IMHO, the people and organizations to forge relationships with are the ones that hunger to understand the use cases for these technological developments in order to visualize and collaborate on projects that can and will affect change in the world. I have included some detailed information about some of these organizations and the technology they bring to the table.

1. Wired
Business
Conference
overview
and
Final
Thoughts
By John Powers

2. Agenda
VISA Experience Highlights
Keynote
Nicholas Thompson / Wired
Organizations
Jigsaw (a Google company)
Google
Numeria
Google Brain
Amazon
Foster and Partners(Apple’s Mothership designer)
Visa
Crispr
Essential Products
Westworld Creators
© 2017 Princeton Identity, Inc.

3. VISA Sponsored Concept / entrance to the event
Focused on a future where currency is no longer required
1. Visitors to the space were provided with a VISA card upon entrance
2. From there all visitors were directed to surrender their card to an Installation specialist
3. The Installation specialist then discarded the card and “INSTALLED” an RFID tag on the visitor
4. Visitors could then make purchases by waving their hand near items they desired

4. Tech Infused Art was on display
Blooms are 3D printed sculptures designed to animate when
spun under a strobe light.
The bloom’s animation effect is achieved by progressive
rotations of the golden ration, phi, the same ratio that nature
employs to generate the spiral patterns we see in pinecones
and sunflowers. The rotational speed and strobe rate of the
bloom are synchronized so that one flash occurs every time
the bloom turns 137.5°(the angular version of phi)

5. Kickoff – Nicholas Thompson / Wired
5
Discussed the impact changehas on our society
“Wired is all about tracking change, not necessarily tech”
Discussed conversations about change
• ISIS recruitment
without social where would they be?
• AI
impact on middle class
• Pain v no pain
advances in medicine, would not feeling pain be a good thing
• Predictive analysis
ML’s impact on everything
• Consequences of scale
Apple, Facebook, Google large companies impacting the world
• Privacy v Security
Bit Coin vs the US Mint
• DNA v Science
What could go wrong
• Storytelling
argued that attention spans are actually growing
• Touch your Phone 3000 times a day
what will be the next “Phone”? what kind of change will that bring?

6. Yasmine Green / Jigsaw (a google company)
Fake News / set out to find the source of the mass of fake
news stories curated during the run up to the 2016
election.
Where did they come from? …and what was the motivation?
• Surprised to find no geopolitical goal associated with the source of the
major spike of fake stories found.
• Identified a small group of people that were essentially growth hacking
fake news pieces, capitalizing on a program that would reward web traffic
driven with US dollars.
Found teens in Macedonia rewriting popular fake US political news stories
to drive even more clicks to the targeted sites that would earn them $Cash$
for clicks.
Spoke at length on use of AI from ML to develop context to
speech tech to improve algorithms built to better
understand human communication
• AI used to provide suggestions for texting responses. I.E..if a person
drafted the following text, “You are an @#$&^#&”, the algorithm would
understand the context and pop up a suggestion or alternative response
prior to allowing you to hit the send button that might say, “Are you sure
you want to respond in this way?”
• Used this AI in a pilot within Google’s search platform where they
successfully identified 300k people who were querying ISIS in some
relevant way in order to deliver “redirect campaign” messaging where
positive life message ads were implemented to help these people make
potentially better life decisions.
Yasmin Green, Director, Research & Development,
Jigsaw in conversation with Issie Lapowsky, WIRED

7. Urs Holzle / Google employee #7
Early days discussion
“We needed to scale quickly to allow for fast search, it was not pretty, far from perfect”
We went from 11 machines in a room to multi site, distributed network created in house to meet the
growing needs of the customers. No resources or models existed as a reference regarding the direction
they were headed in datacenter infrastructure i.e., data speed, bandwidth and storage
7
Urs Hölzle, SVP, Technical Infrastructure, Google
in conversation with Marcus Wohlsen, WIRED

8. Urs Holzle / Google employee #7
8
Recent Problem example:
During development of their speech recognition for mobile
in 2010 they calculated the need to double their data
center infrastructure to achieve their speed goals. Even
though they are Google(lots of $$s on hand) this would be
impractical.
Instead they quickly found that in order to achieve this
goal they would again need to hyper focus on things the
felt strongest about (i.e., develop single purpose, fast drag
race car vs multi purpose fast commuter car) in order to
make speech recognition function the way they had
envisioned. Because they needed to move at such speed,
they realized they had to jettison some concepts that were
not required to support this immediate goal. By doing this
they ended up creating TQ/Tensiflow processing model.
Built a special purpose chip vs general purpose chip. This
solution achieved 50 times greater efficiency. This effort
yielded the need to increase their data center
infrastructure by only 2% vs doubling it.
Tensiflow processing unit – 11,000 trillion operations p sec

9. Richard Craib / Numerai
Determined that ML should be used in finance to do a transformation on the
financial data into new spaces.
“How far can you go with this?” …Go so far that the data has no resemblance to what it used to be
and it could then be transferred securely as well. This enables data scientists the ability to share
newly created predictive AI models to improve hedge fund performance
Went against traditional Hedge fund thinking regarding data (cannot share the data)…
Decided to tap into a larger set of data scientists to collaborate seeking the best way
to encrypt this data to enable building and sharing the of the best data sets.
Homo morphic encryption – cutting edge! using neural cryptography to use a neural net to do the
encryption for you.
One neural net is used to figure out the data while the other is used to obfuscate the data.
In 2009, Netfix proved that if you do open up and give people a data set you can make models that
are way better than working on them as a single entity.
Numerai is changing the entire [hedge fund] design because we have 2 orders of magnitude more
resources than the largest hedge fund. (19,000 AI Scientists collaborating)
Quants do what the models say using structured data sets.
In the future, AI can take on unstructured data sets in the future!...but not too soon
Offers cryonics under their health plan!
9
Data scientists are using the Ethereum block chain to
securely send newly modeled financial data sets to
Numerai to earn Bitcoin
Emphasis on sharing data to
improve end product
Click video to
learn more >

10. Lily Peng / Google Brain
Using Deep Learning to Diagnose Disease
Using AI to diagnose diabetic retinopathy by scanning
retina images from multiple systems to detect
irregularities found on the retina
Normally, the more information the better…
They found algorithm results were skewed by comparing
one set of retinas from another that were photographed
by different systems.
In this case, the AI still needed course correction.
Future: Seeking hardware that is easier to use by a wider
array of technicians to enable less expensive testing
allowing for greater access to the tests themselves.
10
Lily Peng, Product Manager, Google Brain
in conversation with Sarah Fallon, WIRED

11. David Limp / Amazon
Discussed the Future of Amazon
7-8 years ago decided to leverage ML to solve problems.
Asked internally: If you had access to infinite computing power what would/could you do?
Answer: Conversational Speech (ambient computing) like the Starship Enterprise from Star
Trek. Led to development of Alexa.
“Amazon is an AI company, ML is in every aspect of what we’re building.”
Future: develop more cognitive abilities in speech recognition to enable things like the
differentiation between short term memory and long term memory to provide greater
context. i.e., teaching AI to understand pronouns in the course of a conversation
“Conversational speech is not decades away! ...more like 5-10 years away”
Q: Since you[Amazon] are soo big how do you keep from being boring?
A: 1.)Being Nimble - Organizing on customer focus requires it
2.)Be willing to take risks
3.)Need to be an optimist. I.E., Amazon Phone – excited about the phone, it
bombed and they moved on. Fail fast and move on but not without taking the risk.
“I had an equal number of people line up outside my office
for the phone and Alexa projects telling me that they wouldn’t work”
11
David Limp, SVP, Devices, Amazon
in conversation with Nicholas Thompson,
WIRED

12. Lord Foster / Thames Bank OM
Designing for the Future
Create the idealized California from Jobs’ favorite
features of the bay area also drawing on inspiration
from Stanford and trips to London parks.
As with many Apple products, its shape would be
determined by its function
This would be a place where people were open to
each other and open to nature
What began as a clover became a circle through its
need to function as planned, balancing the need for a
place of intense concentration but you could also run
into many people to allow for brainstorming that
unearths innovation.
12
Lord Foster of Thames Bank
OM, Founder & Exec. Chairman, Foster & Partners
in conversation with Richard Dorment, WIRED

13. Jim McCarthy / Visa
The World after Cash
“Mobile has become the terminal”
IOT is exciting because it allows devices to make the purchase for you.
129 Billion transactions last year
Biometrics are a focus to make purchases
i.e., use biometric on mobile to pre order cash at a given ATM for
convenience, making access to cash easier.
Open Source Mindset / expose software to others to improve on
innovation
Looking for a path to get everywhere…
“Less change to behavior is the easiest path.”
13
Jim McCarthy, EVP, Innovation &
Strategic Partnerships, Visa
in conversation with Jason Tanz,
WIRED
< Click here
to see full
video

14. Jennifer Doudna / Crispr
From Super Crops to Designer Babies: Welcome
to the Age of CRISPR
Discovered how to edit gemomes (at low cost) in the early stages
allowing one to potentially impact the DNA structure prior to birth
making it possible to potentially delete a pattern baldness trait or
choose the color of a baby’s hair
• What impact will this have on evolution?
• Will scientists remove the feeling of pain from a
person (why would anyone want to do that?)
Future: How will the world regulate this tech?
A: Did not have answers, only suggestions along with
verbalizing the hope that a worldwide coalition would
come together to address the moral issues that come with
the proliferation of these new found capabilities.
14
Jennifer Doudna, Technology Co-
Inventor, CRISPR-Cas9 in
conversation with Robert Capps,
WIRED

15. Andy Rubin / Essential Products(former Googler)
Vision: What will be the next “phone” or
major innovation?
The mobile space has affected everything… What will the next
ecosystem be?
The big boys are using AI as a platform, ML and neural networks at
scale but Essential will be trenched in organizing IOT in the home.
Focus on IOT organization on the homefront (home
and car) bringing security and cameras with depth
sensors together to work with one appliance to
manage it all using an ambient OS.
Essential Home/touchscreen and LCD will combine
with voice to automate your home.
Future: need interoperability from large players to help
push innovation in security and automation forward.
15
Andy Rubin,
Founder CEO Essential
Products
First product is
a mobile
device

16. Westworld / Co-Creators & Executive Producers
How Storytelling creates the future
Tapped to recreate Westworld and wanted to stay true to the original
film but apply their understanding of AI to bring it to life.
Spoke about the possibility of conscious vs unconscious forms of AI and
how far out those concepts really are given all of the research they have
done to breathe new life into this story.
From Wired: For Nolan, the robots on his show represent more of an
allegory for human behavior than a cautionary tale. And Joy
sees Westworld, and sci-fi in general, as an opportunity to talk about
what humanity could or should do if things start to go wrong, especially
now that advancements in artificial intelligence technologies are
making things like androids seem far more plausible than before.
Storytelling, according to show co-creator Jonathan Nolan, serves an
evolutionary purpose, allowing us to try out different realities. With
sci-fi, because it’s so often forward-looking, “we’re inventing
cautionary tales for ourselves,” Nolan said to Wired’s Peter
Rubin.
Jonathan Nolan and Lisa Joy,
Husband and wife team speaking
with Peter Rubin, Wired

17. When will these advances take shape?

18. They are happening NOW!
I believe much of this technology is already shaping our daily lives as is the case with
Amazon’s Alexa.
I also believe that start ups and organizations of any scale (especially those with historical
market dominance) that embrace the benefits of these developments will be far better off
than those that do not (see Kodak).
These statements may seem obvious but there are many influential naysayers out there
that will push back on new concepts for their lack of understanding or because they
simply want to protect what they already have/know.

19. Final Thoughts…

20. IMHO, the people and organizations to forge relationships with are the ones that
hunger to understand the use cases for these technological developments in order to
visualize and collaborate on projects that can and will affect change in the world.
Fortunately for us all, this is happening at scale right now and I am
thrilled to be a part of an organization that happens to share this
vision with me!
If you happen to share my vision or wish to discuss any of the content further
feel free to add comments here or on LinkedIn or reach out directly to talk further.
Cheers!

21. Thank you