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#life – @pretendy-blog on Tumblr
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pretendy

@pretendy-blog / pretendy-blog.tumblr.com

I'm a physics student at the University of Warwick, UK.
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Protocells and Artificial Life

In this talk, Martin Hanczyc outlines a series of experiments where artificial protocells synthesised from oil and clay display primitive kinds of behaviour associated with life.

He begins by framing his working assumptions - that there exists a continuum between the living and the non-living - and identifies a few key features of a living system: a self-contained body, working metabolism, and inheritable information. The body coupled with metabolism allows an organism to move and interact with its environment, and all three together allow for replication and evolution.

While a cell might contain on the order of 1,000,000 different kinds of molecules, he was able to synthesise "life-like" protocells from just five. Oil disassociates with water and forms globules. These oil globules make up his protocell bodies, while a type of chemically active clay forms the basis of a metabolic system - extracting energy from the environment in order to "do something". What can his protocells do? He shows us a few neat videos:

  • A single protocell moves around its environment (a petri dish)
  • It seek out 'food' 
  • Multiple protocells interact with each other - "dance".
  • On a rare occasion, two cells of a different variety fuse, taking on qualities of both parent cells.
  • Hybridised protocells are observed dividing.

These are really cool experiments. Though his humble artificial organisms are by no means Frankenstein's monster, they go a long way to help us understand what questions we should be asking about what makes something living as opposed to non-living. They show that certain fundamental properties of the complex life we see around us can be observed in relatively simple chemical systems.

Source: pretendy
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This is really cool. Toni Westbrook has created an extensive neural network software package that uses virtual DNA to grow artificial brains. He states:

The ultimate goal is a true, functional model of the biological neural network in software grown using virtual DNA.

In this video his SynthNet program interfaces with a lego robot. He demonstrates its ability to not only interpret sound, but also to use it as a stimulus for associative learning.

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Life is blind.

How do we define life? If you asked this question to a biologist, he or she would point you towards the seven commandments of life science (‘thou shalt metabolise’; ‘thou shalt adapt’; ‘thou shalt reproduceetc.) Life, they would say, is a label we give to anything displaying these seven features. This stone tablet has been able to bestow the status of ‘living’ unto all the fish and trees and mushrooms and amoebae that biologists have so far wanted to study. However is this statutory definition enough? I don’t think it is. It seeks to sort any given collection of molecules into one of two camps: ‘living’ or ‘not living’. It’s a tautological distinction that takes no prisoners. Importantly, rather than attempting to form a truly encompassing definition, all it does is list seven characteristics that are common to everything that had already been colloquially defined as life! It is no more of a definition than an affirmation. It in no way reflects the complex nature of, well... Nature. An individual mammal and the cells inside it are both considered to be living in their own right. Contrast this with a swarm of bees which isn’t generally thought of as an organism in of itself, but rather a collection of organisms. Our intuition seems to only accept something as living if it’s encapsulated in its entirety by skin, scales or a membrane. Yet in many ways a swarm or hive will act as a single coherent organism when reacting to a stimulus. A hive is even organised into subsystems (workers, soldiers, a queen etc.) which all interact with each other in a way that’s fundamentally similar to the way cells interact in a mammal.

We live in hives too, but we call them cities. Cities are often described through metaphors such as ‘thriving’ or ‘alive’, but are these more than metaphors? A city metabolises coal to power and heat itself, it has a body clock and transport network, it’s organised into cells (us) which function to keep it homeostatic, it can grow and die, it adapts to environmental changes over time... Despite all this it we as humans remain very objectionable to the idea that a city might be an actual living organism. But then again, if a red blood cell could philosophise would it too reject the notion that its host was in some sense just as much an individual as it was? Would it not ascribe the seemingly intelligent behaviour of the human it lives in to the computational work performed by individual neurons that it supplies oxygen to rather than the human itself? The human would certainly ascribe intelligence to itself! Or its brain, where it considers the ‘seat of its consciousness’ to be. In what ways, then, is a computer different to a brain? While I’m not going to get into a discussion of consciousness, I will raise the question: do computers think? Well, they don’t think like a human, but that’s not to say they don’t in some sense think. In any case, the answer certainly isn’t either a yes or a no, but complex and multi-faceted one. And I think this is true not just of thought but of life itself. The questions raised here are ones that cannot be addressed (or even asked!) by the limiting definiton that biology has given us. In this sense it is blind to many possibilities of life that we could learn from. Life cannot be defined in such a way that makes it a binary digit (either living or not living). Nor should it be a scale of 1-10. If anything, it’s a many-dimensional vector. The seven pillars should not serve as committee in charge of (lifelong?) membership to the Living Club. Rather, they should be thought of as a set of features that emerge out of the complex behaviours characteristic to life and governed by evolution. Life, if anything is a single individual composed of sub-individuals, sub-systems, subsub-individuals, self-similar on many scales, all interacting, all ecompassing. It is a networked fractal array of cogs and axels but most of all: hugely, vastly, complex.

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Pics or GTFO: Why we haven't found life on Mars.

Over the past couple of days the internet has been buzzing with its perennial excitement over a new 'discovery' of life on Mars. Yesterday came reports that a team of researchers retro-analysing data from NASA's 1976 Viking missions concluded that the landers did indeed find microbial life in martian soil.

A little background: In 1976 Viking 1 and 2, conducted four biological experiments on the martian soil (pictured above). Though three were unambiguously negative, one produced interesting results. Various samples of soil were injected with different microbial nutrients laced with radioactive carbon-14. Over a period of a few days, gas released by the soil was analysed and it was found that traces radioactive carbon dioxide had been released, a possible indication that carbon was being metabolised by bacteria.

Recently, a group of scientists conducted complexity analysis on the data and found that the active samples exhibited complexity associated with biological life, whereas the sterile control samples did not.

Great, that's that then. Well, no, not quite. 'Is there other life out there?' is one of the biggest questions in science history! Therefore, any such discovery cannot be attributed to anything short of the direct observation and full analysis of living samples. In otherwords 'Pics or GTFO'.

Having said that, the original Viking experiments could not have discovered life even if all the results were positive. The most they could have achieved was an observation of a process consistent with what we would expect from a biological process.

Now, while the recent results are very interesting from a complexity science point of view, they do not in anyway prove the existence of life on Mars. They are nothing more than a statistical analysis of 30-year-old inconclusive results of an observation of a phenomenon that may be biological. You can probably start to see now how this is getting quite tenuous.

Unfortunately, this story is yet another example of a poorly researched news piece riding the wave of its ow misleading headline. Bad journalists! Carl Sagan and the Viking lander look down on you with shame...

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