying
to create a data hub collecting data
from sensors, from databases, from
plant equipment, from every which
direction system of record and trying
to analyze all of it, and create insights.
That’s everybody goal.
Falconry claiming to do artificial
intelligence with sensors specifically,
time series data is increased incredibly
hard compute problem and they’re
trying to tackle it from the sensor side.
Moncler they make expensive puffy
coats in the East in Europe and they’re
in bedding unique identifiable sensors
into every coat with the object goal of
reducing counter foot good. As things
become more and more connected
we’re going to have more target
cases. HVAC units being infiltrated so
we have to be wary of this.
Computer must move to the edge
for technology to disappear. We can
no longer have this tethered piece
to the cloud brain, whereby all of
the intelligence is happening in the
cloud or bandwidth and connectivity
are going to be overwhelmed. You’re
seeing early signs of this: Google
open source Tensorflow and turns out
that you can in fact run small scale

examples of tensorflow on a mobile
phone.
Secondly 3d printing, in the case of
manufacturing for discrete parts and
complex pet products, especially as
the design cycle iteration utilizing 3d
printing to get the modeling out the
door more quickly.
Lastly drones and augmented reality
now. Virtual reality will be a much
more of a consumer and much more
of an entertainment focused use case.
That said, we’re due for a platform
shift. Smartphones was really the last
platform that emerged, and that was
in 2007-2008. Historically it’s been
every seven or eight years. Drones and
augmented reality have a place and
they will be roommate.
Cack finishes saying that she has
two more thoughts:
• “More data will always beat better
algorithms.”
• “Lastly the reason we’re here is
because the pace of innovation is
changing and it’s changing rapidly.
This is empirical and this is known,
if you haven’t come away from the
morning picking that up then we
failed. But what remains is the pace of
an option, it’s up to all of you, to each
individual enterprise, each individual
manufacturing company, each
business unit, each business leader,
to determine how and where you’re
going to utilize this data to generate a
competitive advantage.”
***

VIDEO DE LA CHARLA
watch?v=cQpjcrxo5I4
ARTÍCULOS
Data Driven Smarter Industrial
Systems
http://es.slideshare.net/ScaleVP/data-
driving-smarter-industrial-systems
HERRAMIENTAS
https://www.maana.io/
http://sightmachine.com/
http://falkonry.com/
http://uptake.com/

EXPONENTIALS: ENERGY
(DISTRIBUTED & SMART)
Ramez Naam. Professional technologist and science fiction writer.
Ramez starts the speech talking
about the disruption of energy,
because energy which has been a
fairly static industry for decades is
now an exponential industry with
rapid changes in technology.
Ramez says a few years ago he
wrote a book about the challenges of
Natural Resources and environment
and the question: “Can we innovate
fast enough to overcome them?”, and
what he found in doing the research
for that book is that the technology
progress in the energy space is
incredibly rapid and far faster than
most people take for granted, and
if we play out those trends and take
the math seriously it has staggering
consequences. Ramez also says he
is a clean tech investor, so he come
at this from a perspective looking at
where they’re good deals, where there
are opportunities to disrupt markets
and also build large new markets and
large new companies.
Wind power might look like a
stagnant 19th century technology
but it’s actually one that has changed
tremendously. Over the last dozen
years, the amount of wind power we
have deployed to buy a thousand
percent (x10). That’s not normal in
the energy field, and that happen for
a number of reasons: Policy pushing
it was a big one, but that policy would
not have been effective if it were not
for an exponential decline in the
cost of wind power. Whole power,
electricity prices in the US are around
seven cents. Let’s say in the nineteen
eighties wind power costs nearly 10
times that much per kilowatt hour,
now, last year, the average price of a
new wind power long-term contract
in the US was actually 2.3 cents per
kilowatt hour and the cheapest were
below 2 cents. That is a staggering
drop in the price of wind energy and
it’s been driven by a huge amount of
innovation in the sector. A basic thing
is that we have learned to make these
wind turbines bigger. Why does that
matter? Well higher up the wind blows
more steadily and it blows faster, so
that gives you an advantage. And
secondly, the amount of power you
get from a wind turbine is equal to the
area the blade sweeps through, so if
you can double the blade length you
can quadruple the amount of power
you’re capturing. You can also capture
lower speed winds.
So as we’re learning more and more
about manufacturing techniques,
about new materials we’re able to
tap into these, and we can see how
the price of wind power has plunged
as the scale of these turbines has
grown, and this leads not just to more
power at a lower cost, it leads to
steadier power. Today the wind fleet
operates at a thirty percent capacity
factor. That means that a wind turbine
produces about thirty percent of the
max that is expected for, but as we
get towards taller and taller turbines
the Department of Energy expects
that within a few years we’ll be able
to get sixty percent up time of these
wind turbines, and now it no longer
looks like an intermittent platform for
energy but more like a steady one.
GE is one of the leaders worldwide in
the development of these new wind
turbines and innovating in new ways
like the GE space frame to build them
RAMEZ NAAM
Naam was involved
in the development
of software products
such as Microsoft
Internet Explorer and
Microsoft Outlook. His
last role at Microsoft
was as a Partner
Group Program
Manager in Search
Relevance for Live
Search.
Naam currently holds a seat
on the advisory board of
the Acceleration Studies
Foundation, is a member of
the World Future Society,
a Senior Associate of the
Foresight Institute, and
a fellow of the Institute
for Ethics and Emerging
Technologies.

taller while transporting them.
Big data, machine learning, and so
on, that is also vital here because these
individual turbines are intermittent.
What was found is in cases like
Colorado with the excel utility there,
using sensors on the wind turbines
collecting that data and putting it into
algorithms to do predictions of which
turbine was going to spin at which
speed, a few minutes from now, a few
hours from now, on a day from now,
allowed excel to triple the amount of
wind power they could put on their
grid and that saved them billions of
dollars, because it is the cheapest
power they could buy in their state.
As we mentioned before, higher up
the wind blows more steadily. Marc
Andreessen says software is eating the
world, and this is an example of that:
A prototype that’s not in production
yet about a blimp that has inside of it a
small wind turbine, and it is actually a
drone, it flies under computer power
and it can hover about 500 meters
above the ground (three times taller
than the tallest wind turbines) and
tap into those high-speed winds and
then drop down in the case where
the wind is too high for it to be safe.
Or as another example there’s another
drone from a company called Makani
power in the Bay Area. It tilts back,
takes off under computer control, flies
up to as high as a kilometer up tapping
into those high-speed steady wins;
You could never pay the capital cost
for a kilometer-tall tower but you can
pay the software costs to self-steer
this drone and then act as a giant wind
turbine in the sky. This company was
acquired by google two years ago
who wants to bring it to production.
Another point to highlight is Solar
energy. There has been an incredible
pace of innovation in solar panels.
They are made of a chip and if we
wanted to plaster thousands of
square miles with intel chips, the
cost for that would be Quadrillions
of dollars, it would be impossible.
But, like silicon wafers solar power
has had a ferocious and exponential
cost decline over the course of the
last 30 years (it has plunged by 200
times), that means we’re now seeing
solar energy winning deals without
subsidies in various parts of the world.
It happens especially in places where

the 1.3 billion people that don’t have
electricity today live and about three-
quarters of the world’s growth in
energy consumption over the next few
decades will be which is a relatively
sunny area.
Regarding Cross-over, one physical
case worth mentioning is a natural
gas plant in the US the EIA estimates
this cost seven and a half cents per
kilowatt hour if you build a new one. In
Chile we’ve had about a dozen deals
and an average price about six cents
per kilowatt hour without subsidies,
China (the Gobi Desert) also got six
cents, India an Ambar ultra-plant 4
gigawatt plant, an enormous plant
the size of four large coal powered
plants and capacity at about six
cents per kilowatt hour, and in the
US six months ago First Solar sold to
Berkshire Hathaway a 3.9 cents kw/h
central in our deal and then last month
the city of Palo Alto bought solar from
a company in LA at 3.6 cents kw/h.
Now this is a subsidized price, but back
out all the subsidies about five cents
per kilowatt-hour and it’s still about a
third lower the price of new natural
gas and its producing at peak demand
time. And around the world is even
better than that, Mexico: the average
price in their solar auction last month
was 5.1 cents, the lowest price was 3.5
cents unsubsidized. The price in the
US in the last eight years has plunged
about 80%, just a phenomenal pace
of change.
In Dubai, one of the oil capitals of
the world, this 800 megawatt plant a
giant plant being built by Aqua Power
(a Saudi firm) and this price did with
no subsidies for this plant for the next
tranche was 2.99 cents, about half the
price of natural gas. In the last three
years we’ve gone from solar being
completely uncompetitive to solar
in sunny parts of the world crushing
all other competitors as far as price
goes up and that has helped drive an
enormous explosion.
Wind power scaled by a thousand
percent 10x in a dozen years, Solar has
left that in the dust a 100 times growth
in 13 years. For now, this explosion
is unlike anything that we’ve seen in
energy.
This happens for a lot of reasons.
Manufacturing scale, one of the first
Exponential’s we ever saw is that the
price drops along the learning curve,
and this curve is quite ferocious, 20
to 25% reduction in cost per doubling
of scale, and that’s going to keep on
going for quite some time. That allows
the industry to reinvest revenue in
R&D to make more and more efficient
cells that capture more of the sunlight
that hits them, so the prices are going
to keep dropping. We are very far
from done yet and the prices that you
see in Dubai or Mexico will one day
be the prices in California, and then
after that they’ll be the prices in Middle
America and we will have the ability
to extend the grid to spread out but,
what do you do if the Sun isn’t shining
or if the wind isn’t blowing? These are
still intermittent resources, no matter
how high their capacity factors are.
With good integration, you have
a far steadier output. Diversity, you
can put solar and wind together.
We think now that about eighty
percent of electricity meet needs in
California can be met with no storage
just putting together solar and wind
and large-scale grid connections.
There’s also another kind of challenge
that happens because solar is getting
so cheap so fast. For a long time, the
power prices that you all had been
paying are highest in the middle of the
day, because that’s when peak demand
is (Supply and demand: there’s more
demand the middle of the day in the
late afternoon so prices are higher),
but as solar comes online or perhaps
a decade away from a point where
the middle of the day power prices
in much in America are at the lowest
prices because it’s a surplus of power

right then and there.
Internet of Things. You hear a lot
about smart power, and that’s what
this means is being clever about how
and when to use energy to match
the prices you want. Nest company
bought by Google. Why does google
want a thermostat? Because this is
part of the smart grid. This thermostat
knows if someone is home and it has
a connection to the utility, and if the
utility sees that a very expensive peak
of power demand is coming late that
afternoon because it’s a hot day in
Austin, then they can reach out to
these nests and say “hey we want to
avoid that peak run the air conditioner
a little harder a couple hours early and
then we won’t have to have such a high
peak demand”, and spin up new power
plants and the person at home never
notices this is happening and they get
a reward. They had a kickback from
the utility because this is a savings of
tens of billions of dollars potentially
across the country.
In Europe it’s hot water heaters, so
these hot water heaters increasingly
are getting smart. They know when
the power cost is low; in Europe it’s
when wind power peaks sometimes
it might the price drops to zero or
negative, utilities will pay you to
take energy, and so these connected
smart water heaters know that and
say we’ll take that will save it up for
the morning. Or data centers, the
world’s data centers use now about
12% of electricity and growing; all that
IOT and cloud stuff it’s not for free,
it’s real and it exists in places like this,
and they’re becoming increasingly
smart being able to absorb load.
Another example are electric vehicles;
if you have a Tesla you already know
that has programming to go for low
power prices or during the day they
sit at work and whether its own solar
panels at the workplace or just the
solar utility-scale attention to the grid,
when that price drops during the peak
hours of the day that car is sitting there
and ready to be charged and provide
services of the grid by being able to
soak up the extra.
Water. In West coast California
where there is a massive drought,
we can desalinate water. Desalinated
acceleration is expensive but about
half the cost is energy costs, so this is
somethingyoucandowhentheenergy
gets the cheapest; a desalination
plant in Dubai consumes 12 gigawatts
of power and desalination about
500 million barrels of water gallons
of water per day. Mapping that the
lowest energy prices suddenly allows
you the flexibility didn’t have.

Ultimately though you need energy
storage. We all know who Elon
Musk is. He’s announcing the tesla
powerwall battery, and the funny
thing is Panasonic makes that battery
and it’s got a Tesla casing on the
outside; but it’s not some technical
breakthrough that got them there it’s a
long-term exponential trend. A tripling
in the amount of power you can store
program and a 10x reduction in the
cost of batteries over the course of
the last 20 years and that keeps on
going.
In Germany now it looks like with a
small battery, about half the size of the
powerwall, and a small solar panel a
German household can provide about
seventy percent of its own energy in
summer months. So if your utility and
your business model is charging by
volume, what happens to you in this
world? Businesses models are going
to have to change and now we start
to see utilities wanting to own that
solar panel so they can get it on both
sides, and the ones that flourish will
do that but Tesla got a billion dollars
in pre-orders the first week they
announced the battery most of them
did not go to homes ninety percent
were for this size battery which went
to businesses, commercial spaces,
factories and utilities and now every
manufacturer in the world that does
solar is moving into the same thing.
Trina solar battery, the largest solar
company in the world, about a 1
megawatt hour battery, and they go
after some very simple scenarios, even
if you don’t care about solar that’s
probably the case that you pay one
price for energy at night that’s very
cheap and another price during the
day; in California that Delta is about 20
cents per kw/h. Guess what? A battery
is cheaper than that now, so you can
fill it up at night with cheap power
and then discharged it during the
day instead of using that expensive
power.
Battery prices are not done coming
down. There is a whole range of
different forecasts about where
battery prices would go and these
analysts (including the EIA) said that
there would be huge drops over a 10
years’ period. Batteries also follow the
exponential learning curve, as they get
higher scale they drop in price and
they do so it basically the exact same
pace as solar. This leads to a crazy
idea being that energy going clean
might actually be cheaper than dirty
energy, we’ve always assumed that
going clean meant higher prices, but
now we’re starting to see even very
conservative organizations say that it
might actually be cheaper.
The IEA says solar will be the
dominant form of electricity in
midcentury and the cost will be
unbeatable for UBS. They said
renewables are now deflationary to
energy prices. We’ve coupled the cost
of energy to the ever-declining cost of
technology. It’s like your Kodak: you
think these digital cameras will never
catch up. The world is now to using
more clean energy per year than dirty
energy, and we will never look back.
The former Saudi oil minister once
said: “The stone age didn’t and for a
lack of stone, and the oil age will end
long before we run out of oil”. He’s
warning us that the world is going to
produce a technology replacement

for oil. Oil fluctuates by a two percent,
two million barrels per day difference
in supply demand has caused this
huge oil fluctuation that nobody
predicted it, but we are headed there
and ELECTRIC VEHICLES are going to
get us there. The EIA forecasted that
we’d be selling 1,000 vehicles a year
with a 200-mile range by 2040, so you
just can’t trust the experts in this, trust
the technology and the innovators.
And as the battery prices come down
we’ll sell more EVs which will bring
down the cost of batteries, which will
make EVs cheaper, and we’ll some
more EVs as a perfect virtuous cycle.
By 2030 they’ll be cheaper than the
cheapest car sold in the US. The long-
term price of oil is very cheap as our
demand drops.generated over sixteen
billion dollars in revenue.
***
VIDEO DE LA CHARLA
watch?v=9Ui-4MxgeW4
ARTÍCULOS
Meet the Makani Energy Kite
http://www.alternative-energy-
news.info/makani-energy-kite/
The floating wind turbine that
thinks it’s a blimp
http://www.wired.co.uk/article/
turbine-blimp
This wind turbine can think for
itself
http://www.wired.co.uk/article/
thinking-wind-turbine
This Plant in Dubai Makes Half a
Billion Gallons of Fresh Water a
Day
http://time.com/3625511/this-
plant-in-dubai-makes-half-a-
billion-gallons-of-fresh-water-a-
day/
The Claude “Bud” Lewis Carlsbad
Desalination Plant
http://carlsbaddesal.com/
HERRAMIENTAS
http://www.trinasolar.com/sp/
index.html

HACKING ATOMS: THE
FUTURE OF ADDITIVE
MANUFACTURING
Andre Wegner. Founder and CEO, Authentis.
Andre is a frequent speaker on
emerging intellectual property issues
in 3D Printing and opportunities of
distributed manufacturing at events
such as Singularity University, Rapid,
Designer of Things, Inside 3D Printing,
3D Print Show, Pacific Crest & WIRED.
He has been quoted in publications
such as BBC News, MIT Tech Review,
Chicago Tribune, and Bloomberg. He
is an expert in greenfield value chain
creation, leading the development of
a $300m low income gas distribution
business for West Africa’s leading Oil
and Gas company.
Andre starts his speech talking
about additive manufacturing, and
mentioning the spike in the stock
prices. He says that it’s not over.
Over the last couple of months
especially, there has been crystallizing
opportunities in the additive
manufacturing space, it’s a bit like the
internet was for digital products. We’re
realizing that it impacts have absolutely
everything we do around us. Andre
says they’ve been crystallizing out one
of the opportunities that “really makes
sense” and in that process they’ve
been filtering out the stuff that doesn’t
work.
One of the things that has been
coming for the last year, especially
over the last 18 months, a lot of speed
innovations. HP came out with a
printer at end of 2014 and said it was
10 times faster than its predecessor,
for example, and now you hear
Chinese companies saying they can
make a printer of five hundred times
faster speed.
Electronics is also an area that is
growing rapidly. A lot of startups in that
space, but also established companies
like a Xerox investing “Hot Lips”,
looking about how we can combine
different electronic components in the
3D printing process to enable us to
print entire circuits. Lot of innovation
happening both in PCB, prototyping,
but also in printing an electronics onto
materials such as clothing to have
flexible electronic printing.
A third area of technology that’s
really going to boost in the last 12
months is metal. Metal is being driven
by a lot of industrial applications,
different kinds of approaches to actual
problems or obstacles.
What’s driving all of this innovation
is really the fact that managers
have now started to engage with
the technology, and are dictating
the innovation agenda for additive
manufacturing. We’re becoming a lot
smart about where we are investing
our money, because the companies
are getting more signals from where
you and other manufacturers like you
tell them what needs to be done.
What they’re doing with this is clear,
in three areas: Prototyping, Tooling
and Direct production.
Andrethenkeepsongivingexamples
in different areas where innovation has
played a huge part, such as Medical
with fully porous acetabular cups, that
grow go up to twenty-five percent
faster into the bone reducing healing
times, or in space where SpaceX has
been flying 3d printed components
since 2014.
ANDRE WEGNER
He is a frequent
speaker on emerging
intellectual property
issues in 3D Printing
and opportunities
of distributed
manufacturing.
Prior to founding
Authentise Andre also
managed a venture
capital fund in Nigeria and
advisory services in India.
Andre is a graduate of St.
Andrews University (M.A. -
UK), ESSEC (M.Sc. - France)
and Singularity University
(California).

As Andre mentions, a lot of
applications that are being developed
on top of those innovations because
managers are finally setting the
agenda, and showing us where we
have to go. Singularity had a very
special visitor: 3d printed supercar
done by a company called Divergent.
It’s twice the power to weight ratio of
a Bugatti, and reducing the tooling
costs from 250 million dollars for
small series car to16 million dollars.
Let’s just repeat that, for car that makes
that’s made in volumes about 10,000
a year, tooling cost is down from 250
million dollars to 16 million dollars.
Andre then reinforces: “A lot of
different kinds of industries being
impacted and what we’re seeing is
as a result of these innovations is that
people are coming up against barriers,
all the time…” He then talks about
the case of Invisalign, suing clear
connect in front of the International
Trade Commission saying that Clear
Connect was breaking its patterns by
processing the files for those Invisalign
teeth that Clear Connect makes by
processing them in Pakistan and
importing the digital file to print it in
the US.
The barriers keep on coming.
Experimentation in 3d printing make
us have to look to rewrite sections of
the law to account for the fact that we
can now import digital products, but
as a result of all this experimentation
the percentage of finished parts
industry is dramatically changing.
Their additive industries dramatically
changing, and we see this kind of
exponential curve going up the volume
of additive manufacturing fit a final
parts, and this doesn’t even account
for some of the really big examples
like the assets of acetabular cups, or
the fuel injection nozzle, examples we
mentioned earlier. Massive innovation
in terms of a going from a purely
prototyping industry, to one that’s a
really a production alternative. There’s
an estimation going on that says that
in five years we will be printing shoes
at home. A lot of smart people are
working on very specific applications
that makes sense to how to apply
additive manufacturing. It fits really
neatly into a growing exponential
curve.
The next step on the agenda is a
moredata-drivenagilemanufacturing
environment, an estimate added the
additive manufacturing landscape wall
will run and lead. Andre then mentions
Minecraft, and says they reckon it as
the biggest 3D design tool in the
world, because you can export directly
the 3d images directly from there into
3d prints. So if you have kids and are
playing with those tools, and you’re
getting upset about how much time
they are playing on it, there’s a way
for them to engage with a 3d reality
and make those physical. What’s
important here is that amazing ease
of transition we’re going from a
digital file which we can now design
in an augmented reality space, to a
physical product in the drop of a hat.
The process, every part of the value
chain is hard right now. To get a file
from ideation to production you need
to go through many steps, dozens
of manual steps to get the part into
production. Andre walks about one
how of his clients, that’s a major sports

manufacturer, wastes 15 to 35 minutes
per design being printed, and that’s
completely unsustainable if you want
to go into a production environment.
The reality is that transformation that
you see in Minecraft still isn’t as simple
as it could be, and the importance
of combining those parts becomes
evident.
Andre then goes on explaining some
of the converging technologies that
he thinks are running into the additive
manufacturing sector, for example
sensing (Google Tanger project, 3D
additive and subtractive machining in
the same machine
Combining those four different
trends and you have a very cheap
sensors detecting whether a part
has broken ten years after it was
produced, you take that data into the
cloud and you use machine learning
to identify why it was broken, you take
that data and push it into a generative
design tool that and redesigns the
tool, including the microstructures
to give more strength to the part, and
finally pushes that whole thing into a
“factory in a box”. We can combine
the full production system in a much
better way than we could in any
previous manufacturing time. What’s
important is that we are switching
between a control loop that was just
in the machine, to one that is across
the entire value chain, from the IOT
space into the design space. Andre
reinforces there’s a lot of work for us
to do, and as we’re doing that tend to
realize that it’s not only our engineers
that will be affected. If we look at the
entire production landscape, we’re
integrating this whole thing to make a
production much more efficient, and
of course is going to be impacting
absolutely every part of every
organization.
We are beginning to realize that
the layers of value are the startups
that are operating in the space of
specializing, Imax does the same
for the gaming industry and allows
you to print objects right out of your
computer game. Andre’s realization
was that actually because of the
integrated nature of additive we are
a sandbox; we are a digital lightning
rod for what additive or what the
digital manufacturing landscape
might become. It’s important because
manufacturers need to become
more agile. Li & Fong recently, as you
know, met massive trading house
between Asia, the US and Europe but
they only lost five percent of their
sensinginthephone;inoneyearwewill
be generating more 3d content than
the previous 10), or design as another
example of technologies changing
radically, from one where the human
designs where the human issues
the constraints and designs based
on those constraints, to generative
design tools coming into the market
that are going to make additive
manufacturing even more exciting.
Another example Andre gives is about
architected materials: materials
that aren’t driven by chemistry but
they’re driven by design. You can
influence of microstructures and
have a part that has completely
converse characteristics from what
you used to imagine. Or even hybrid
manufacturing, Andre talks about a
“factory in a box” where you have

production because they were able to
switch between different production
facilities very quickly. Toyota, who’s
East Coast operations were washed
out with a tsunami, wasn’t able to
adjust so quickly and lost the crown
of the most car sold. There are many
other ways in which manufactures
aren’t yet agile enough, and Andre
thinks this is exactly where this digital
thread and the coalition of additive
manufacturing with other digital
manufacturing technologies comes
in. We’ve gone from an environment
that is a multi-step process to one
that in certain segments is already
fully digital integrated and allows us
to explore what the limits of digital
manufacturing or digitally integrated
manufacturing really look like, that’s
why additives important not only as
a manufacturing technology but as
a sandbox for digital manufacturing
environments as a whole.
***
VIDEO DE LA CHARLA
watch?v=bD9w7DdYhF0
ARTÍCULOS
Andre Wegner 3d printing will
change 20% of manufacturing
watch?v=zW1vv8gwX5M
How 3D Printing is killing
manufacturing
http://www.biznews.com/
innovation/2015/05/28/andre-
wegner-3d-printing-meets-
formula-1/
HERRAMIENTAS
http://www.3dsystems.com/
https://glowforge.com/
http://www.stratasys.com/

THE BIG SHIFT: THEN,
NOW AND TOMORROW
John Hagel. Co-Chairman, Deloitte’s Center for the Edge.
Our global economy is rapidly
shifting to a new set of rules, and
industries are being fundamentally
reshaped. Few arenas are as affected
as manufacturing, which is re-
inventing everything from the ways
that products are envisioned, to the
ways they are delivered. What does
this Big Shift mean for manufacturing
in the future?
John says his speech will focus on
some of the business implications of
all exponential technologies. “Where
is the money in all of this?” he says.
When we talk about exponential
manufacturing it implies there are
some boundaries there that are
important and relevant, and at one
level we are, but another level one
of the challenges and opportunities
of this exponential world is all those
boundaries that were so familiar with
are blurring, and we need to think
beyond the boundaries.
In that context it was mentioned
that John has been doing work at the
center for the edge about what they
call the big shift, which is a view about
how the business world on a global
basis is transforming over a period
of decades. His belief is that this big
shift actually isn’t out in the future,
it’s not even today, it’s been going on
for at least 50 years. The big shift is
going to be profoundly disruptive to
all businesses, all businesses will have
to change in some pretty significant
ways, not just manufacturing.
One of those ways is recaptured
around the notion of push to pull.
Traditional businesses that have been
built up and been very successful to
date, have been built around a model
of push as a resource mobilization. The
key in push models is that you develop
a forecaster prediction of demand, and
then you push all the relevant people
and resources into the right place, at
the right time, to meet that demand.
Hugely efficient way of organizing and
mobilizing resources, if those forecasts
and predictions are accurate. In an
increasingly uncertain world, in an
increasingly exponential world, their
belief is that the companies that will
succeed in the future are those that
master scalable pull platforms.
When we talk about scalable
pull platforms, we’re talking about
platforms that involve tens of
thousands, hundreds of thousands,
and an increasing number of cases
millions of participants that can be
drawn out, pulled out, when needed
and where needed as needed. A very
different approach to mobilizing and
organizing resources, and requires
significant changes in all our business
practices.
Based on John’s research, the
leading edge companies in terms
of scalable pull platforms are not in
the United States, or Western Europe,
they’re actually in China and India.
There are companies that area
doing some very interesting things
around scalable pull platforms, in
industries as diverse as apparel,
motorcycles, agricultural products,
financial services.
John then talks about a chinese
company called Li & Fung. They are
in the clothing apparel Industry,
their customers are the brand apparel
designers that we all know and love
such as Calvin Klein and Taylor. They
JOHN HAGEL
co-chairman for
Deloitte LLP’s Center
for the Edge with
nearly 30 years
of experience as
a management
consultant, author,
speaker, and
entrepreneur.
He has served as senior
vice president of strategy
at Atari, Inc., and is the
founder of two Silicon
Valley startups. Author of
“The Power of Pull,” “Net
Gain,” “Net Worth,” “Out
of the Box” and “The Only
Sustainable Edge,” John
holds a B.A. from Wesleyan
University, a B.Phil from
Oxford University and a
J.D. and MBA from Harvard
University.

organize all the activities required,
from sourcing of raw materials
through all the stages of production,
all the logistics, to deliver to whatever
retail distribution center you specify
anywhere in the world. The really
interesting thing about Li & Fung is that
they do none of that themselves. They
operate through a global ecosystem
network of over 15,000 business
partners who do all that activity. Li
& Fung is the orchestrator of all that
activity but they don’t do the activity,
they have created scalable global pull
platform involving 15,000 partners
at a time. When Western companies
are steadily shrinking the number of
partners in their global supply chains
in the name of efficiency, Li & Fung
is adding more partners every day,
they’re expanding.
We’re in the early stages of a big
shift that is going to be profoundly
disruptive, and one of the key
questions that we would put on the
table is: Where should I position
myself in this big shift, in this new
global business landscape? There’s a
debate that’s been going on in Silicon
Valley for decades, and it has two
sides that are very passionate about
their beliefs. There’s one side of the
debate which argues that the impact
of all this digital technology is to
fragment everything, we’re all going
to become free agents, independent
contractors will loosely affiliate when
we need to around specific projects,
but basically companies are dinosaurs,
we’re going to fragment down to
the individual. The gig economy to
the max. There’s another side with
equal passion and conviction that
argues actually because of network
effects, digital technology is creating
a winner-take-all economy, where
there will be a very few global entities
highly concentrated that will capture
the vast bulk of the economic wealth
and everybody else is going to be
marginalized.
John’s team came up with the
answer: both the right. It just depends
on which part of the economy you’re
talking about. Their belief is there will
be fragmentation in certain parts
of the economy, and there will be
concentration consolidation in other
parts of the economy.
If they’re right about that, if you
are a large company today or have
aspirations to be a very large company,
you sure would like to be positioned
in the parts of the business landscape
that are going to concentrate and
consolidate, because if you’re in the
fragmenting part of the landscape life
is going to get harder and harder for
you as a large company.
Fragmentation is going to
occur largely. Product innovation/
commercialization businesses
coming up with creative new
products, getting them into market
quickly and accelerating the adoption
of those products. A variety of forces
that we see driving this, one force
is the notion that the means of

production are becoming more and
more accessible, in part because of
these technologies used to be that
if you were going to create a music
record, you needed to go into an
extraordinary expensive studio to
produce that record. Now you can
do it in your garage with equipment
that’s affordable by virtually anyone,
so the means of production are
becoming more accessible, and if
they’re not affordable, they’re available
increasingly on a rental basis. I don’t
need to have a chip facility; I can rent
capacity in somebody else’s facility if I
got an interesting chip design.
On the other side you have
platforms that are emerging
everything, from funding platforms to
talent platforms, to market platforms,
that can help provide a small
business with access to whatever it
needs to create and commercialize
that product. In digital media, from
music to video to software, there is
increasingly fragmentation of product
businesses, because more and more
people can participate at much smaller
scale.
John’s belief is there are certain
variables that you would look to
to assess the vulnerability and
fragmentation, part of it has to do
with regulation, part of it has to do with
product complexity, size and weight,
and issues around just functionality
of the product that can be digitized.
How much of the product today
that’s physical can be digitized and
delivered in digital form?
The concentration and
consolidation will occur in a different
part of the economy, according to
John. In several areas they’re already
seeing significant concentration and
consolidation in infrastructure service.
There’s a second part of the economy
that they believe are concentrating
and it has to do with aggregation
platforms. Aggregating resources
that are value to a lot of participants
and making those more readily

The Future of Manufacturing 2016

The Future of Manufacturing 2016

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The Future of Manufacturing 2016