machine intelligence to free human intelligence: how automation helps you win
TRANSCRIPT
Machine intelligence to free human intelligence: How automation helps you win
Roger Chen @rgrchen [email protected] O’Reilly Solid 2015 June 25, 2015
There’s been a lot of excitement about robotics & AI recently
“the development of full artificial intelligence could spell the end of the human race.”
“I think it’s a distraction from the conversation about…serious issues,”
"With artificial intelligence, we are summoning the demon"
Contrary to what some would have you believe…
…robot AIs are not going to end humanity anytime soon
So don’t be awkward about it
And get to know the machines that can help you
What’s going on?
How did this happen?
What’s new this time around?
Rules of engagement for automation
So what’s all the fuss about? Robots aren’t new…
…but these ones are
Big companies are innovating too
Source: BCG
Robotics is accelerating
0
50
100
150
200
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2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014
Indu
stria
l rob
ots
(000
s)Global industrial robot sales
Globally
South Korea
Japan
Germany
US
China
Industrial robots operating by region
Industrial robots per 10,000 manufacturing employees
30
437
323
282
152
307K
237K
182K
176K
175K
How did this happen?
Smartphones
How did this happen? Smartphones
Sensors
Novel, cheaper sensors
How did this happen? Smartphones
Sensors
Actuators
Actuator & servo innovation
¡ Compliance (safety)
¡ Cost
¡ Performance
Series elastic actuator (1993)
Further actuator innovation (1993 – …)
First low-cost robotics startups (Baxter, 2008)
New startups pushing envelope (Modbot, 2015)
How did this happen? Smartphones
Sensors
Actuators
Software
Open source software: Robot Operating System (ROS)
¡ Collaboration
¡ Standardization
¡ Lowering technical barriers ¡ “From 20 man-years to 18 months”
ROS proliferating in technical world
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600
800
1000
1200
1400
1600
1800
Cita
tions
Total citations over time
0
10000
20000
30000
40000
50000
60000
Jan-0
7
Nov-07
Sep-08
Jul-0
9
May-10
Mar-11
Jan-1
2
Nov-12
Sep-13
Jul-1
4
IPs
Unique IPs downloading packages
Switchyard (Feb 2007)
ROS at Willow Garage (Nov 2007)
ROS at ICRA (May 2009)
ROS 0.4 release (Feb 2009)
ROS being put to use
ROS global
How did this happen? Smartphones
Sensors
Actuators
Software
Market
Consumers
Online retail sales $262B (US, 2012) 10% CAGR
Logistics and transportation Total spending
$1.33 trillion (US, 2013) 8.5% of US GDP
Customers (brands) Want more for less to satisfy consumer demand
Competitors Are undercutting one another on price
Faster Xiaomi $12B sales 135% ñ
Cheaper Personalized
Intense market forces
Workforce 600K unfilled mfg jobs 25% turnover in MH&L
What’s new this time around?
What’s new this time around?
It’s not just hardware
Rise of data and machine learning
¡ Machine learning algorithms (deep learning)
¡ Explosion of training data
¡ Hardware (GPUs)
¡ Interest and resources
Deep learning
Explosion in training data
Perception automation
GPUs
What’s new this time around?
Connectivity
Connect, measure, control
DevOps in the physical world
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Machine learning
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Deploy
What’s new this time around?
Flexible automation
Flexible
No days off! Keep working!
Pick items for shipping
Pack manufactured goods
Clean Roger’s car
Do some research
Transport some boxes
Why flexible automation matters
ROI ~ (ResultsA + ResultsB + ResultsC)/($A + $B + $C)
Project B
Project A
Achieve ROI across multiple deployments
Project C
Machine’s work capacity
Fixed to flexible to programmable
Production volume
Low Medium High
Va
riety
High
Medium
Low
Programmable
Flexible
Fixed
Too hard
Poor ROI
What’s new this time around?
Cost and compliance
Lower cost and compliance open up new applications
$25K $34K
Fetch Robotics
Logistics
Warehousing
Material handling
Transportation
Manufacturing
Plethora Labs Manufacturing
Emerald Cloud Lab Life science lab robotics
Riffyn R&D data automation
Design Measure Improve
Make it reproducible Stack it
Build protocols like Legos
Automate data acquisi=on
Automate error checking & root cause analysis
Share and version like Git
Collaborate
Riffyn
Rules of engagement for automation
It has to work
2+2=3?!
ROI “If it doesn’t make dollars, it doesn’t make sense” ¡ Cost savings
¡ Productivity
¡ Quality
¡ Turnaround
¡ Scalability
¡ Reproducibility
¡ New opportunities
¡ Machines for problem reduction, not the entire solution
Human + machine
Machine • Perfect memory • Complex statistical
analysis • Repeatability • Endurance
Human • Intuition • Creativity • Inference • Abstraction
But this matters!
Human + machine + process
“Weak human + machine + better process was superior to a strong computer alone and, more remarkably, superior to a strong human + machine + inferior process.”
-Garry Kasparov, Chess Grandmaster The Chess Master and the Computer
Everyone should read this!
Use machines, intelligently
Machine’s work capacity
ROI ~ Work/$ ROI ~ Results/$
Garbage work
Useful work
¡ Garbage in, garbage out
¡ Process matters – work smart, not just hard
¡ What problem are you really solving?
¡ If you struggle to fill capacity, automation may not be right for you
Challenges
¡ Technology ¡ Perception, deployment, programming
¡ Implementation ¡ Safety, security, cultural acceptance
¡ Society ¡ Impact on labor and economy
¡ Machines are reinventing work…
What does the future of work look like?
“There’s plenty of room at the bottom.”
“There’s plenty of room at the bottom.”
There’s also plenty of room at the top.
Thanks! Roger Chen @rgrchen [email protected]