Genesis Machines

Martyn Amos

• Publisher: Atlantic Books
• Year: 2014
• ISBN:
  9781782394914
• Topic: Informatik
• Subtopic: Informatik Allgemein

Silicon chips are out. Today's scientists are using real, wet, squishy, living biology to build the next generation of computers. Cells, gels and DNA strands are the 'wetware' of the twenty-first century. Much smaller and more intelligent, these organic computers open up revolutionary possibilities.

Tracing the history of computing and revealing a brave new world to come, Genesis Machines describes how this new technology will change the way we think not just about computers - but about life itself

/ Contents

Acknowledgements

Prologue

Introduction

1The Logic of Life

2Birth of the Machines

3There’s Plenty of Room at the Bottom

4The TT–100

5The Gold Rush

6Flying Fish and Feynman

7Scrap-heap Challenge

Epilogue

Notes

Index

/ Acknowledgements

First thanks must go to my publisher, Toby Mundy, who saw the first seeds of a book in my entry to the Wellcome Trust prize. Without Toby’s enthusiastic support, constant encouragement and gentle marshalling of the project, this book would never have been written. Thank you Toby, for the opportunity. I have benefited greatly from the input of my two editors; Alice Hunt helped me considerably in the early stages of the project, before she left Atlantic for academia, and Sarah Castleton provided marvellous moral support, editorial advice and a friendly ear at all times. I was privileged to have Annabel Huxley handle the early publicity for the book, which she did admirably. On that note, I also thank Jonathan Black at the Royal Institution, Stephen Emmott of Microsoft Research, Oliver Morton at Nature, Johnjoe McFadden, Caspar Hewett and John Burn for helping with book-related events.

My own work has benefited enormously from the support and collaboration of many gifted people. Foremost among these is Alan Gibbons, my Ph.D. supervisor at Warwick, and now a good friend and colleague. His unstinting support, friendship, guidance and willingness to go off-piste in search of new scientific terrain were the primary factors in my being in a position to write this book from the perspective of an insider. David Hodgson has also proved to be a wonderful collaborator, gently demolishing our more outlandish ideas while being open to new challenges, offering incisive biological analysis and supervising the laboratory work with impeccable precision. On that note, I must also thank Gerald Owenson and Steve Wilson, our indefatigable post-docs, who stuck with it long after most would have thrown in the towel.

I thank the following for conversations, collaborations, support and advice: Len Adleman, Charles Cantor, Dave Corne, Chris Cox, Paul Dunne, Brian Goodwin, Lila Kari, Laura Landweber, the late Ray Paton, Mike Poppleton, Somasundaram Ravindran, Grzegorz Rozenberg, Paul Sant, Dennis Shasha, Mike Simpson Ron Weiss and Eric Winfree.

I am immensely grateful to Alan Gibbons, Jim Shapiro and Paul Rothemund for reading and commenting on drafts of the manuscript; any errors that remain are, of course, my sole responsibility.

I thank my parents, for their unfailing love and support, but most of all I thank my wife, Justine Ashby, for everything.

/ Prologue

Stanford, California – June 2015

The shiny black slab stood on a low mound of grass, marble glinting in the hazy early morning sunlight. Inscribed in gold on one side of the sign were the initials ‘ABC’, and, beneath these, the full corporate name, ‘Advanced BioComputing’. The ABC labs and administrative offices were housed in a low, U-shaped white structure surrounding a paved courtyard, where early starters congregated to drink coffee and discuss science.¹

As bioengineer Neal Mendal pulled his car around the long, gentle sweep towards the main car park, his mind began to focus on the day’s work that awaited him. He worked in a second-floor Level 2 containment laboratory at the heart of the complex. Each lab was graded according to the relative risk of the organisms manipulated within it; laboratories with the highest 4-rating were used by specialist teams in oxygen suits working on microbes such as the deadly Ebola virus. Neal’s corporation, on the other hand, dealt with relatively benign creatures, and no such elaborate containment facilities were required. Even so, he still had to swipe his card through a reader at the main door and then pass a biometric retinal scan to gain entry to his laboratory.

As he sat in his office, waiting for his morning coffee to brew, Neal began to muse on the nature of his work. Back in the twentieth century, software engineers had implemented programs by meticulously designing components and implementing them in an unambiguous programming language. How different the job was now, Neal thought. The processing units that he wrote his programs for were not built from silicon, but from colonies of living cells. Neal’s job was to develop methods of phrasing instructions in the language of the cells, so that they could then go about their work. Instead of learning a traditional programming language, Neal had been trained in the language of biological differentiation and pattern formation. By manipulating the genetic material of cells and then altering their environment, Neal could coax colonies of cells into performing human-defined computations that ‘traditional’ computers struggled with. As the smell of fresh coffee filled his office, Neal found himself pondering, as he often did, the ‘magical’ process occurring within the organic modules. He could still barely imagine data being transformed and manipulated by living cells, however hard he tried. Somehow it was easier to imagine the much simpler operation of symbol processing in traditional computer systems.

Neal’s first task of the day was to replace the nutrients in the main processing unit. He flipped open the covers on a couple of nutrient cases, tossed the old cartridge in the trash and, rather more gently, dropped the replacement into place. He waited to see the clear liquid seep down the inclined surface, just in case the cartridge seal hadn’t punctured properly. The organic modules were far too valuable to risk letting them run dry.

As Neal waited for the nutrient broth to fill the processor case, he wandered around his lab, noting the usual mix of smells. He had always been told that the organic computing modules were sealed units, but nevertheless they always seemed to exude some low-level odours that gave a unique sensory profile any modern-day system administrator would recognise. In any case, the chemicals were harmless and at low concentrations, posing no threat to the human staff. Neal was more concerned that contaminants might inadvertently enter the organic computing modules and affect their proper functioning. With relief, he noted that everything appeared to be normal, as each module was exhibiting the typical patterns of fluorescent green scintillations with which he had become so familiar. He could now judge by eye when a module had been contaminated or had developed some aberrant behaviour. In any case, the modules were inherently self-healing in nature, and would adapt to any minor problems by reconfiguring themselves. Neal chuckled to himself as he recalled that, decades ago, people would complain that their computers ‘had a life of their own’. His computer was different. It was alive.

/ Introduction

In 1985, Greg Bear published Blood Music,² a novel that established its author’s reputation and led him to being heralded as ‘the next Arthur C. Clarke’. The science-fiction magazine Locus lauded it as ‘A Childhood’s End for the 1980s, replacing aliens and mysterious evolution with the effects of genetic engineering run wild.’ In the book, a brilliant microbiologist works to develop biochips, using DNA as the next ‘quantum leap’ in computer technology. As his work progresses, Vergil I. Ulam³ develops intelligent cellular colonies that appear to exhibit intelligence way beyond that of ‘higher’ creatures. In one memorable section, Ulam observes groups of trained cells running through a complex miniature glass maze to earn nutritional rewards, just like laboratory rats scurrying for food.

I was sent a copy of Blood Music in 1999 by a thoughtful delegate who had recently attended a talk I’d delivered to a computer conference in Madrid. This was not simply a random act of generosity by a stranger who had just happened to enjoy a presentation of mine. The particular choice of book was motivated precisely by the content of my talk, in which I had described ongoing work that, only a decade or so previously, had been mere fantasy, imagined only in the pages of a science-fiction novel.

My talk was part of a ‘Frontiers of Computing’ event organized by the Unisys Users’ Association, during which several speakers were invited to present their vision of the future of computers in the years and decades to come. Nicholas Negroponte, the founder of MIT’s Media Lab, spoke about Being Digital,⁴ while Wim van Dam from Oxford University gave a presentation on quantum computing, the notion that quantum states of atoms could somehow be harnessed to build machines of almost unimaginable power.⁵ I was invited to speak about a growing research area that had existed in practice for just five years.

This book tells the story of a whole new connection between two ancient sciences: mathematics and biology. Just as physics dominated the second half of the twentieth century with the atomic bomb, the moon landing and the microchip, it’s becoming increasingly clear that the twenty-first century will be characterised and defined by advances in biology and its associated disciplines. Cloning, stem cells and genetic engineering have become the new hot topics of debate in newspapers and on the Web. New genome sequences are being produced at an astonishing rate, capturing the genetic essence of organisms as diverse as the orang-utan and the onion.⁶ This flood of sequence data is transforming biology from a lab-based discipline into a whole new information science. The pioneers at the forefront of this genomic unravelling speak of ‘networks’, ‘data mining’ and ‘modelling’, the language of computer science and mathematics. The sequencing of the human genome, one of the triumphs of the modern scientific age, was only made possible through the development of sophisticated mathematical algorithms to piece together countless DNA sequence fragments into a coherent whole. The growth of the Web has led to unprecedented levels of scientific collaboration, with researchers across the globe depositing gene sequences into communal databases in a distributed effort to understand the fundamental processes of life. These advances have been facilitated by mathematicians and computer scientists training their analytical armoury on the big biological questions facing us today.

However, simple biological organisms existed millions...