Tuesday, May 24. 2016
Note: even people developing automation will be automated, so to say...
Do you want to change this existing (and predictable) future? This would be the right time to come with counter-proposals then...
But I'm quite surprized by the absence of nuanced analysis in the Wired article btw (am I? further than "make the workd a better place" I mean): indeed, this is a scientific achievement, but then what? no stakes? no social issues? It seems to be the way things should go then... (and some people know pretty well how "The Way Things Go", always wrong ;)), to the point that " No, Asimo isn’t quite as advanced—or as frightening—as Skynet." Good to know!
Via Wired
-----
By Cade Metz
Deep neural networks are remaking the Internet. Able to learn very human tasks by analyzing vast amounts of digital data, these artificially intelligent systems are injecting online services with a power that just wasn’t viable in years past. They’re identifying faces in photos and recognizing commands spoken into smartphones and translating conversations from one language to another. They’re even helping Google choose its search results. All this we know. But what’s less discussed is how the giants of the Internet go about building these rather remarkable engines of AI.
Part of it is that companies like Google and Facebook pay top dollar for some really smart people. Only a few hundred souls on Earth have the talent and the training needed to really push the state-of-the-art forward, and paying for these top minds is a lot like paying for an NFL quarterback. That’s a bottleneck in the continued progress of artificial intelligence. And it’s not the only one. Even the top researchers can’t build these services without trial and error on an enormous scale. To build a deep neural network that cracks the next big AI problem, researchers must first try countless options that don’t work, running each one across dozens and potentially hundreds of machines.
“It’s almost like being the coach rather than the player,” says Demis Hassabis, co-founder of DeepMind, the Google outfit behind the history-making AI that beat the world’s best Go player. “You’re coaxing these things, rather than directly telling them what to do.”
That’s why many of these companies are now trying to automate this trial and error—or at least part of it. If you automate some of the heavily lifting, the thinking goes, you can more rapidly push the latest machine learning into the hands of rank-and-file engineers—and you can give the top minds more time to focus on bigger ideas and tougher problems. This, in turn, will accelerate the progress of AI inside the Internet apps and services that you and I use every day.
In other words, for computers to get smarter faster, computers themselves must handle even more of the grunt work. The giants of the Internet are building computing systems that can test countless machine learning algorithms on behalf of their engineers, that can cycle through so many possibilities on their own. Better yet, these companies are building AI algorithms that can help build AI algorithms. No joke. Inside Facebook, engineers have designed what they like to call an “automated machine learning engineer,” an artificially intelligent system that helps create artificially intelligent systems. It’s a long way from perfection. But the goal is to create new AI models using as little human grunt work as possible.
Feeling the Flow
After Facebook’s $104 billion IPO in 2012, Hussein Mehanna and other engineers on the Facebook ads team felt an added pressure to improve the company’s ad targeting, to more precisely match ads to the hundreds of millions of people using its social network. This meant building deep neural networks and other machine learning algorithms that could make better use of the vast amounts of data Facebook collects on the characteristics and behavior of those hundreds of millions of people.
According to Mehanna, Facebook engineers had no problem generating ideas for new AI, but testing these ideas was another matter. So he and his team built a tool called Flow. “We wanted to build a machine-learning assembly line that all engineers at Facebook could use,” Mehanna says. Flow is designed to help engineers build, test, and execute machine learning algorithms on a massive scale, and this includes practically any form of machine learning—a broad technology that covers all services capable of learning tasks largely on their own.
Basically, engineers could readily test an endless stream of ideas across the company’s sprawling network of computer data centers. They could run all sorts of algorithmic possibilities—involving not just deep learning but other forms of AI, including logistic regression to boosted decision trees—and the results could feed still more ideas. “The more ideas you try, the better,” Mehanna says. “The more data you try, the better.” It also meant that engineers could readily reuse algorithms that others had built, tweaking these algorithms and applying them to other tasks.
Soon, Mehanna and his team expanded Flow for use across the entire company. Inside other teams, it could help generate algorithms that could choose the links for your Faceboook News Feed, recognize faces in photos posted to the social network, or generate audio captions for photos so that the blind can understand what’s in them. It could even help the company determine what parts of the world still need access to the Internet.
With Flow, Mehanna says, Facebook trains and tests about 300,000 machine learning models each month. Whereas it once rolled a new AI model onto its social network every 60 days or so, it can now release several new models each week.
The Next Frontier
The idea is far bigger than Facebook. It’s common practice across the world of deep learning. Last year, Twitter acquired a startup, WhetLab, that specializes in this kind of thing, and recently, Microsoft described how its researchers use a system to test a sea of possible AI models. Microsoft researcher Jian Sun calls it “human-assisted search.”
Mehanna and Facebook want to accelerate this. The company plans to eventually open source Flow, sharing it with the world at large, and according to Mehanna, outfits like LinkedIn, Uber, and Twitter are already interested in using it. Mehanna and team have also built a tool called AutoML that can remove even more of the burden from human engineers. Running atop Flow, AutoML can automatically “clean” the data needed to train neural networks and other machine learning algorithms—prepare it for testing without any human intervention—and Mehanna envisions a version that could even gather the data on its own. But more intriguingly, AutoML uses artificial intelligence to help build artificial intelligence.
As Mehana says, Facebook trains and tests about 300,000 machine learning models each month. AutoML can then use the results of these tests to train another machine learning model that can optimize the training of machine learning models. Yes, that can be a hard thing to wrap your head around. Mehanna compares it to Inception. But it works. The system can automatically chooses algorithms and parameters that are likely to work. “It can almost predict the result before the training,” Mehanna says.
Inside the Facebook ads team, engineers even built that automated machine learning engineer, and this too has spread to the rest of the company. It’s called Asimo, and according to Facebook, there are cases where it can automatically generate enhanced and improved incarnations of existing models—models that human engineers can then instantly deploy to the net. “It cannot yet invent a new AI algorithm,” Mehanna says. “But who knows, down the road…”
It’s an intriguing idea—indeed, one that has captivated science fiction writers for decades: an intelligent machine that builds itself. No, Asimo isn’t quite as advanced—or as frightening—as Skynet. But it’s a step toward a world where so many others, not just the field’s sharpest minds, will build new AI. Some of those others won’t even be human.
Thursday, April 21. 2016
Note: the idea of automation is very present again recently. And it is more and more put together with the related idea of a society without work, or insufficient work for everyone --which is already the case in the liberal way of thinking btw--, as most of it would be taken by autonomous machines, AIs, etc.
Many people are warning about this (Bill Gates among them, talking precisely about "software substitution"), some think about a "universal income" as a possible response, some say we shouldn't accept this and use our consumer power to reject such products (we spoke passionatey about it with my good old friend Eric Sadin last week during a meal at the Palais de Tokyo in Paris, while drinking --almost automatically as well-- some good wine), some say it is almost too late and we should plan and have visions for what is coming upon us...
Now comes also an exhibition about the same subject at Kunsthalle Wien that tries to articulate the questions: "Technical devices that were originally designed to serve and assist us and are now getting smarter and harder to control and comprehend. Does their growing autonomy mean that the machines will one day overpower us? Or will they remain our subservient little helpers, our gateway to greater knowledge and sovereignty?"
Via WMMNA
-----
Installation view The Promise of Total Automation. Image Kunsthalle Wien
Cécile B. Evans, How happy a Thing Can Be, 2014. Image Kunsthalle Wien
The word ‘automation’ is appearing in places that would have seemed unlikely to most people less than a decade ago: journalism, art, design or law. Robots and algorithms are being increasingly convincing at doing things just like humans. And sometimes even better than humans.
The Promise of Total Automation, an exhibition recently opened at Kunsthalle Wien in Vienna, looks at our troubled relationship with machines. Technical devices that were originally designed to serve and assist us and are now getting smarter and harder to control and comprehend. Does their growing autonomy mean that the machines will one day overpower us? Or will they remain our subservient little helpers, our gateway to greater knowledge and sovereignty?
The “promise of total automation” was the battle cry of Fordism. What we nowadays call “technology” is an already co-opted version of it, being instrumentalised for production, communication, control and body-enhancements, that is for a colonisation and rationalisation of space, time and minds. Still technology cannot be reduced to it. In the exhibition, automation, improvisation and sense of wonder are not opposed but sustain each other. The artistic positions consider technology as complex as it is, animated at the same time by rational and irrational dynamics.
The Promise of Total Automation is an intelligent, inquisitive and engrossing exhibition. Its investigation into the tensions and dilemmas of human/machines relationship explore themes that go from artificial intelligence to industrial aesthetics, from bio-politics to theories of conspiracy, from e-waste to resistance to innovation, from archaeology of digital communication to utopias that won’t die.
The show is dense in information and invitations to ponder so don’t forget to pick up one of the free information booklet at the entrance of the show. You’re going to need it!
A not-so-quick walk around the show:
James Benning, Stemple Pass, 2012
James Benning‘s film Stemple Pass is made of four static shots, each from the same angle and each 30 minutes long, showing a cabin in the middle of a forest in spring, fall, winter and summer. The modest building is a replica of the hideout of anti-technology terrorist Ted Kaczynski. The soundtrack alternates between the ambient sound of the forest and Benning reading from the Unabomber’s journals, encrypted documents and manifesto.
Kaczynski’s texts hover between his love for nature and his intention to destroy and murder. Between his daily life in the woods and his fears that technology is going to turn into an instrument that enables the powerful elite to take control over society. What is shocking is not so much the violence of his words because you expect them. It’s when he gets it right that you get upset. When he expresses his distrust of the merciless rise of technology, his doubts regarding the promises of innovation and it somehow makes sense to you.
Konrad Klapheck, Der Chef, 1965. Photo: © Museum Kunstpalast – ARTOTHEK
Konrad Klapheck’s paintings ‘portray’ devices that were becoming mainstream in 1960s households: vacuum cleaner, typewriters, sewing machines, telephones, etc. In his works, the objects are abstracted from any context, glorified and personified. In the typewriter series, he even assigns roles to the objects. They are Herrscher (ruler), Diktator, Gesetzgeber (lawgiver) or Chef (boss.) These titles allude to the important role that the instruments have taken in administrative and economic systems.
Tyler Coburn, Sabots, 2016, courtesy of the artist, photo: David Avazzadeh
This unassuming small pair of 3D-printed clogs alludes to the workers struggles of the Industrial Revolution. The title of the piece, Sabots, means clogs in french. The word sabotage allegedly comes from it. The story says that when French farmers left the countryside to come and work in factories they kept on wearing their peasant clogs. These shoes were not suited for factory works and as a consequence, the word ‘saboter’ came to mean ‘to work clumsily or incompetently’ or ‘to make a mess of things.’ Another apocryphal story says that disgruntled workers blamed the clogs when they damaged or tampered machinery. Another version saw the workers throwing their clogs at the machine to destroy it.
In the early 20th century, labor unions such as the Industrial Workers of the World (IWW) advocated withdrawal of efficiency as a means of self-defense against unfair working conditions. They called it sabotage.
Tyler Coburn, Waste Management, 2013-15
Tyler Coburn contributed another work to the show. Waste Management looks like a pair of natural stones but the rocks are actually made out of electronic waste, more precisely the glass from old computer monitors and fiber powder from printed circuit boards that were mixed with epoxy and then molded in an electronic recycling factory in Taiwan. The country is not only a leader in the export of electronics, but also in the development of e-waste processing technologies that turn electronic trash into architectural bricks, gold potassium cyanide, precious metals—and even artworks such as these rocks. Coburn bought them there as a ready made. They evoke the Chinese scholar’s rocks. By the early Song dynasty (960–1279), the Chinese started collecting small ornamental rocks, especially the rocks that had been sculpted naturally by processes of erosion.
Coburn’s rocks are thus artificial objects that crave an aesthetic value that can only come from natural objects.
Accompanying these objects is a printed broadsheet which narrates the circulation and transformation of a CRT monitor into the stone artworks. The story follows from the “it-narrative” or novel of circulation, a sub-genre of 18th Century literature, in which currencies and commodities narrated their circulation within a then-emerging global economy.
Osborne & Felsenstein, Personal Computer Osborne 1a and Monitor NEC, 1981, Loan Vienna Technical Museum, photo: David Avazzadeh
Adam Osborne and Lee Felsenstein, Personal Computer Osborne 1a, 1981, Courtesy Technisches Museum, Wien
Several artifacts ground the exhibition into the technological and cultural history of automation: A mechanical Jacquard loom, often regarded as a key step in the history of computing hardware because of the way it used punched cards to control operations. A mysterious-looking arithmometer, the first digital mechanical calculator reliable enough to be used at the office to automate mathematical calculations. A Morse code telegraph, the first invention to effectively exploit electromagnetism for long-distance communication and thus a pioneer of digital communication. A cybernetic model from 1956 (see further below) and the first ‘portable’ computer.
Released in 1981 by Osborne Computer Corporation, the Osborne 1 was the first commercially successful portable microcomputer. It weighed 10.7 kg (23.5 lb), cost $1,795 USD, had a tiny screen (5-inch/13 cm) and no battery.
At the peak of demand, Osborne was shipping over 10,000 units a month. However, Osborne Computer Corporation shot itself in the foot when they prematurely announced the release of their next generation models. The news put a stop to the sales of the current unit, contributing to throwing the company into bankruptcy. This has comes to be known as the Osborne effect.
Kybernetisches Modell Eier: Die Maus im Labyrinth (Cybernetics Model Eier: The Mouse in the Maze), 1956. Image Kunsthalle Wien
Around 1960, scientists started to build cybernetic machines in order to study artificial intelligence. One of these machines was a maze-solving mouse built by Claude E. Shannon to study the labyrinthian path that a call made using telephone switching systems should take to reach its destination. The device contained a maze that could be arranged to create various paths. The system followed the idea of Ariadne’s thread, the mouse marking each field with the path information, like the Greek mythological figure did when she helped Theseus find his way out of the Minotaur’s labyrinth. Richard Eier later re-built the maze-solving mouse and improved Shannon’s method by replacing the thread with two two-bits memory units.
Régis Mayot, JEANNE & CIE, 2015. Image Kunsthalle Wien
In 2011, the CIAV (the international center for studio glass in Meisenthal, France) invited Régis Mayot to work in their studios. The designer decided to explore the moulds themselves, rather than the objects that were produced using them. By a process of sand moulding, the designer revealed the mechanical beauty of some of these historical tools, producing prints of a selection of moulds that were then blown by craftsmen in glass.
Jeanne et Cie (named after one of the moulds chosen by the designer) highlights how the aesthetics of objects are the result of the industrial instruments and processes that enter into their manufacturing.
Bureau d’études, ME, 2013, © Léonore Bonaccini and Xavier Fourt
Bureau d’Etudes, Electromagnetic Propaganda, 2010
The exhibition also presented a selection of Bureau d´Études‘ intricate and compelling cartographies that visualize covert connections between actors and interests in contemporary political, social and economic systems. Because knowledge is power, the maps are meant as instruments that can be used as part of social movements. The ones displayed at Kunsthalle Wien included the maps of Electro-Magnetic Propaganda, Government of the Agro-Industrial System and the 8th Sphere.
I fell in love with Mark Leckey‘s video. So much that i’ll have to dedicate another post to his work. One day.
David Jourdan, Untitled, 2016, © David Jourdan
David Jourdan’s poster alludes to an ad in which newspaper Der Standard announced that its digital format was ‘almost as good as paper.’
More images from the exhibition:
Magali Reus, Leaves, 2015
Thomas Bayrle, Kleiner koreanischer Wiper
Juan Downey, Nostalgic Item, 1967, Estate of Joan Downey courtesy of Marilys B. Downey, photo: David Avazzadeh
Judith Fegerl, still, 2013, © Judith Fegerl, Courtesy Galerie Hubert Winter, Wien
Wesley Meuris, Biotechnology & Genetic Engineering, 2014. Image Kunsthalle Wien
Installation view The Promise of Total Automation. Image Kunsthalle Wien
Installation view. Image Kunsthalle Wien
Installation view. Image Kunsthalle Wien
More images on my flickr album.
Also in the exhibition: Prototype II (after US patent no 6545444 B2) or the quest for free energy.
The Promise of Total Automation was curated by Anne Faucheret. The exhibition is open until 29 May at Kunsthalle Wien in Vienna. Don’t miss it if you’re in the area.
Monday, April 04. 2016
Note: in a time when we'll soon have for the first time a national vote in Switzeralnd about the Revenu de Base Inconditionnel ("Universal Basic Income") --next June, with a low chance of success this time, let's face it--, when people start to speak about the fact that they should get incomes to fuel global corporations with digital data and content of all sorts, when some new technologies could modify the current digital deal, this is a manifesto that is certainly more than interesting to consider. So as its criticism in this paper, as it appears truly complementary.
More generally, thinking the Future in different terms than liberalism is an absolute necessity. Especially in a context where, also as stated, "Automation and unemployment are the future, regardless of any human intervention".
Via Los Angeles Review of Books
-----
By Ian Lowrie
January 8th, 2016
IN THE NEXT FEW DECADES, your job is likely to be automated out of existence. If things keep going at this pace, it will be great news for capitalism. You’ll join the floating global surplus population, used as a threat and cudgel against those “lucky” enough to still be working in one of the few increasingly low-paying roles requiring human input. Existing racial and geographical disparities in standards of living will intensify as high-skill, high-wage, low-control jobs become more rarified and centralized, while the global financial class shrinks and consolidates its power. National borders will continue to be used to control the flow of populations and place migrant workers outside of the law. The environment will continue to be the object of vicious extraction and the dumping ground for the negative externalities of capitalist modes of production.
It doesn’t have to be this way, though. While neoliberal capitalism has been remarkably successful at laying claim to the future, it used to belong to the left — to the party of utopia. Nick Srnicek and Alex Williams’s Inventing the Future argues that the contemporary left must revive its historically central mission of imaginative engagement with futurity. It must refuse the all-too-easy trap of dismissing visions of technological and social progress as neoliberal fantasies. It must seize the contemporary moment of increasing technological sophistication to demand a post-scarcity future where people are no longer obliged to be workers; where production and distribution are democratically delegated to a largely automated infrastructure; where people are free to fish in the afternoon and criticize after dinner. It must combine a utopian imagination with the patient organizational work necessary to wrest the future from the clutches of hegemonic neoliberalism.
Strategies and Tactics
In making such claims, Srnicek and Williams are definitely preaching to the leftist choir, rather than trying to convert the masses. However, this choir is not just the audience for, but also the object of, their most vituperative criticism. Indeed, they spend a great deal of the book arguing that the contemporary left has abandoned strategy, universalism, abstraction, and the hard work of building workable, global alternatives to capitalism. Somewhat condescendingly, they group together the highly variegated field of contemporary leftist tactics and organizational forms under the rubric of “folk politics,” which they argue characterizes a commitment to local, horizontal, and immediate actions. The essentially affective, gestural, and experimental politics of movements such as Occupy, for them, are a retreat from the tradition of serious militant politics, to something like “politics-as-drug-experience.”
Whatever their problems with the psychodynamics of such actions, Srnicek and Williams argue convincingly that localism and small-scale, prefigurative politics are simply inadequate to challenging the ideological dominance of neoliberalism — they are out of step with the actualities of the global capitalist system. While they admire the contemporary left’s commitment to self-interrogation, and its micropolitical dedication to the “complete removal of all forms of oppression,” Srnicek and Williams are ultimately neo-Marxists, committed to the view that “[t]he reality of complex, globalised capitalism is that small interventions consisting of relatively non-scalable actions are highly unlikely to ever be able to reorganise our socioeconomic system.” The antidote to this slow localism, however, is decidedly not fast revolution.
Instead, Inventing the Future insists that the left must learn from the strategies that ushered in the currently ascendant neoliberal hegemony. Inventing the Future doesn’t spend a great deal of time luxuriating in pathos, preferring to learn from their enemies’ successes rather than lament their excesses. Indeed, the most empirically interesting chunk of their book is its careful chronicle of the gradual, stepwise movement of neoliberalism from the “fringe theory” of a small group of radicals to the dominant ideological consensus of contemporary capitalism. They trace the roots of the “neoliberal thought collective” to a diverse range of trends in pre–World War II economic thought, which came together in the establishment of a broad publishing and advocacy network in the 1950s, with the explicit strategic aim of winning the hearts and minds of economists, politicians, and journalists. Ultimately, this strategy paid off in the bloodless neoliberal revolutions during the international crises of Keynesianism that emerged in the 1980s.
What made these putsches successful was not just the neoliberal thought collective’s ability to represent political centrism, rational universalism, and scientific abstraction, but also its commitment to organizational hierarchy, internal secrecy, strategic planning, and the establishment of an infrastructure for ideological diffusion. Indeed, the former is in large part an effect of the latter: by the 1980s, neoliberals had already spent decades engaged in the “long-term redefinition of the possible,” ensuring that the institutional and ideological architecture of neoliberalism was already well in place when the economic crises opened the space for swift, expedient action.
Demands
Srnicek and Williams argue that the left must abandon its naïve-Marxist hopes that, somehow, crisis itself will provide the space for direct action to seize the hegemonic position. Instead, it must learn to play the long game as well. It must concentrate on building institutional frameworks and strategic vision, cultivating its own populist universalism to oppose the elite universalism of neoliberal capital. It must also abandon, in so doing, its fear of organizational closure, hierarchy, and rationality, learning instead to embrace them as critical tactical components of universal politics.
There’s nothing particularly new about Srnicek and Williams’s analysis here, however new the problems they identify with the collapse of the left into particularism and localism may be. For the most part, in their vituperations, they are acting as rather straightforward, if somewhat vernacular, followers of the Italian politician and Marxist theorist Antonio Gramsci. As was Gramsci’s, their political vision is one of slow, organizationally sophisticated, passive revolution against the ideological, political, and economic hegemony of capitalism. The gradual war against neoliberalism they envision involves critique and direct action, but will ultimately be won by the establishment of a post-work counterhegemony.
In putting forward their vision of this organization, they strive to articulate demands that would allow for the integration of a wide range of leftist orientations under one populist framework. Most explicitly, they call for the automation of production and the provision of a basic universal income that would provide each person the opportunity to decide how they want to spend their free time: in short, they are calling for the end of work, and for the ideological architecture that supports it. This demand is both utopian and practical; they more or less convincingly argue that a populist, anti-work, pro-automation platform might allow feminist, antiracist, anticapitalist, environmental, anarchist, and postcolonial struggles to become organized together and reinforce one another. Their demands are universal, but designed to reflect a rational universalism that “integrates difference rather than erasing it.” The universal struggle for the future is a struggle for and around “an empty placeholder that is impossible to fill definitively” or finally: the beginning, not the end, of a conversation.
In demanding full automation of production and a universal basic income, Srnicek and Williams are not being millenarian, not calling for a complete rupture with the present, for a complete dismantling and reconfiguration of contemporary political economy. On the contrary, they argue that “it is imperative […] that [the left’s] vision of a new future be grounded upon actually existing tendencies.” Automation and unemployment are the future, regardless of any human intervention; the momentum may be too great to stop the train, but they argue that we can change tracks, can change the meaning of a future without work. In demanding something like fully automated luxury communism, Srnicek and Williams are ultimately asserting the rights of humanity as a whole to share in the spoils of capitalism.
Criticisms
Inventing the Future emerged to a relatively high level of fanfare from leftist social media. Given the publicity, it is unsurprising that other more “engagé” readers have already advanced trenchant and substantive critiques of the future imagined by Srnicek and Williams. More than a few of these critics have pointed out that, despite their repeated insistence that their post-work future is an ecologically sound one, Srnicek and Williams evince roughly zero self-reflection with respect either to the imbrication of microelectronics with brutally extractive regimes of production, or to their own decidedly antiquated, doctrinaire Marxist understanding of humanity’s relationship towards the nonhuman world. Similarly, the question of what the future might mean in the Anthropocene goes largely unexamined.
More damningly, however, others have pointed out that despite the acknowledged counterintuitiveness of their insistence that we must reclaim European universalism against the proliferation of leftist particularisms, their discussions of postcolonial struggle and critique are incredibly shallow. They are keen to insist that their universalism will embrace rather than flatten difference, that it will be somehow less brutal and oppressive than other forms of European univeralism, but do little of the hard argumentative work necessary to support these claims. While we see the start of an answer in their assertion that the rejection of universal access to discourses of science, progress, and rationality might actually function to cement certain subject-positions’ particularity, this — unfortunately — remains only an assertion. At best, they are being uncharitable to potential allies in refusing to take their arguments seriously; at worst, they are unreflexively replicating the form if not the content of patriarchal, racist, and neocolonial capitalist rationality.
For my part, while I find their aggressive and unapologetic presentation of their universalism somewhat off-putting, their project is somewhat harder to criticize than their book — especially as someone acutely aware of the need for more serious forms of organized thinking about the future if we’re trying to push beyond the horizons offered by the neoliberal consensus.
However, as an anthropologist of the computer and data sciences, it’s hard for me to ignore a curious and rather serious lacuna in their thinking about automaticity, algorithms, and computation. Beyond the automation of work itself, they are keen to argue that with contemporary advances in machine intelligence, the time has come to revisit the planned economy. However, in so doing, they curiously seem to ignore how this form of planning threatens to hive off economic activity from political intervention. Instead of fearing a repeat of the privations that poor planning produced in earlier decades, the left should be more concerned with the forms of control and dispossession successful planning produced. The past decade has seen a wealth of social-theoretical research into contemporary forms of algorithmic rationality and control, which has rather convincingly demonstrated the inescapable partiality of such systems and their tendency to be employed as decidedly undemocratic forms of technocratic management.
Srnicek and Williams, however, seem more or less unaware of, or perhaps uninterested in, such research. At the very least, they are extremely overoptimistic about the democratization and diffusion of expertise that would be required for informed mass control over an economy planned by machine intelligence. I agree with their assertion that “any future left must be as technically fluent as it is politically fluent.” However, their definition of technical fluency is exceptionally narrow, confined to an understanding of the affordances and internal dynamics of technical systems rather than a comprehensive analysis of their ramifications within other social structures and processes. I do not mean to suggest that the democratic application of machine learning and complex systems management is somehow a priori impossible, but rather that Srnicek and Williams do not even seem to see how such systems might pose a challenge to human control over the means of production.
In a very real sense, though, my criticisms should be viewed as a part of the very project proposed in the book. Inventing the Future is unapologetically a manifesto, and a much-overdue clarion call to a seriously disorganized metropolitan left to get its shit together, to start thinking — and arguing — seriously about what is to be done. Manifestos, like demands, need to be pointed enough to inspire, while being vague enough to promote dialogue, argument, dissent, and ultimately action. It’s a hard tightrope to walk, and Srnicek and Williams are not always successful. However, Inventing the Future points towards an altogether more coherent and mature project than does their #ACCELERATE MANIFESTO. It is hard to deny the persuasiveness with which the book puts forward the positive contents of a new and vigorous populism; in demanding full automation and universal basic income from the world system, they also demand the return of utopian thinking and serious organization from the left.
Wednesday, April 08. 2015
Via The Guardian
-----
By Steven Poole
Songdo in South Korea: a ‘smart city’ whose roads and water, waste and electricity systems are dense with electronic sensors. Photograph: Hotaik Sung/Alamy.
A woman drives to the outskirts of the city and steps directly on to a train; her electric car then drives itself off to park and recharge. A man has a heart attack in the street; the emergency services send a drone equipped with a defibrillator to arrive crucial minutes before an ambulance can. A family of flying maintenance robots lives atop an apartment block – able to autonomously repair cracks or leaks and clear leaves from the gutters.
Such utopian, urban visions help drive the “smart city” rhetoric that has, for the past decade or so, been promulgated most energetically by big technology, engineering and consulting companies. The movement is predicated on ubiquitous wireless broadband and the embedding of computerised sensors into the urban fabric, so that bike racks and lamp posts, CCTV and traffic lights, as well as geeky home appliances such as internet fridges and remote-controlled heating systems, become part of the so-called “internet of things” (the global market for which is now estimated at $1.7tn). Better living through biochemistry gives way to a dream of better living through data. You can even take an MSc in Smart Cities at University College, London.
Yet there are dystopian critiques, too, of what this smart city vision might mean for the ordinary citizen. The phrase itself has sparked a rhetorical battle between techno-utopianists and postmodern flâneurs: should the city be an optimised panopticon, or a melting pot of cultures and ideas?
And what role will the citizen play? That of unpaid data-clerk, voluntarily contributing information to an urban database that is monetised by private companies? Is the city-dweller best visualised as a smoothly moving pixel, travelling to work, shops and home again, on a colourful 3D graphic display? Or is the citizen rightfully an unpredictable source of obstreperous demands and assertions of rights? “Why do smart cities offer only improvement?” asks the architect Rem Koolhaas. “Where is the possibility of transgression?”
Smart beginnings: a crowd watches as new, automated traffic lights are erected at Ludgate Circus, London, in 1931. Photograph: Fox Photos/Getty Images
The smart city concept arguably dates back at least as far as the invention of automated traffic lights, which were first deployed in 1922 in Houston, Texas. Leo Hollis, author of Cities Are Good For You, says the one unarguably positive achievement of smart city-style thinking in modern times is the train indicator boards on the London Underground. But in the last decade, thanks to the rise of ubiquitous internet connectivity and the miniaturisation of electronics in such now-common devices as RFID tags, the concept seems to have crystallised into an image of the city as a vast, efficient robot – a vision that originated, according to Adam Greenfield at LSE Cities, with giant technology companies such as IBM, Cisco and Software AG, all of whom hoped to profit from big municipal contracts.
“The notion of the smart city in its full contemporary form appears to have originated within these businesses,” Greenfield notes in his 2013 book Against the Smart City, “rather than with any party, group or individual recognised for their contributions to the theory or practice of urban planning.”
Whole new cities, such as Songdo in South Korea, have already been constructed according to this template. Its buildings have automatic climate control and computerised access; its roads and water, waste and electricity systems are dense with electronic sensors to enable the city’s brain to track and respond to the movement of residents. But such places retain an eerie and half-finished feel to visitors – which perhaps shouldn’t be surprising. According to Antony M Townsend, in his 2013 book Smart Cities, Songdo was originally conceived as “a weapon for fighting trade wars”; the idea was “to entice multinationals to set up Asian operations at Songdo … with lower taxes and less regulation”.
In India, meanwhile, prime minister Narendra Modi has promised to build no fewer than 100 smart cities – a competitive response, in part, to China’s inclusion of smart cities as a central tenet of its grand urban plan. Yet for the near-term at least, the sites of true “smart city creativity” arguably remain the planet’s established metropolises such as London, New York, Barcelona and San Francisco. Indeed, many people think London is the smartest city of them all just now — Duncan Wilson of Intel calls it a “living lab” for tech experiments.
So what challenges face technologists hoping to weave cutting-edge networks and gadgets into centuries-old streets and deeply ingrained social habits and patterns of movement? This was the central theme of the recent “Re.Work Future Cities Summit” in London’s Docklands – for which two-day public tickets ran to an eye-watering £600.
The event was structured like a fast-cutting series of TED talks, with 15-minute investor-friendly presentations on everything from “emotional cartography” to biologically inspired buildings. Not one non-Apple-branded laptop could be spotted among the audience, and at least one attendee was seen confidently sporting the telltale fat cyan arm of Google Glass on his head.
“Instead of a smart phone, I want you all to have a smart drone in your pocket,” said one entertaining robotics researcher, before tossing up into the auditorium a camera-equipped drone that buzzed around like a fist-sized mosquito. Speakers enthused about the transport app Citymapper, and how the city of Zurich is both futuristic and remarkably civilised. People spoke about the “huge opportunity” represented by expanding city budgets for technological “solutions”.
Usman Haque’s project Thingful is billed as a ‘search engine for the internet of things’
Strikingly, though, many of the speakers took care to denigrate the idea of the smart city itself, as though it was a once-fashionable buzzphrase that had outlived its usefulness. This was done most entertainingly by Usman Haque, of the urban consultancy Umbrellium. The corporate smart-city rhetoric, he pointed out, was all about efficiency, optimisation, predictability, convenience and security. “You’ll be able to get to work on time; there’ll be a seamless shopping experience, safety through cameras, et cetera. Well, all these things make a city bearable, but they don’t make a city valuable.”
As the tech companies bid for contracts, Haque observed, the real target of their advertising is clear: “The people it really speaks to are the city managers who can say, ‘It wasn’t me who made the decision, it was the data.’”
Of course, these speakers who rejected the corporate, top-down idea of the smart city were themselves demonstrating their own technological initiatives to make the city, well, smarter. Haque’s project Thingful, for example, is billed as a search engine for the internet of things. It could be used in the morning by a cycle commuter: glancing at a personalised dashboard of local data, she could check local pollution levels and traffic, and whether there are bikes in the nearby cycle-hire rack.
“The smart city was the wrong idea pitched in the wrong way to the wrong people,” suggested Dan Hill, of urban innovators the Future Cities Catapult. “It never answered the question: ‘How is it tangibly, materially going to affect the way people live, work, and play?’” (His own work includes Cities Unlocked, an innovative smartphone audio interface that can help visually impaired people navigate the streets.) Hill is involved with Manchester’s current smart city initiative, which includes apparently unglamorous things like overhauling the Oxford Road corridor – a bit of “horrible urban fabric”. This “smart stuff”, Hill tells me, “is no longer just IT – or rather IT is too important to be called IT any more. It’s so important you can’t really ghettoise it in an IT city. A smart city might be a low-carbon city, or a city that’s easy to move around, or a city with jobs and housing. Manchester has recognised that.”
One take-home message of the conference seemed to be that whatever the smart city might be, it will be acceptable as long as it emerges from the ground up: what Hill calls “the bottom-up or citizen-led approach”. But of course, the things that enable that approach – a vast network of sensors amounting to millions of electronic ears, eyes and noses – also potentially enable the future city to be a vast arena of perfect and permanent surveillance by whomever has access to the data feeds.
Inside Rio de Janeiro’s centre of operations: ‘a high-precision control panel for the entire city’. Photograph: David Levene
One only has to look at the hi-tech nerve centre that IBM built for Rio de Janeiro to see this Nineteen Eighty-Four-style vision already alarmingly realised. It is festooned with screens like a Nasa Mission Control for the city. As Townsend writes: “What began as a tool to predict rain and manage flood response morphed into a high-precision control panel for the entire city.” He quotes Rio’s mayor, Eduardo Paes, as boasting: “The operations centre allows us to have people looking into every corner of the city, 24 hours a day, seven days a week.”
What’s more, if an entire city has an “operating system”, what happens when it goes wrong? The one thing that is certain about software is that it crashes. The smart city, according to Hollis, is really just a “perpetual beta city”. We can be sure that accidents will happen – driverless cars will crash; bugs will take down whole transport subsystems or the electricity grid; drones could hit passenger aircraft. How smart will the architects of the smart city look then?
A less intrusive way to make a city smarter might be to give those who govern it a way to try out their decisions in virtual reality before inflicting them on live humans. This is the idea behind city-simulation company Simudyne, whose projects include detailed computerised models for planning earthquake response or hospital evacuation. It’s like the strategy game SimCity – for real cities. And indeed Simudyne now draws a lot of its talent from the world of videogames. “When we started, we were just mathematicians,” explains Justin Lyon, Simudyne’s CEO. “People would look at our simulations and joke that they were inscrutable. So five or six years ago we developed a new system which allows you to make visualisations – pretty pictures.” The simulation can now be run as an immersive first-person gameworld, or as a top-down SimCity-style view, where “you can literally drop policy on to the playing area”.
Another serious use of “pretty pictures” is exemplified by the work of ScanLAB Projects, which uses Lidar and ground-penetrating radar to make 3D visualisations of real places. They can be used for art installations and entertainment: for example, mapping underground ancient Rome for the BBC. But the way an area has been used over time, both above and below ground, can also be presented as a layered historical palimpsest, which can serve the purposes of archaeological justice and memory – as with ScanLAB’s Living Death Camps project with Forensic Architecture, on two concentration-camp sites in the former Yugoslavia.
The former German pavilion at Staro Sajmište, Belgrade – produced from terrestrial laser scanning and ground-penetrating radar as part of the Living Death Camps project. Photograph: ScanLAB Projects
For Simudyne’s simulations, meanwhile, the visualisations work to “gamify” the underlying algorithms and data, so that anyone can play with the initial conditions and watch the consequences unfold. Will there one day be convergence between this kind of thing and the elaborately realistic modelled cities that are built for commercial videogames? “There’s absolutely convergence,” Lyon says. A state-of-the art urban virtual reality such as the recreation of Chicago in this year’s game Watch Dogs requires a budget that runs to scores of millions of dollars. But, Lyon foresees, “Ten years from now, what we see in Watch Dogs today will be very inexpensive.”
What if you could travel through a visually convincing city simulation wearing the VR headset, Oculus Rift? When Lyon first tried one, he says, “Everything changed for me.” Which prompts the uncomfortable thought that when such simulations are indistinguishable from the real thing (apart from the zero possibility of being mugged), some people might prefer to spend their days in them. The smartest city of the future could exist only in our heads, as we spend all our time plugged into a virtual metropolitan reality that is so much better than anything physically built, and fail to notice as the world around us crumbles.
In the meantime, when you hear that cities are being modelled down to individual people – or what in the model are called “agents” – you might still feel a jolt of the uncanny, and insist that free-will makes your actions in the city unpredictable. To which Lyon replies: “They’re absolutely right as individuals, but collectively they’re wrong. While I can’t predict what you are going to do tomorrow, I can have, with some degree of confidence, a sense of what the crowd is going to do, what a group of people is going to do. Plus, if you’re pulling in data all the time, you use that to inform the data of the virtual humans.
“Let’s say there are 30 million people in London: you can have a simulation of all 30 million people that very closely mirrors but is not an exact replica of London. You have the 30 million agents, and then let’s have a business-as-usual normal commute, let’s have a snowstorm, let’s shut down a couple of train lines, or have a terrorist incident, an earthquake, and so on.” Lyons says you will get a highly accurate sense of how people, en masse, will respond to these scenarios. “While I’m not interested in a specific individual, I’m interested in the emergent behaviour of the crowd.”
City-simulation company Simudyne creates computerised models ‘with pretty pictures’ to aid disaster-response planning
But what about more nefarious bodies who are interested in specific individuals? As citizens stumble into a future where they will be walking around a city dense with sensors, cameras and drones tracking their every movement – even whether they are smiling (as has already been tested at the Cheltenham Jazz Festival) or feeling gloomy – there is a ticking time-bomb of arguments about surveillance and privacy that will dwarf any previous conversations about Facebook or even, perhaps, government intelligence agencies scanning our email. Unavoidable advertising spam everywhere you go, as in Minority Report, is just the most obvious potential annoyance. (There have already been “smart billboards” that recognised Minis driving past and said hello to them.) The smart city might be a place like Rio on steroids, where you can never disappear.
“If you have a mobile phone, and the right sensors are deployed across the city, people have demonstrated the ability to track those individual phones,” Lyon points out. “And there’s nothing that would prevent you from visualising that movement in a SimCity-like landscape, like in Watch Dogs where you see an avatar moving through the city and you can call up their social-media profile. If you’re trying to search a very large dataset about how someone’s moving, it’s very hard to get your head around it, but as soon as you fire up a game-style visualisation, it’s very easy to see, ‘Oh, that’s where they live, that’s where they work, that’s where their mistress must be, that’s where they go to drink a lot.’”
This is potentially an issue with open-data initiatives such as those currently under way in Bristol and Manchester, which is making publicly available the data it holds about city parking, procurement and planning, public toilets and the fire service. The democratic motivation of this strand of smart-city thinking seems unimpugnable: the creation of municipal datasets is funded by taxes on citizens, so citizens ought to have the right to use them. When presented in the right way – “curated”, if you will, by the city itself, with a sense of local character – such information can help to bring “place back into the digital world”, says Mike Rawlinson of consultancy City ID, which is working with Bristol on such plans.
But how safe is open data? It has already been demonstrated, for instance, that the openly accessible data of London’s cycle-hire scheme can be used to track individual cyclists. “There is the potential to see it all as Big Brother,” Rawlinson says. “If you’re releasing data and people are reusing it, under what purpose and authorship are they doing so?” There needs, Hill says, to be a “reframed social contract”.
The interface of Simudyne’s City Hospital EvacSim
Sometimes, at least, there are good reasons to track particular individuals. Simudyne’s hospital-evacuation model, for example, needs to be tied in to real data. “Those little people that you see [on screen], those are real people, that’s linking to the patient database,” Lyon explains – because, for example, “we need to be able to track this poor child that’s been burned.” But tracking everyone is a different matter: “There could well be a backlash of people wanting literally to go off-grid,” Rawlinson says. Disgruntled smart citizens, unite: you have nothing to lose but your phones.
In truth, competing visions of the smart city are proxies for competing visions of society, and in particular about who holds power in society. “In the end, the smart city will destroy democracy,” Hollis warns. “Like Google, they’ll have enough data not to have to ask you what you want.”
You sometimes see in the smart city’s prophets a kind of casual assumption that politics as we know it is over. One enthusiastic presenter at the Future Cities Summit went so far as to say, with a shrug: “Internet eats everything, and internet will eat government.” In another presentation, about a new kind of “autocatalytic paint” for street furniture that “eats” noxious pollutants such as nitrous oxide, an engineer in a video clip complained: “No one really owns pollution as a problem.” Except that national and local governments do already own pollution as a problem, and have the power to tax and regulate it. Replacing them with smart paint ain’t necessarily the smartest thing to do.
And while some tech-boosters celebrate the power of companies such as Über – the smartphone-based unlicensed-taxi service now banned in Spain and New Delhi, and being sued in several US states – to “disrupt” existing transport infrastructure, Hill asks reasonably: “That Californian ideology that underlies that user experience, should it really be copy-pasted all over the world? Let’s not throw away the idea of universal service that Transport for London adheres to.”
Perhaps the smartest of smart city projects needn’t depend exclusively – or even at all – on sensors and computers. At Future Cities, Julia Alexander of Siemens nominated as one of the “smartest” cities in the world the once-notorious Medellin in Colombia, site of innumerable gang murders a few decades ago. Its problem favelas were reintegrated into the city not with smartphones but with publicly funded sports facilities and a cable car connecting them to the city. “All of a sudden,” Alexander said, “you’ve got communities interacting” in a way they never had before. Last year, Medellin – now the oft-cited poster child for “social urbanism” – was named the most innovative city in the world by the Urban Land Institute.
One sceptical observer of many presentations at the Future Cities Summit, Jonathan Rez of the University of New South Wales, suggests that “a smarter way” to build cities “might be for architects and urban planners to have psychologists and ethnographers on the team.” That would certainly be one way to acquire a better understanding of what technologists call the “end user” – in this case, the citizen. After all, as one of the tribunes asks the crowd in Shakespeare’s Coriolanus: “What is the city but the people?”
Monday, April 28. 2014
Tiny robots build tiny architectures.... (min. 1.10 & 1.50). Another DARPA project.
Via Dvice (and Bruno Samper)
-----
More about it HERE.
Thursday, April 17. 2014
Via Computed·Blg via PCWorld
-----
When Jules Verne wrote Around the World in Eighty Days, this probably isn’t what he had in mind: Google’s Project Loon announced last week one of its balloons had circumnavigated the Earth in 22 days.
Granted, we’re not talking a grand tour of the world here: The balloon flew in a loop over the open ocean surrounding Antarctica, starting at New Zealand. According to the Project Loon team, it was the latest accomplishment for the balloon fleet, which just achieved 500,000 kilometers of flight.
While it may seem like fun and games, Project Loon’s larger goal is to use high-altitude balloons to “connect people in rural and remote areas, help fill coverage gaps, and bring people back online after disasters.”
Currently, the project is test-flying balloons to learn more about wind patterns, and to test its balloon designs. In the past nine months, the project team has used data it’s accumulated during test flights to “refine our prediction models and are now able to forecast balloon trajectories twice as far in advance.”
It also modified the balloon’s air pump (which pumps air in and out of the balloon) to operate more efficiently, which in turn helped the balloon stay on course in this latest test run.
Project Loon’s next step toward universal Internet connection is to create “a ring of uninterrupted connectivity around the 40th southern parallel,” which it expects to pull off sometime this year.
Friday, February 28. 2014
It looks like managing a "smart" city is similar to a moon mission! IBM Intelligent Operations Center in Rio de Janeiro.
Via Metropolis
-----
IBM, INTELLIGENT OPERATIONS CENTER, RIO DE JANEIRO
At the Intelligent Operations Center in Rio, workers manage the city from behind a giant wall of screens, which beam them data on how the city is doing— from the level of water in a street following a rainstorm to a recent mugging or a developing traffic jam. As the home to both the 2014 World Cup and the 2016 Olympics, the city hopes to prove it can be in control of itself, even under pressure. And IBM hopes to prove the power of its new Smarter Cities software to a global audience.
And an intersting post, long and detailed (including regarding recent IBM, CISCO, Siemens "solutions" and operations), about smart cities in the same article, by Alex Marshall:
"The smart-city movement spreading around the globe raises serious concerns about who controls the information, and for what purpose."
More about it HERE.
Wednesday, February 26. 2014
Three years ago we published a post by Nicolas Nova about Salvator Allende's project Cybersyn. A trial to build a cybernetic society (including feedbacks from the chilean population) back in the early 70ies.
Here is another article and picture piece about this amazing projetc on Frieze. You'll need to buy the magazione to see the pictures, though!
-----
Via Frieze
Phograph of Cybersyn, Salvador Allende's attempt to create a 'socialist internet, decades ahead of its time'
This is a tantalizing glimpse of a world that could have been our world. What we are looking at is the heart of the Cybersyn system, created for Salvador Allende’s socialist Chilean government by the British cybernetician Stafford Beer. Beer’s ambition was to ‘implant an electronic nervous system’ into Chile. With its network of telex machines and other communication devices, Cybersyn was to be – in the words of Andy Beckett, author of Pinochet in Piccadilly (2003) – a ‘socialist internet, decades ahead of its time’.
Capitalist propagandists claimed that this was a Big Brother-style surveillance system, but the aim was exactly the opposite: Beer and Allende wanted a network that would allow workers unprecedented levels of control over their own lives. Instead of commanding from on high, the government would be able to respond to up-to-the-minute information coming from factories. Yet Cybersyn was envisaged as much more than a system for relaying economic data: it was also hoped that it would eventually allow the population to instantaneously communicate its feelings about decisions the government had taken.
In 1973, General Pinochet’s cia-backed military coup brutally overthrew Allende’s government. The stakes couldn’t have been higher. It wasn’t only that a new model of socialism was defeated in Chile; the defeat immediately cleared the ground for Chile to become the testing-ground for the neoliberal version of capitalism. The military takeover was swiftly followed by the widespread torture and terrorization of Allende’s supporters, alongside a massive programme of privatization and de-regulation. One world was destroyed before it could really be born; another world – the world in which there is no alternative to capitalism, our world, the world of capitalist realism – started to emerge.
There’s an aching poignancy in this image of Cybersyn now, when the pathological effects of communicative capitalism’s always-on cyberblitz are becoming increasingly apparent. Cloaked in a rhetoric of inclusion and participation, semio-capitalism keeps us in a state of permanent anxiety. But Cybersyn reminds us that this is not an inherent feature of communications technology. A whole other use of cybernetic sytems is possible. Perhaps, rather than being some fragment of a lost world, Cybersyn is a glimpse of a future that can still happen.
Monday, June 17. 2013
An interesting conference that will take place at the ETHZ CAAD department next July that I'm fowarding here:
---------------
Via DARCH - ETHZ
By Manuel Kretzer
Dear friends, colleagues and students,
I'm happy to invite you to join us for the - international symposium on adaptive architecture
The full day event will be take place on July 8th, 2013 / 9:00 - 18:00 at the Chair for Computer Aided Architectural Design ETH Zürich-Hönggerberg, HPZ Floor F.
Speakers include: Prof. Ludger Hovestadt (ETH Zürich, CH) | Prof. Philip Beesley (University of Waterloo, CA) | Prof. Kas Oosterhuis (TU Delft, NL) Martina Decker (DeckerYeadon, US) | Claudia Pasquero (ecoLogicStudio, UK) | Manuel Kretzer (ETH Zürich, CH) Tomasz Jaskiewicz (TU Delft, NL) | Jason Bruges (Jason Bruges Studio, UK) | Areti Markopoulou (IAAC, ES) | Ruairi Glynn (UCL, UK) Simon Schleicher (Universität Stuttgart, DE) | John Sarik (Columbia University, US) | Stefan Dulman (Hive Systems, NL)
More info on the speakers, the detailed program, location and registration can be found on the event's website and the attached flyer. www.alive2013.wordpress.com
The symposium is free of charge however registration until July 3rd, 2013 is obligatory. Seats are limited. http://alive13.eventbrite.com
The event is organised by Manuel Kretzer and Tomasz Jaskiewicz, hosted by the Chair for CAAD and supported through the Swiss National Science Foundation.
Wednesday, May 08. 2013
Via Slash Gear via Computed·Blg
-----
We’ve been hearing a lot about Google‘s self-driving car lately, and we’re all probably wanting to know how exactly the search giant is able to construct such a thing and drive itself without hitting anything or anyone. A new photo has surfaced that demonstrates what Google’s self-driving vehicles see while they’re out on the town, and it looks rather frightening.
The image was tweeted by Idealab founder Bill Gross, along with a claim that the self-driving car collects almost 1GB of data every second (yes, every second). This data includes imagery of the cars surroundings in order to effectively and safely navigate roads. The image shows that the car sees its surroundings through an infrared-like camera sensor, and it even can pick out people walking on the sidewalk.
Of course, 1GB of data every second isn’t too surprising when you consider that the car has to get a 360-degree image of its surroundings at all times. The image we see above even distinguishes different objects by color and shape. For instance, pedestrians are in bright green, cars are shaped like boxes, and the road is in dark blue.
However, we’re not sure where this photo came from, so it could simply be a rendering of someone’s idea of what Google’s self-driving car sees. Either way, Google says that we could see self-driving cars make their way to public roads in the next five years or so, which actually isn’t that far off, and Tesla Motors CEO Elon Musk is even interested in developing self-driving cars as well. However, they certainly don’t come without their problems, and we’re guessing that the first batch of self-driving cars probably won’t be in 100% tip-top shape.
|
