The On-Demand Manufacturing Revolution
Dale Dougherty, Editor & Publisher, Make, O’Reilly Media, Inc.
John Hagel
Andrew Huang, Vice President Hardware, Chumby Industries
Brian Warshawsky, VP of Operations, Potenco, Inc.
– Personal Production — OLPC / Potenco
– Chumby – contract manufacture
From Manufacturing to The Attention Economy
Seth Goldstein, Co-founder, attentionsoft
Jacob DeHart, skinnyCorp
Jeff Jonas, Distinguished Engineer and Chief Scientist, IBM Entity Analytics
Jeffrey Kalmikoff, Chief Creative Officer, skinnyCorp (Chicago)
http://www.amazon.com/Only-Sustainable-Edge-Productive-Specialization/dp/1591397200
Tung Ching – 32m people – motorcycle centre – modularised japanese designs – modularaised design processes -
Manufacturing and supply chain integration e.g. shipping kit cars to local mechanics for maufacturing and sale
Important – Standardise Interface definition – downside difficult to move products in and out
HOWTO Protect IP – rapid iterations
Modular / Loosely Coupled Architectures – How to get large amounts of businesses and networks working together
Convert ind rev decreasing returns to increasing returns
skinnycorp.com
threadless.com
threadlesskids.com
nakedandangry.com
voting dynamic to decide on what products to sell – shortcuts R&D
never made a product they didn’t sell out of.
Attention Trust
Looking at peoples tastes through their clicks
atten.tv – one persons attention into anothers clickstream
myspace vs web 2.0 – who they like to see their identify strangers vs friends
Jeff Jonas – http://jeffjonas.typepad.com/
Security in Vegas
Nora – Non obvious relationship awareness
Enterprise Amnesia
need to figuring out relationships with things that are not linked at the moment
Push information as it arises – queries are stored in the same table space as data – analytics on data as it streams in – trying to boil the ocean – have to boil water as it enters the system
how to find an identity that has been created not stolen – look at the “thickness” of peoples identities
dataset grew to 700 million and duplicates started to glue and decrease the number down to manageable numbers – dirty data becomes an advantage e. learn that o’connor = oconnor = oconner = o’conner etc
data tipping points – hit critical mass and new behaviours emerges
nora for orgs to share their perceptions of data (e.g. people data) across orgs one way flow pig -> grinder -> sausage cannot revert
data (people) paying attention to data (people)
SideNote: http://iconfactory.com/software/twitterrific
Side Note: irc – #etech on freenode
Ain’t Dead Yet: Skyrider and the Next Gen P2P Economy
Edward Kozel, Edward Kozel, President and CEO, Skyrider
p2p reorganising the way we do things today
entertainment ind is as much a social experience as it is a content delivery exprience
perhaps p2p will no longer be anonymous – (isn’t there a firefox plugin that does this?)
p2p is about the edge of the network – back to seth re individual having the best record of all their transactions, everyone else gets a filtered view
no apps no longer require that we just go vertical
recently purchased yahoo shares….. benefits of no 1 and no 2 are fundamental yahoo is a strong number 2….. interesting…. they have put a lot of effort in the infrastructure and are commited to making search work fr them in the long run.
long term consolidation in search – p2p will rip it apart and open it again ( next year…. )
Peter Rip … is Web 2.0 over …. we’ll know its over when its owned by just a few big companies, then its time for the next thing
Mobile phones are an xciing new frontier…. could recreate youtube n a p2p platform in less cost.
Disrutong ecomoics of how we do things today… p2p leverages all the storage and processing power out there to kick the cenralised platforms asses
data is spread out, the beauty is in the shape of the network and how it organises itself … isps have an opp to ngage directly in user activity (by brokering)…
After Lunch:
Energy Innovation
Allison Randal, President, The Perl Foundation
Alec Proudfoot
Notes: Forsyth Group – Google boys – energy google uses – science foo camp – energy -
O’Reilly Energy Conference – 3 Tracks.
Lots of power needed etc etc….
Carrier hotels
Google needs lots power…. yawn…
move cooling on chips … mims tech
virtualisation..
the more i hear about energy the more i like p2p… distributed cooling!
DC distribution is a good option…. Tesla was right.
popularity of service can be related to power usage…..?
S1 filing … streaming video from data centre
Metaweb: The Semantic Web Meets Web 2.0
Robert Cook, Executive Vice President of Product Development and Co-Founder, Metaweb Technologies, Inc.
Esther Dyson, Editor at Large, CNET Networks
Metaweb = database = universal
realtime query returns
IT never used to be realtime??
topic = key to MW >> people, place, thing or idea
freebase – first MW app – open database
robert@metaweb.com for access to freebase.com alpha
structured wiki style database
chefmoz / imdb/ wikipedia/ musicbrainz
Web 2.0 and Wall Street
Peter Bloom, Managing Director, General Atlantic LLC
William H. Janeway, Vice Chairman, Warburg Pincus
9000ms to trade stocks 2 years ago, 30ms is now avg
new direct mkt speed = 1ms — no latency
Mike Bloomberg – didnt like democratising trade stock speeds
trans vs info efficiency – small vol high commission in
rip off 0.02 commision per share
3rd largest broker trades a billion shares this month … larger than morgan stanley etc
hedge funds – 14 families
liquidnet
share volume sale size has declined to hide activity – avg below 400 shares
seth goldstein – 2value of securitised attention”
price discovery of adwords – difficult as only one price source
**why smart people make big business mitakes** – highly rated
nobel research showing predictable behavours in bad decisions in investing e.g. double when in trouble
Behavioural Finance – good trader wants to buy euros >> hand off to the market. weak trader does same >> broker holds onto trans cos they know he’ll lose
give money to people to spend and give them cut of profits
sensors and actuators
web 2.0 is about efficient networks
no latency
can be a problem e.g. no “buffer stocks” … don’t have time to see if you have made a mistake
automated stock mkt system that crashed the mkt in 87 …. controls put in place to stop trading on a serious drop …. gives very long latency .. time to look and see what the problem is
valueinvestorsclub.com… collective curation
Backing Up Instinct with the Numbers
Bill Tancer, General Manager, Global Research, Hitwise
glacier bay toilet corection factor — google
stacy keibler correction factor
google trends… poor mans version of hitwise
claritas prizm segment 7 (money and brains) and 4 (young digerati)…. predict next hot sites … imeem wikimedia commons veoh metacafe
why is the sky blue / why did britney shave her head
Roger Magoulas, Director Market Research, O’Reilly Media, Inc.
rate of change in a signal rather than the value of it
“LLoyd: What Happened” – Recommended Book
progamming language index – add jobs and books data to derive mkt shares / dominance in the mkt.
i.e. add all variables for items to get idea of spread of mkt share
participatory analysis: swivel and many eyes
inkling
stack real time activity
stamen visualisations
exploratorium / cabspotting.org
spore flash hingy – genetic algorithms
CIBER – To be inspired by how and animal works — RHEX
stickybot