The Singularity is FarComputing Nature

Artificial Life, Virtual Worlds & Simulation

Bruce Damerfor the Singularity University

August 3, 2010

• I. The Birth of Computing(and the Von Neumann Bottleneck)

II. The Birth of Visual Computing and Virtual Worlds (still running through the Von Neumann Bottleneck)

III. State of the Art in Simulating Nature (Physics) for Space and Chemistry

IV. Computing Nature (?)

Discussion

III. Computing Nature (?)Can Von Neumann Do It?

Conventional vs Natural ComputationSystemic Computer model by Peter J. Bentley, UCL, Digital Biology Group

Conventional Natural Deterministic Stochastic Synchronous Asynchronous

Serial Parallel Heterostatic Homoestatic

Batch Continuous Brittle Robust

Fault intolerent Fault tolerant Human-reliant Autonomous

Limited Open-ended Centralised Distributed

Precise Approximate Isolated Embodied

Linear causality Circular causality

Table 1 Features of conventional vs Natural computation

Non-living natural world supports a massive number of parallel interactions but they are finite, bounded

Living natural world supports infinitely repeatable computations in a massively parallel fashion

E-coli, a massively parallel computing universeDavid S. Goodsell from The Machinery of Life

E-coli, a massively parallel computing universe

The complexity of Cytoplasm

A cube 100nm on the side contains roughly:- 450 proteins- 30 ribosomes- 340 tRNA molecules- several mRNA molecules- 30,000 small organic molecules (amino acids, nucleotides, sugars, ATP etc)- 50,000 ions- remaining 70% is water- all in continuous interaction

Nerve cells: two orders of magnitude more complex than e-coli

So can any kind of (Von Neumann) machine simulate a whole cell?

Definitely not

Low level approximations (overhead)

How about a lot of these? Perhaps… for the equivalent

of a small volume of aqueous chemicals, Anton: 1

microsecond per month

You need this…. to originate and evolve complex life (and civilization)

Penny Boston, CONTACT Conference 2009, NASA Ames

Question: What is the computing architecture and cost of simulating a single neuron at the

molecular dynamics level?

Answer: This is beyond the current and probably subsequent two or three

generations of supercomputers, even those dedicated to MD simulation.

Result: Even excluding the “non informational/maintenance” parts of the simulation of a neuron, the high fidelity modeling of a single neuron is still a substantial computing challenge.

Therefore concepts of a Singularity as derived from science fiction (Vinge) remain wholly in the realm of

science fiction.

So how to map this computer onto this one?

Perhaps……toil for a number of decades toward a most

minimal type of “Singularity”,an Artificial Origin of Life

The EvoGrid An “artificial origin of life” in cyberspace in this Century

Origins of Life: Archaean to Cambrian1997: Digital Burgess - quest for life’s algorithmic

origins in the “Cambrian Explosion”, Biota.org

Early exemplar: Karl Sims’ Evolving Virtual Creatures (1991-4)

“Soft” Artificial Life Through the Ages: field named in the 1980s, progress through the

1990s, 2000s

Evolving Virtual Creatures by Karl SimsInspired a generation of Soft Alife developers in the 1990s-2000s

Karl Sims: Evolving Virtual Creatures

Early exemplar: Karl Sims’ Evolving Virtual Creatures (1991-4)

State of the art of “Soft” Artificial Life

Roll tape!Enter the EvoGrid

Roll Tape!

EvoGrid The Movie

The EvoGrid: conceptually a large central artificial chemistry simulation operated upon by analysis clients

What is the ‘Secret Sauce’ of the EvoGrid?

Answer: Stochastic hill-climbing

algorithm utilizing analysis, feedback

and temporal backtracking

EvoGrid Engine

Roll tape!Odd Future Applications of EvoGrids

Roll Tape!

EvoGrid Asteroid Eaters

But how realistic is this?Enter “wet” artificial life

(not synthetic biology)

Creation of life “from scratch”(ie: not Craig Venter)

The Dawn of “Wet” ALife Protocells (Monnard, Rasmussen, Bedau et al)

Model for a minimal cell

Protocells must form on their own through successive “ratchets” of complexity

Ref Pierre-Alain Monnard, FLinT

Fundamental Living Technologies LaboratoryOdense, Denmark

University of Southern Denmark, Odense

Protocells from Chemical Soups

Origins of Life the “hard way””

Your chemical origins of life computing equipment

Micelle SimulationExploring Life’s Origins Project (Harvard)

Micelle Division

Radically new chemical life cycles

feeding

light (hv)

heating

containerdivision

informationreplication

metabolicconversion

addition of resources

Roll tape!FLinT Protocell Life Cycle (draft!)

Roll Tape!

Radically new chemical life cycles

Roll tape!But what does a Whole Cell look like?Harvard’s Inner Life of a Cell

Roll Tape!

Harvard’s Inner Life of a Cell

Will we create a digital or in vitro primordial soup any time soon?

Closing Thought

Resources and Acknowledgements & Discussion Project EvoGrid at: http://www.evogrid.orgProject Biota & Podcast at: http://www.biota.org DigitalSpace 3D simulations and all (open) source code at: http://www.digitalspace.com

We would also like to thank NASA and many others for funding support for this work. Other acknowledgements include: Dr. Richard Gordon at the University of Manitoba, Tom Barbalet, DM3D Studios, Peter Newman, Ryan Norkus, SMARTLab, Peter Bentley, University College London, FLiNT, Exploring Life’s Origins Project, Scientific American Frontiers, DigiBarn Computer Museum, The Shelby White and Leon Levy Archives Center, Institute for Advanced Study, Princeton, NJ, USA, and S. Gross.