Anthropologist Steven Gonzalez Monserrate draws on five years of research and ethnographic fieldwork in server farms to illustrate some of the diverse environmental impacts of data storage. The Cloud is not only material, but is also an ecological force.

Of the many beloved and influential franchises to come out of the medium of video games, Doom is a name that comes to mind for a lot of players.

In the past few years, we’ve been deluged with discussions of how artificial intelligence (AI) will either save or destroy the world. Self-driving cars will keep us alive; social media bubbles will destroy democracy; robot toasters will rob us of our ability to heat bread.

Bitcoin and other cryptocurrencies like Ethereum, Ripple, and Litecoin have soared in value over the past year, thanks to continued interest from a range of investors.

Researchers based in New Zealand say they have restored the first known recording of computer-generated music which dates back to 1951 and was produced on a contraption made by Alan Turing.

Computers at Google now have a machine-learning system that can analyze images like the one above and generate captions for them. The phrase used to caption this image? "A person riding a motorcycle on a dirt road." It might not seem like much, but it's actually one hell of an accomplishment.

It is uncontroversial that the human brain has capabilities that are, in some respects, far superior to those of all other known objects in the cosmos.

I wrote a short piece for Grafik Magazine’s Screenshot feature: Moravec’s Paradox states that ‘low-level’ sensorimotor skills require far more computational resources than ‘high-level’ abstract reasoning. In general terms, this translates into the doctrine that computers are very good at solving some types of problems, humans at others. Picking out the face of a loved one in a packed crowd and walking over to embrace them is laughably easy for a human to do, but not a robot. Alternatively, calculating the square-root of 1,276,433,9 takes a cheap pocket calculator a few nanoseconds. As for a human? Well, try it out for yourself * Sustained by these principles, a new breed of machine/human hybrid systems have begun infecting our social and economic networks. Rather than imitate tasks that humans can do effortlessly, these programs are built to work with us, allowing the distinct strengths of human and ‘artificial’ intelligences to coalesce. One particularly intriguing example of this is the reCaptcha password system. Maintained by Google, reCaptcha is employed hundreds of millions of times every day, according to Google’s own promotional blurb, to ‘stop spam, read books’. You yourself — perhaps without knowing it — have taken part in a vast online act of computation, donating a short burst of your highly evolved pattern recognition skill to Google’s project of digitising every one of the world’s printed books. The reCaptcha system is doubly fascinating in regards Moravec’s Paradox because it marks the meeting-point between low-level and high-level computable problems. Every password is guessable given enough time and computer resources. Alternatively, the smudged word on page 286, line forty three of the Magna Carta is incredibly difficult for a computer to recognise. If it fails, a different smudge with a different ‘solution’ is pulled from the database, ensuring your email account remains secure. Whilst determining whether or not you are a human the reCaptcha software quietly hijacks your biological brain, translating the task it has been allotted to protect your data into a moment of distributed, invisible labour. The question is: who or what is using who or what, for what or whom? Systems like reCaptcha could be hailed as the birth of a ‘world brain’: a thinking web connecting everyone on Earth into a vast meta-mind capable of incredible feats of computation. The truth, however, is both far more mundane and far more profound in its implications. A generation or two ago we envisaged the future as a place where intricate machines would carry out most menial tasks, leaving humans free to contemplate their place in the universe, embrace loved ones in crowds, and sunbathe under the depleted ozone layer. Instead, we have inherited a world where humans carry out menial tasks at the bequest of machines, whilst maintaining the illusion that it is we, personally, who have benefited from each transaction. Every click and swipe of your finger is a collaboration between invisible entities — corporate, synthetic or not-even-invented yet. Next time you scan your own produce at the supermarket, track your eating and exercise habits, and upload them to a corporately maintained database, follow the advice of a piece of software on which stock to sell, or which car to buy, search Google for a weird string of misspelt terms, or retweet a Twitter bot, you are taking part in a vast experiment that has already evolved beyond any single person or machine’s ability to comprehend. The future of information is augmented, symbiotic, invisible and incessant. But does it belong to users? Corporations? Or semi-autonomous machines? Only you and your synthetic assistants can decide. * The answer, according to my smartphone, is 3572.7215116770576

In central London this spring, eight of the world’s greatest minds performed on a dimly lit stage in a wood-panelled theatre. An audience of hundreds watched in hushed reverence.

The digital eye is an ubiquitous feature of current portable technology—webcams, DSLRs, mobile phones, tablets, even MP3 players.

Using DNA would finally divorce the thing that stores information from the things that read it. Time and again, our storage formats become obsolete because we stop making the machines that read them-think about video tapes, cassettes, or floppy disks. That's a faff-it means that archivists have to co

Frances Egan is a mind-bombing philosopher who wonders on explanatory frameworks of science, the fits and starts of mind evolution, the links between neuroscience and meaning, the redness of tomatoes, the difference between horizon and zenith moons, fMRI interfaces with philosophy, mind/computer uploading and the consciousness of the USA. All in all, she is a deep groove hipster of the philo-mindster jive. Awesome!

3:AM: What made you a philosopher and has it been rewarding so far?

Frances Egan: I read some political philosophy on my own in high school, but I wasn’t exposed to philosophy systematically until college. I took a philosophy course in my first semester because I was looking for something different. After a brief introduction to logic we discussed the problem of evil: how could an omnipotent, benevolent god allow so much pain and suffering? I was raised Catholic but that was the end of religion for me. Nothing quite that dramatic has happened since, but thinking about fund

Earlier this year, IBM celebrated the 15-year anniversary of its supercomputer Deep Blue beating chess champion Garry Kasparov. According to a new book, however, it may have been an accidental glitch rather than computing firepower that gave Deep Blue the win. At the Washington Post, Brad Plumer high

Alex Churchill has posted a way to implement a Turing complete computer within a game of Magic: The Gathering ("Turing complete" is a way of classifying a calculating engine that is capable of general-purpose computation). The profound and interesting thing about the recurrence of Turing completeness in many unexpected places -- such as page-layout descriptive engines -- is that it suggests that there's something foundational about the ability to do general computation. It also suggests that attempts to limit general computation will be complicated by the continued discovery of new potential computing engines. That is, even if you lock down all the PCs so that they only play restricted music formats and not Ogg, if you allow a sufficiently speedy and scriptable Magic: The Gathering program to exist, someone may implement the Ogg player using collectible card games.

With an eight-track tape recorder and 100,000 times less memory than an iPod, Voyager 1 is celebrating its 35th birthday at the edge of the solar system. Traipsing through a giant, turbulent, plasma bubble near the fringes, the longest-running, most-distant spacecraft in NASA's history celebrates a l

Digital information is accumulating at an astounding rate, straining our ability to store and archive it. DNA is among the most dense and stable information media known. The development of new technologies in both DNA synthesis and sequencing make DNA an increasingly feasible digital storage medium.

‘An important feature of a learning machine is that its teacher will often be very largely ignorant of quite what is going on inside, although he may still be able to some extent to predict his pupil’s behaviour.’ Alan Turing, Computing Machinery and Intelligence (1950)

Replenishing each worn-out piece of its glimmering hull, one by one, the day arrives when the entire ship of Argo has been displaced – each of its parts now distinct from those of the ‘original’ vessel. For Roland Barthes, this myth exposes two modest activities:

Substitution (one part replaces another, as in a paradigm) Nomination (the name is in no way linked to the stability of the parts) 1

The discrete breaches the continuous in the act of nomination. Take for instance the spectrum of colours, the extension of which ‘is verbally reduced to a series of discontinuous terms’ 2 such as red, green, lilac or puce. Each colour has no cause but its name. By being isolated in language the colour ‘blue’ is allowed to exist, but its existence is an act of linguistic and, some would argue, perceptual severance. The city of Hull, the phrase “I will”, the surface of an ice cube and an image compression algorithm are entities each sustained by the same nominative disclosure: a paradox of things that seem to flow into one another with liquid potential, but things, nonetheless, limited by their constant, necessary re-iteration in language. There is no thing more contradictory in this regard than the human subject, a figure Barthes’ tried to paradoxically side-step in his playful autobiography. Like the ship of Argo, human experience has exchangeable parts, but at its core, such was Barthes’ intention, ‘the subject, unreconciled, demands that language represent the continuity of desire.’ 3

In an esoteric paper, published in 1930, Lewis Richardson teased out an analogy between flashes of human insight and the spark that leaps across a stop gap in an electrical circuit. The paper, entitled The Analogy Between Mental Images and Sparks, navigates around a provocative sketch stencilled into its pages of a simple indeterminate circuit, whose future state it is impossible to predict. Richardson’s playful label for the diagram hides a deep significance. For even at the simplest binary level, Richardson argued, computation need not necessarily be deterministic.

The discrete and the continuous are here again blurred by analogy. Electricity flowing and electricity not flowing: a binary imposition responsible for the entire history of information technology.

1 Roland Barthes, Roland Barthes (University of California Press, 1994), 46.

2 Roland Barthes, Elements of Semiology (Hill and Wang, 1977), 64.

3 Paul John Eakin, Touching the World: Reference in Autobiography (Princeton University Press, 1992), 16.

Animation of first 200 steps of Langton’s ant

Was reading about microchips that are designed to allow a few mistakes (known as 'Sloppy Chips'), and pondering equivalent kinds of 'coding' errors and entropy in biological systems. Can a fair comparison be made between the two? OK, to setup my question I probably need to run through my (basic) understanding of biological vs silicon entropy...

In the transistor, error is a bad thing (in getting the required job done as efficiently and cheaply as possible), metered by parity bits that come as standard in every packet of data transmitted. But, in biological systems error is not necessarily bad. Most copying errors are filtered out, but some propogate and some of those might become beneficial to the organism (in thermodynamics sometimes known as "autonomy producing equivocations").

Relating to the article about 'sloppy chips', how does entropy and energy efficiency factor into this? For the silicon chip efficiency leads to heat (a problem), for the string of DNA efficiency leads to fewer mutations, and thus less change within populations, and thus, inevitably, less capacity for organisms to diversify and react to their environments - leading to no evolution, no change, no good. Slightly less efficiency is good for biology, and, it seems, good for some kinds of calculations and computer processes.

What work has been done on these connections I draw between the biological and the silicon?

I'm worried that my analogy is limited, based as it is on a paradigm for living systems that too closely mirrors the digital systems we have built. Can DNA and binary parity bit transistors be understood on their own terms, without resorting to using the other as a metaphor to understanding?

Where do the boundaries lie in comparing the two?

Letting microchips make a few mistakes here and there could make them much faster and more energy-efficient.

Managing the probability of errors and limiting where they occur can ensure that the errors do not cause any problems. The result of a mathematical calculation, for example, need not always be calculated precisely—an accuracy of two or three decimal places is often enough. Dr Palem offers the analogy of a person about to cross a big room. Rather than wasting time and energy calculating the shortest path, it’s better just to start walking in roughly the right direction.