Can we make software that comes to life?

Is evolution about to enter a new phase? Today, 300 biologists, computer scientists, physicists, mathematicians, philosophers and social scientists from around the world are gathering in Winchester. Their aim is to address one of the greatest challenges in modern science: how to create a genuine artificial life form.


Is evolution about to enter a new phase? Today, 300 biologists, computer scientists, physicists, mathematicians, philosophers and social scientists from around the world are gathering in Winchester. Their aim is to address one of the greatest challenges in modern science: how to create a genuine artificial life form.

Intelligent design: self-aware computers such as Pixar’s Wall-E
are surprisingly tricky to put together

The idea that life owes its existence to some “vital essence” or “animating spark” has long been discredited in scientific circles. Instead, it is believed that the first living thing emerged after a chemical reaction crossed the watershed that divides inanimate objects from the kind of self-replicating “organic” reactions that run our cells.

Researchers into artificial life, or “ALife”, take two basic approaches. In “wet” ALife, scientists either tinker with microbes and other forms of simple life, or try to cook up cocktails of chemicals in water (hence “wet”) that have the capacity to extract energy and raw materials from the environment, to grow and reproduce, and ultimately to evolve. Meanwhile, “in silico” ALifers use silicon chips to try to kindle the spark of life in the heart of a computer.

In the latter field, a celebrated experiment was carried out almost two decades ago by Dr Thomas Ray, at the University of Delaware. He created the first successful attempt at Darwinian evolution inside a computer, in which organisms – scraps of computer code – fought for memory (space) and processor power (energy) within a cordoned-off “nature reserve” inside the machine.

His evocative experiment was called “Tierra”, after the Spanish for “Earth”. Back in 1993, when I met him in Oxford, it seemed to be a vital tool in helping us understand why the world is seething with diversity, from rainforest to coral reef.

For evolution to occur, Dr Ray had to allow his programs to mutate. The “Tierran” programming language he devised was robust enough that it could often work after mutations. He also had natural selection: a program called the reaper killed off old and faulty software, enabling more successful organisms to monopolise resources.

On January 3 1990, he started with a program some 80 instructions long, Tierra’s equivalent of a single-celled sexless organism, analogous to the entities some believe paved the way towards life. The “creature” – a set of instructions that also formed its body – would identify the beginning and end of itself, calculate its size, copy itself into a free region of memory, and then divide.

Before long, Dr Ray saw a mutant. Slightly smaller in length, it was able to make more efficient use of the available resources, so its family grew in size until they exceeded the numbers of the original ancestor. Subsequent mutations needed even fewer instructions, so could carry out their tasks more quickly, grazing on more and more of the available computer space.

A creature appeared with about half the original number of instructions, too few to reproduce in the conventional way. Being a parasite, it was dependent on others to multiply. Tierra even went on to develop hyper-parasites – creatures which forced other parasites to help them multiply. “I got all this ecological diversity on the very first shot,” Dr Ray told me.

Other versions of computer evolution followed. Researchers thought that with more computer power, they could create more complex creatures – the richer the computer’s environment, the richer the ALife that could go forth and multiply.

But these virtual landscapes have turned out to be surprisingly barren. Prof Mark Bedau of Reed College in Portland, Oregon, will argue at this week’s meeting – the 11th International Conference on Artificial Life – that despite the promise that organisms could one day breed in a computer, such systems quickly run out of steam, as genetic possibilities are not open-ended but predefined. Unlike the real world, the outcome of computer evolution is built into its programming.

His conclusion? Although natural selection is necessary for life, something is missing in our understanding of how evolution produced complex creatures. By this, he doesn’t mean intelligent design – the claim that only God can light the blue touch paper of life – but some other concept. “I don’t know what it is, nor do I think anyone else does, contrary to the claims you hear asserted,” he says. But he believes ALife will be crucial in discovering the missing mechanism.

Dr Richard Watson of Southampton University, the co-organiser of the conference, echoes his concerns. “Although Darwin gave us an essential component for the evolution of complexity, it is not a sufficient theory,” he says. “There are other essential components that are missing.”

One of these may be “self-organisation”, which occurs when simpler units – molecules, microbes or creatures – work together using simple rules to create complex patterns and behaviour.

Heat up a saucer of oil and it will self-organise to form a honeycomb pattern, with adjacent “cells” forming as the oil turns by convection. In the correct conditions, water molecules will self-organise into beautiful six-sided snowflakes. Add together the correct chemicals in something called a BZ reaction, and one can create a “clock” that routinely changes colour.

At the Winchester conference, Prof Takashi Ikegami, from the University of Tokyo, will explain the ways that self-organisation operates among birds, to help them form flocks, and in robots, children, flies and cells, too. Another keynote speaker will be Prof Peter Schuster of the University of Vienna.

With the Nobel Laureate Manfred Eigen, he came up with the idea of the “hypercycle” – different components “feeding on each others’ waste” while maintaining an (often fragile) overall stability. This scheme was used to show how simple chemicals co-operated to create the first living things billions of years ago.

“Evolution on its own doesn’t look like it can make the creative leaps that have occurred in the history of life,” says Dr Seth Bullock, another of the conference’s organisers. “It’s a great process for refining, tinkering, and so on. But self-organisation is the process that is needed alongside natural selection before you get the kind of creative power that we see around us.

“Understanding how those two processes combine is the biggest challenge in biology.”


A simple single-celled amoeba has been turned into a computer by Drs Masashi Aono and Masahiko Hara at the Japanese research institute Riken. They harnessed the way that the creature responds to light to allow it to solve a famous puzzle called the travelling salesman problem.

The set-up is this: a sales rep has, say, six cities to visit. To minimise his travel costs, he must find the shortest route between them, one that visits every city just once. Once the number of cities grows to several hundred, the task will become too complex for even the cleverest computers.

In this case, the slime mould Physarum polycephalum solved the problem for four cities. The team harnessed two facts: the creature wants to have the biggest body area, but dislikes light. Thus they forced it to search for nutrients down specific branches – the routes between the cities – while it tried to minimise its exposure to illumination.

Hugo Marques of Essex University will discuss a pioneering attempt to give computers some imagination – which he believes “may be a significant step towards building a robot with a mental life”. He will try to mimic the relationship between the human brain and body by giving a robotic consciousness a skeleton to inhabit.

Scientists are also hoping to enhance our ability to study pollution and climate change by using “smart dust” – wireless chips with their own power supply and sensors that link to each other via radio. The Winchester conference will hear a proposal by Prof Davide Anguita and Dr Davide Brizzolara at the University of Genoa for a marine equivalent called smart plankton, which will provide “shoal intelligence”.

A new way to fight junk emails has been developed by Alaa Abi-Haidar of Indiana University and Luis Rocha of the Instituto Gulbenkian de Ciência, in Portugal. It is inspired by the way the body’s immune system fights off invading diseases and, according to Dr Abi-Haidar, promises greater resilience than existing systems to changes in the ratio of spam received compared to normal email (“ham”).

Roger Highfield

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2 thoughts on “Can we make software that comes to life?”

  1. How much do we humans enjoy our current status as the most intelligent beings on earth? Enough to try to stop our own inventions from surpassing us in smarts? If so, we’d better pull the plug right now, because if Ray Kurzweil is right we’ve only got until about 2020 before computers outpace the human brain in computational power. Kurzweil, artificial intelligence expert and author of The Age of Intelligent Machines, shows that technological evolution moves at an exponential pace. Further, he asserts, in a sort of swirling postulate, time speeds up as order increases, and vice versa. He calls this the “Law of Time and Chaos,” and it means that although entropy is slowing the stream of time down for the universe overall, and thus vastly increasing the amount of time between major events, in the eddy of technological evolution the exact opposite is happening, and events will soon be coming faster and more furiously. This means that we’d better figure out how to deal with conscious machines as soon as possible—they’ll soon not only be able to beat us at chess, but also likely demand civil rights, and might at last realize the very human dream of immortality.

    The Age of Spiritual Machines
    When Computers Exceed Human Intelligence
    by Ray Kurzweil
    Imagine a world where the difference between man and machine blurs, where the line between humanity and technology fades, and where the soul and the silicon chip unite. This is not science fiction. This is the twenty-first century according to Ray Kurzweil, the “restless genius” (Wall Street Journal) and inventor of the most innovative and compelling technology of our era. In The Age of Spiritual Machines, the brains behind the Kurzweil Reading Machine, the Kurzweil synthesizer, advanced speech recognition, and other technologies devises a framework for envisioning the next century. In his inspired hands, life in the new millennium no longer seems daunting. Instead, Kurzweil’s twenty-first century promises to be an age in which the marriage of human sensitivity and artificial intelligence fundamentally alters and improves the way we live.
    The Age of Spiritual Machines is no mere list of predictions but a prophetic blueprint for the future. Kurzweil guides us through the inexorable advances that will result in computers exceeding the memory capacity and computational ability of the human brain. According to Kurzweil, machines will achieve all this by 2020, with human attributes not far behind. We will begin to have relationships with automated personalities and use them as teachers, companions, and lovers. A mere ten years later, information will be fed straight into our brains along direct neural pathways; computers, for their part, will have read all the world’s literature. The distinction between us and computers will have become sufficiently blurred that when the machines claim to be conscious, we will believe them.
    In The Age of Spiritual Machines, the “ultimate thinking machine” forges the ultimate road to the next century.

    “The human brain has about 100 billion neurons. With an estimated average of one thousand connections between each neuron and its neighbors, we have about 100 trillion connections, each capable of a simultaneous calculation… (but) only 200 calculations per second… With 100 trillion connections, each computing at 200 calculations per second, we get 20 million billion calculations per second. This is a conservatively high estimate… by the year 2020, (a massively parallel neural net computer) will have doubled about 23 times (from 1997’s $2,000 modestly parallel computer that could perform around 2 billion connection calculations per second) … resulting in a speed of about 20 million billion neural connection calculations per second, which is equal to the human brain”.
    Ray Kurzweil, “The Age of Spiritual Machines”

    “People often go through three stages in examining the impact of future technology: awe and wonderment at its potential to overcome age old problems, then a sense of dread at a new set of grave dangers that accompany these new technologies, followed, finally and hopefully, by the realization that the only viable and responsible path is to set a careful course that can realize the promise while managing the peril.”
    Ray Kurzweil, “The Law of Accelerating Returns”


  2. Un robot fonctionne avec un cerveau composé de neurones de rat

    PARIS (AFP) – Un robot fonctionnant avec un véritable petit cerveau vivant composé de neurones de rat, capable “d’apprendre” des comportements comme éviter un mur, a été mis au point à l’Université de Reading (Angleterre) par des émules de Frankenstein.
    “Nous lui avons déjà donné un certain apprentissage par répétition, puisqu’il reproduit certaines actions”, a déclaré à l’AFP le responsable de l‘équipe multidisciplinaire, Kevin Warwick. “Mais nous voulons maintenant lui apprendre” des comportements, a-t-il dit.
    Le cerveau biologique du robot, baptisé Gordon, a été créé à partir de neurones prélevés sur un rat. Ils ont été placés dans une solution, séparés puis mis sur un lit d’une soixantaine d‘électrodes.
    “Dans les 24 heures, a souligné le chercheur, des connexions ont poussé entre eux”, formant un réseau comme dans un cerveau normal. Et “en une semaine il s’est produit des impulsions électriques spontanées et ce qui paraissait être une activité de cerveau ordinaire”.
    “Nous avons utilisé cette réaction pour relier le cerveau au robot avec des électrodes. Désormais, le cerveau contrôle le robot, et celui-ci apprend, par répétition”, explique le scientifique.
    Ces recherches, qui pourraient faciliter à terme l‘étude de traitements pour lutter contre les maladies neurodégénératives (Alzheimer, Parkinson…), permettent de suivre les réactions des neurones.
    Lorsque le robot, qui ressemble à Wall.E, le héros du dernier film des studios Pixar, heurte un mur, le cerveau reçoit une stimulation et il apprend par habitude à contourner l’obstacle. “Maintenant, nous étudions comment lui apprendre : en augmentant le voltage sur différents électrodes”, en utilisant des produits chimiques pour favoriser ou stopper les transmissions entre neurones, détaille Kevin Warwick.
    Mais déjà, “s’il est à un certain endroit et que nous voulons le faire aller à droite, nous pouvons envoyer une stimulation électrique” pour lui en donner l’ordre, ajoute-t-il.
    “Nous voulons comprendre comment les souvenirs sont archivés dans un cerveau biologique, par rapport à un cerveau d’ordinateur”, a-t-il poursuivi.
    “A l’heure actuelle, nous estimons qu’il y a de 50.000 à 100.000 neurones en activité” dans le cerveau de Gordon, a noté le chercheur. Un rat en possède au plus un million, et un Homme quelque 100 milliards.
    Et comme dans le cas de l’Homme, si le cerveau de Gordon n’est pas stimulé régulièrement, “il se laisse aller”. Alors qu’avec “des stimulations, les connexions se renforcent, il semble devenir plus alerte”, fait remarquer Kevin Warwick.
    “Nos travaux ont ainsi un rapport avec Alzheimer en ce qui concerne le stockage de la mémoire et comment on peut le renforcer”, par exemple en augmentant les stimuli élctriques, note-t-il.
    En effet, le cerveau de Gordon “est une version simplifiée de ce qui se passe dans le cerveau humain. Mais là, on peut regarder, et contrôler, les éléments essentiels comme nous le voulons”, contrairement à ce qui peut se faire in vivo chez l’Homme.
    L‘équipe de l’Université de Reading dispose de plusieurs cerveaux en activité. “Et c’est drôle, fait remarquer le chercheur, il y a des différences entre eux : il y en a un un peu violent, un peu actif. Un autre ne fera pas ce qu’on lui demande, il s‘écrasera contre les murs. Chacun a sa personnalité !”
    Quatre ou cinq autres groupes de scientifiques travaillent sur de tels cerveaux biologiques dans le monde, mais “en termes d’apprentissage par expérience et habitude, je ne l’ai jamais vu auparavant”, a noté Kevin Warwick.
    Quant à utiliser des neurones humains pour Gordon: “il y a clairement des obstacles éthiques. C’est plus une question éthique que technique”, répond-il.
    AFP – Mercredi 14 août, 2008


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