Spatial Computing, Synthetic Biology, and Emerging IP Challenges. Jacob Beal November, 2010

Transcription

1 Spatial Computing, Synthetic Biology, and Emerging IP Challenges Jacob Beal November, 2010

2 Spatial Computers Robot Swarms Reconfigurable Computing Biological Computing Cells during Morphogenesis Sensor Networks Modular Robotics

3 How can we program these? Desiderata for approaches: Simple, easy to understand code Robust to errors, adapt to changing environment Scalable to potentially vast numbers of devices Take advantage of spatial nature of problems One answer: continuous space programs!

4 Example: Mobile Streaming

5 Example: Mobile Streaming

6 Example: Mobile Streaming

7 Example: Mobile Streaming I want Alice to be able to listen in on this great conversation

8 Geometric Program: Channel Source Destination (cf. Butera)

9 Geometric Program: Channel Source Destination (cf. Butera)

10 Geometric Program: Channel Source Destination (cf. Butera)

11 Geometric Program: Channel Source Destination (cf. Butera)

12 Geometric Program: Channel Source Destination (cf. Butera)

13 Geometric Program: Channel Source Destination (cf. Butera)

14 Geometric Program: Channel Source Destination (cf. Butera)

15 Computing with fields source destination gradient gradient width distance + <= dilate

16 Computing with fields source destination gradient gradient width distance <= dilate

17 Amorphous Medium device neighborhood Continuous space & time Infinite number of devices See neighbors' past state Approximate with: Discrete network of devices Signals transmit state

18 Proto Global (def gradient (src)...) (def distance (src dst)...) (def dilate (src n) (<= (gradient src) n)) evaluation (def channel (src dst width) (let* ((d (distance src dst)) global to local compilation (gradient dst)) d))) (dilate trail width))) platform specificity & optimization device neighborhood discrete approximation Device Kernel Local Discrete (trail (<= (+ (gradient src) [Beal & Bachrach, '06]

19 Proto's Families of Primitives Pointwise Restriction restrict + Feedback 41 delay Neighborhood nbr any-hood

20 Why use continuous space? Scaling & Portability Robustness Composability 2000 devices 150 devices

21 Proto (def gradient (src)...) (def distance (src dst)...) (def dilate (src n) (<= (gradient src) n)) (def channel (src dst width) (let* ((d (distance src dst)) (trail (<= (+ (gradient src) (gradient dst)) d))) (dilate trail width))) Energy Management X X Swarm Robotics Device Kernel X Zome Energy Networks Synthetic Biology Morphogenetic Engineering

22 IP Challenges Many parts: free, protected, & commercializable? Documentation

23 IP Challenges Many parts: free, protected, & commercializable? GPL/libc CC:BY 3.0 Documentation Thank you, Creative Commons!

24 Proto (def gradient (src)...) (def distance (src dst)...) (def dilate (src n) (<= (gradient src) n)) (def channel (src dst width) (let* ((d (distance src dst)) (trail (<= (+ (gradient src) (gradient dst)) d))) (dilate trail width))) Energy Management X X Swarm Robotics Device Kernel X Zome Energy Networks Synthetic Biology Morphogenetic Engineering

25 Proto (def gradient (src)...) (def distance (src dst)...) (def dilate (src n) (<= (gradient src) n)) (def channel (src dst width) (let* ((d (distance src dst)) (trail (<= (+ (gradient src) (gradient dst)) d))) (dilate trail width))) Energy Management X X Swarm Robotics Device Kernel X Zome Energy Networks Synthetic Biology Morphogenetic Engineering

26 Computation via Transcription Network regulatory protein RNA RNA polymerase ribosome DNA promoter Decay Protein

27 Proto BioCompiler High-Level Language (def band-detector (signal lo hi) (and (> signal lo) (< signal hi))) Genetic Regulatory Network Compile Optimize (let ((v (diffuse (atc) ))) (green (band-detect v 0.2 1))) Assemble Simulate Living Cells w. Weiss

28 Band detect: code Proto Engineered Bacteria (def band-detector (signal lo hi) (and (> signal lo) (< signal hi))) (let ((v (diffuse (atc) ))) (green (band-detect v 0.2 1))) simpler, more reusable [Beal & Bachrach, '08] [Weiss '05]

29 Band detect: behavior Proto [Beal & Bachrach, '08] Engineered Bacteria [Weiss '05]

30 Motif-based Compilation Dataflow Network IPTG not green

31 Motif-based Compilation Dataflow Network IPTG not green IPTG LacI outputs arg0 outputs arg0 GFP outputs

32 Motif-based Compilation Dataflow Network IPTG not green IPTG A LacI outputs B arg0 outputs arg0 GFP outputs

33 Motif-based Compilation Dataflow Network IPTG not green IPTG A outputs LacI B arg0 outputs GFP outputs arg0 IPTG Genetic Regulatory Network LacI A B GFP

34 Classical Optimization can be Adapted Example: XOR circuit IPTG LacI E D K B G K J atc A TetR C L J F I H L GFP

35 Classical Optimization can be Adapted Example: XOR circuit IPTG K LacI G K L atc TetR J C L GFP J After optimization: ~50% improvement

36 End-to-End Toolchain Project

37 And on to larger organisms...

38 IP Challenges IP Types DNA sequences databases students biologists computer scientists industry software patents organisms CAD engineers Communities Regulators Many components; integration with vendors Full automation: no human interpretation

39 Summary Proto allows complex spatial computing problems to be solved with simple programs. Proto & other approaches beginning to link together to automate synthetic biology Major IP thunderclouds on the horizon...

40 Proto is available (or google MIT Proto ) Includes libraries, compiler, kernel, simulator, platforms, tutorial Licensed under GPL (w. libc-type exception)