4. Moore’s Law — A Recurring Catalyst
Source: Ray Kurzweil (each dot is a computing machine)
5. Why does technology accelerate?
“All technologies are combinations of technologies that already exist.” —
• Combinatorial Explosion
• Creates Economy
— “Science quickly became the greatest tool
for making new things the world has ever
seen. Science was in fact a superior
method for a culture to learn.”
“Throughout history, the engine of human progress has been the
meeting and mating of ideas to make new ideas. The human race
will prosper mightily in the years ahead, because ideas are having
sex with each other as never before.”
• Urbanization
• Interdisciplinary Disruption
• Globalization
—
12. Eve Bio: a possible path to ubiquitous sequencing
Sources: “DNA sequencing via motion”, Stanford U. , US Pat No: 7,556,922, Ecoli RNAP data and Optical trap system. W J Greenleaf, S M Block Science
2006;313:801-801, T7-RNAP in Magnetic Trap: SUNY and UMDNJ: McAllister lab: Richard T. Pomerantz et al., Nano Lett., Vol 5, No 9,2005.
13. Synthetic Biology: Gen9 Gene Printer
Chip2Gene
• Parallel Chip synthesis
• Pooled Assembly
• Automated QC
• Picoliter scale
• Mut-S Error
Correction
• Sequence
verified
• 250,000 at once
Oligo
Synthesis
Gene
Assembly
Quality
Control
14. What to build?
GenBank Release 194
260,000 Organisms
190 Gb (billion base pairs)
Doubling every 1.5 years
Human Drug Targets (Proteins)
Enzyme Homologs
1.5 Gb
150 Mb
Polyketides (Small Molecules)
200 Mb
16. GMOs for Food, Chemicals, and maybe Fuels
“To support humanity’s needs,
we will have to grow more crops
in the next 50 years
than in the past 10,000 years combined.”
Chris Keely, Monsanto
AgraCast
18. Building Complex Systems
• Nanotech
• Synthetic Biology
• Computer Science
• Innovative Organizations
…whether to design or evolve?
19. The Problem with Evolution
• Subsystem Inscrutability
- Black box defined by its interfaces
- No “reverse evolution”
• No simple shortcuts across the iterations
- Simulation ~ Reality
- Beauty from irreducibility
• Locus of Learning is Process, not Product
• Robust, within co-evolutionary islands
22. Google’s First Quantum Computer
“We actually think
quantum machine
learning may provide
the most creative
problem-solving
process under the
known laws of
physics.” - Google Blog
23. Rose’s Law
1,000
100
Number of Qubits
10,000
512q Vesuvius 4
Faster than the universe
128q Rainier 4
Faster than all computers
Competitive Performance with
Classic Computers
28q Leda
16q Europa II
10
FOR DISCRETE
OPTIMIZATION
PROBLEMS
4q Calypso
1
2002
2006
2010
2014
2018
“Quantum computers have the potential to solve problems that would take a classical
computer longer than the age of the universe.” — Professor David Deutsch, Oxford
24. Beyond Engineering
Danny Hillis, The Pattern on the Stone
“The greatest achievement of our technology
may well be the creation of tools that allow
us to go beyond engineering –
that allow us to create more than we can
understand.”
25. Summary
Efficiency
Accelerating Technological Change
- Interdisciplinary Renaissance
- IT innervates $T markets
- More Black Swans
- Perpetual driver of disruption
Virtuous cycle for entrepreneurs
a great time for the new
27. Iterative Algorithms & Evolved Systems
• Consider:
- Cellular automata
- Genetic programming
- Analog Circuits & Antennae
- Danny Hillis: Sort Algorithms
- Neural networks
- Quantum computers
- Wisdom of Crowds
28. The Problem with Evolution
• Subsystem Inscrutability
- Black box defined by its interfaces
- No “reverse evolution”
- Tweak the process not the product
• No simple shortcuts across the iterations
- Simulation ~ Reality
- Beauty from irreducibility
29. The tradition of design…
Design
• Simple Problems
• Control
• Brittle
• Subsystem Clarity
- Portable, Modular
• Top Down
- Inheritance of Scale
30. Dichotomy
Design
• Simple Problems
Evolution
• Complex
- Transcendence proof
• Control
• Brittle
• Out of Control
• Robust, Resilient, Adaptive
- Co-evolutionary islands
• Subsystem Clarity
• Inscrutable subsystems
- Portable, Modular
• Top Down
- Inheritance of Scale
• Bottom Up
- Hierarchical subsumption
- Layers of abstraction
- Path dependence
32. AI Implications
• Cut & Paste Portability?
• Locus of learning: Process, not Product
- Would we bother to reverse engineer?
- No hard take off?
• Co-evolutionary islands
- accustomed environment (differential immunity)
• Path dependence
- algorithm survival
- AI = Alien Intelligence defined by sensory I/O