Imitation of Life: How Biology Is Inspiring Computing


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But there are signs of a revival driven by an accumulating body of knowledge and expertise in what might be called fundamental biomimicry, which trawls nature for inspiration in a more systematic way by matching the products of evolution with specific target applications.

This change came with the realization that natural systems can rarely be exploited directly for various reasons, such as the choice of materials or a lack of understanding of the underlying mechanisms. A good example of this wrongheaded approach is artificial photosynthesis. Scientists realized early on that proteins are not the best materials for artificial systems to harness sunlight for energy production, because they have to be constantly renewed. Alternative materials such as ruthenium are therefore preferred as catalysts to exploit the principles of photosynthesis 1.

8 things you didn’t know about Alan Turing

Exploiting nature's inventions is more about ideas and inspiration rather than blind mimicry. When I speak at biomimicry conferences, it is usually in the role of the skeptic.


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Kiers cited her own specialty, which is cooperation in nature as in symbiotic relationships. But the truth is that these cooperative relationships are built on reciprocal exploitation, so that both parties may benefit but with an inherent tension. Both parties are trying to maximize their gains and there is really nothing harmonious about it. Other examples of what is not biomimicry include wastewater cleaning with bacteria.

This is rather bioutilization, where the organism is selected or engineered to provide a particular function. One field where biomimicry has been applied widely and sometimes inappropriately is architecture, where it has almost become a dogma in some quarters. In fact, architects have been copying nature for centuries, with birds' nests inspiring huts or by emulating termite nests for efficient ventilation and temperature control in larger buildings.

At the same time, though, there has been mounting criticism of a slavish adherence to biomimetics driven by a desire for environmental correctness rather than hard science. Such considerations do not apply so much for the design of materials with specific properties, such as stickiness. In one case, this has led to a novel solution for a previously intractable problem, namely sealing holes in children's hearts during surgery. Downsizing them simply does not work for kids. Their hearts are growing. Karp and his colleagues envisioned a patch coated with glue that could be placed into the heart and pushed up against the hole.

It seemed the sort of problem that might have cropped up in nature among creatures inhabiting wet environments and eventually inspiration was found from more than one organism. So, we thought, what if you can develop an adhesive like that, that was entirely hydrophobic. You put it inside a beating heart onto the tissue surface and it would repel the blood away from the surface and then because it's viscous it would remain in place, even in the presence of flowing blood, long enough for us then to cure it in place.

The material has been shown to seal the carotid artery and aorta in pigs, as well as holes in the hearts of rats 2. Silk, produced by spiders and the silk worm, has long been a cheerleader for bioinspired materials because of its combination of strength, elasticity, and lightness.

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Yet, exploiting these properties, either artificially or through recombinant approaches, has proven difficult. Unlike silk worms, spiders cannot readily be harnessed for fabricating silk at scale because they begin to eat each other if reared in close proximity. Thus, efforts have focused on isolating the relevant genes and transferring them to suitable organisms. Spiber Systems, based in Stockholm, Sweden, uses recombinant E.

Bolt Threads, in Emeryville, CA, USA, ferments recombinant yeast with spidroin genes to produce silk at large scale, with the aim of at least matching the costs of producing fibers by established techniques, including silkworm silk and fine wools. Unlike Spiber, which focuses on medical applications, Bolt Threads aims at the textile market. Views Total views. Actions Shares. Embeds 0 No embeds. No notes for slide.

Network and Complex Systems www. Bio-inspired methods have recently gained importance in computing due to the need for flexible,adaptable ways of solving engineering problems.

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Bio-inspired algorithms are based on the structure andfunctioning of complex natural systems and tend to solve problems in an adaptable and distributed fashion. An example of a bio-inspired approach to solving the problem of location search has been taken up anddiscussed in this paper. The bio-inspired methodology has several merits and demerits, which are alsodiscussed in the paper. IntroductionComputers have grown from rudimentary calculation machines to sophisticated complex machines that canperform detailed and precise computations and store huge amounts of data.

However, the capacity ofcomputers is still limited by the physical limits imposed by the raw material used to make computers. Nancy Forbes Several computation techniques have been introduced to enhance computation beyond the physical limitsof computers to solve complex problems. One such approach is biologically inspired computing, alsoknown as Bio-Inspired approach. Despite the numerous advances in computing technologies, we continue to be humbled by the way natureoperates.

The variety, sophistication of nature has always amazed the human kind. A problem solvingmethodology derived from the structure, behaviour and operation of a natural system is called a Bio-Inspired approach. Several systems such as the ant-colony system, bee foraging, bird flocking etc. Bio-inspired algorithms have gained importancein the field of computing for their remarkably flexible and adaptable nature. What is Bio-Inspired Computing? Computing has evolved to help us solve problems with increasing ease. Several complicated problems canbe solved using engineering approaches.

However classical approaches to solve such problems lack inflexibility and require rigorous mathematical analysis. In direct contrast to these approaches are newmethodologies inspired by the natural world that provide simple solutions to complex problems that wouldbe hard by traditional computing approaches. Biologically inspired algorithms or bio-inspired algorithms are a class of algorithms that imitate specificphenomena from nature. Bio-inspired algorithms are usually bottom-up, decentralized approaches Ding that specify a simple set of conditions and rules and attempt to solve a complex problem byiteratively applying these rules.

Such algorithms tend to be adaptive, reactive and distributed. Rocha 2. Biological organisms dealwith environmental demands using ingenious solutions that differ greatly from engineering solutions thatare traditionally used to solve similar problems. Such biological solutions are commonplace and easilyavailable to study. Inspiration has been drawn from biology since the time of early computing.

The first digital computer byvon Newmann was based on the human brain. Nancy Forbes However the use of algorithms directlymimicking the behaviour of natural organisms is a recent development and these algorithms are proven tobe significantly more robust and adaptive than traditional algorithms while not compromising much onperformance. Bio-inspired algorithms imitate a biological system in terms of their component behaviour. Biologicalsystems heavily depend on individual components of the system. Thus the first step in building a bio-inspired algorithm is to build individual simplistic components that imitate the behaviour of their biologicalcounterparts.

These components then try to reach the overall goal that is defined for them.

The componentscan then be tailored to meet specific problem requirements such as performance or adaptability. An ExampleThere have been several papers in this area targeting specific real world problems. Researchers havetailored generic bio-inspired approaches such as genetic engineering and ant-colony optimisation tospecialized computing problems such as developing self-organizing systems and dynamic resourceallocation. One such application is the use of the Haptotaxis phenomenon to perform a location search in anunstructured p2p network.

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Cell migration to a wounded area or to an inflamed area in the body mustmaintain a defined direction and speed. This is achieved by cell adhesion proteins that are present in the cellwalls. Adhesion ligands are present in the extra-cellular matrix ECM. The ECM is a layer that surroundscells in a tissue. The ECM creates a gradient of cell adhesion causing the cells to move towards higheradhesion between ECM ligands and cell receptors. The magnitude of adhesion affects the speed of cellmovement while the gradient of adhesion affects direction of cell movement. The Haptotaxis phenomenonis an example of making cells move closer to the destination.

This concept can easily be applied to anyguided search problem where at any given point of time, the entity should be directed closer to thedestination.

Imitation of life : how biology is inspiring computing / Nancy Forbes | Smithsonian Institution

This techniqueis called the Hapto-search algorithm. The authors assume a key based network, where the aim of the system is to retrieve location information ofother nodes in the system. Each node is assigned a key, which it distributes to a fixed number of nodes inthe network. We say that a node A knows the location information of a node B if it knows the key of B. Thus, if a node A wants to find the location information of a node B, it tries to reach a node C which has akey of node B. Figure 1 depicts an instance of the use of the Hapto-search algorithm in a key based network.

Assume that anode X distributes its key to nodes C and D. A node G tries to find location information of node X. It firstsearches the keys it contains to determine if it itself contains the location information of the node X If nodeG does not contain the key of node it searches its neighbours to find the neighbour that is closest to thedestination. But the formal pardon doesn't really do anything for him: he's dead. A Turing would have described himself as a mathematician. I think it's fair to unpack that and describe some of the things he did. The two things he did which are most distinctive are that he founded the whole concept of computer science, upon which everything in computer science theory is now based.

And the other thing was his work during the Second World War, which was extremely important cryptanalysis. Although what he did often seems abstruse, he was unusual in that he was very alive to engineering and the concrete application of difficult ideas. The best example of that is in his code-breaking work. But you can see it in everything he did. Computer science is all about linking logical possibilities with the physical reality.

There are lots of paradoxes in Turing's life, but this is the central theme. A The central most distinctive thing he did was the breaking of the naval Enigma messages. That was something that he alone took on after the more basic form of the Enigma had been dealt with. You have to make that distinction: the Enigma machine was used by all branches of the German Armed Forces, and indeed by diplomatic and other departments as well.

But it was the use by the German Navy that was the most difficult to break. They used it much more carefully than the others. Turing was taken on by the government as a part-time consultant in and only started full-time in September immediately on the outbreak of war. He, with Gordon Welchman and helped by very important information coming from Polish mathematicians, really dealt with the basic Enigma problem very quickly. The crucial thing about what Turing did — what makes him distinctive — is that he took on the naval problem, which was commonly thought of as impossible.

That's what he attacked doggedly, and with very little to go on. There was a breakthrough when, in February , the British captured codebook papers. Afterthat Turing's advanced methods were very successful and he recruited a team of very brilliant young mathematicians to help.

His group at Hut 8 was perhaps the most distinctive of the war in what it achieved. A It's a complicated story because that success was cut off completely on 1 February , when the German U-boat system went over to an advanced Enigma with four rotors. You don't really capture what Turing did without realising that there was this drama to it. It wasn't just a case of breaking the code, and then it was done.

There was this constant knife-edge situation where a small change in the Enigma system could make a huge difference in the deciphering business. In fact, Turing's role went on from there. The US production of the cipher-breaking Bombe machines played a crucial part in the latter part of the war, and Turing was the top-level person who made the liaison with the US between November and March After that, Turing was the top consultant to all aspects of the code-breaking business both at Bletchley Park and the US. He was the most important person on the scientific side at Bletchley Park during the Second World War.

A He had a particular type of mind that combined very abstract things with things that were very down to earth as well. You can see that in his big work, his paper 'On Computable Numbers'. That took off from the most abstruse and abstract problem of mathematics, which he resolved by giving this concrete picture of a teleprinter-like machine.

He asks what can such a machine do. What can't it do?


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He argues that this model encompasses everything that you could possibly call computation. Turing was the person who linked that theoretical question with something that was physical, concrete. The outcome of that was the concept of a Universal Machine as something, again, that you could actually construct.

He must have thought about doing that in the late s, and that's now what we call the principle of the digital computer; the principle of the stored program; the principle that programs are themselves a form of data so that you can copy them, translate them, do anything you like with them, just as you can do anything like that with numbers. There's no real distinction. That was very much his own thing: it didn't come from reading what other people had done.

Imitation of Life: How Biology Is Inspiring Computing Imitation of Life: How Biology Is Inspiring Computing
Imitation of Life: How Biology Is Inspiring Computing Imitation of Life: How Biology Is Inspiring Computing
Imitation of Life: How Biology Is Inspiring Computing Imitation of Life: How Biology Is Inspiring Computing
Imitation of Life: How Biology Is Inspiring Computing Imitation of Life: How Biology Is Inspiring Computing
Imitation of Life: How Biology Is Inspiring Computing Imitation of Life: How Biology Is Inspiring Computing
Imitation of Life: How Biology Is Inspiring Computing Imitation of Life: How Biology Is Inspiring Computing
Imitation of Life: How Biology Is Inspiring Computing Imitation of Life: How Biology Is Inspiring Computing

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