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Tiberius Brastaviceanu

The Baffler - 0 views

  • This tendency to view questions of freedom primarily through the lens of economic competition, to focus on the producer and the entrepreneur at the expense of everyone else, shaped O’Reilly’s thinking about technology.
  • the O’Reilly brand essence is ultimately a story about the hacker as hero, the kid who is playing with technology because he loves it, but one day falls into a situation where he or she is called on to go forth and change the world,
  • His true hero is the hacker-cum-entrepreneur, someone who overcomes the insurmountable obstacles erected by giant corporations and lazy bureaucrats in order to fulfill the American Dream 2.0: start a company, disrupt an industry, coin a buzzword.
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  • gospel of individualism, small government, and market fundamentalism
  • innovation is the new selfishness
  • mastery of public relations
  • making it seem as if the language of economics was, in fact, the only reasonable way to talk about the subject
  • memes are for losers; the real money is in epistemes.
  • “Open source software” was also the first major rebranding exercise overseen by Team O’Reill
  • It’s easy to forget this today, but there was no such idea as open source software before 1998; the concept’s seeming contemporary coherence is the result of clever manipulation and marketing.
  • ideological cleavage between two groups
  • Richard Stallman
  • Free Software Foundation, preoccupied with ensuring that users had rights with respect to their computer programs. Those rights weren’t many—users should be able to run the program for any purpose, to study how it works, to redistribute copies of it, and to release their improved version (if there was one) to the public
  • “free software.”
  • association with “freedom” rather than “free beer”
  • copyleft
  • profound critique of the role that patent law had come to play in stifling innovation and creativity.
  • Plenty of developers contributed to “free software” projects for reasons that had nothing to do with politics. Some, like Linus Torvalds, the Finnish creator of the much-celebrated Linux operating system, did so for fun; some because they wanted to build more convenient software; some because they wanted to learn new and much-demanded skills.
  • Stallman’s rights-talk, however, risked alienating the corporate types
  • he was trying to launch a radical social movement, not a complacent business association
  • By early 1998 several business-minded members of the free software community were ready to split from Stallman, so they masterminded a coup, formed their own advocacy outlet—the Open Source Initiative—and brought in O’Reilly to help them rebrand.
  • “open source”
  • The label “open source” may have been new, but the ideas behind it had been in the air for some time.
  • In those early days, the messaging around open source occasionally bordered on propaganda
  • This budding movement prided itself on not wanting to talk about the ends it was pursuing; except for improving efficiency and decreasing costs, those were left very much undefined.
  • extremely decentralized manner, using Internet platforms, with little central coordination.
  • In contrast to free software, then, open source had no obvious moral component.
  • “open source is not particularly a moral or a legal issue. It’s an engineering issue. I advocate open source, because . . . it leads to better engineering results and better economic results
  • While free software was meant to force developers to lose sleep over ethical dilemmas, open source software was meant to end their insomnia.
  • Stallman the social reformer could wait for decades until his ethical argument for free software prevailed in the public debate
  • O’Reilly the savvy businessman had a much shorter timeline: a quick embrace of open source software by the business community guaranteed steady demand for O’Reilly books and events
  • The coup succeeded. Stallman’s project was marginalized. But O’Reilly and his acolytes didn’t win with better arguments; they won with better PR.
  • A decade after producing a singular vision of the Internet to justify his ideas about the supremacy of the open source paradigm, O’Reilly is close to pulling a similar trick on how we talk about government reform.
  • much of Stallman’s efforts centered on software licenses
  • O’Reilly’s bet wa
  • the “cloud”
  • licenses would cease to matter
  • Since no code changed hands
  • So what did matter about open source? Not “freedom”
  • O’Reilly cared for only one type of freedom: the freedom of developers to distribute software on whatever terms they fancied.
  • the freedom of the producer
  • who must be left to innovate, undisturbed by laws and ethics.
  • The most important freedom,
  • is that which protects “my choice as a creator to give, or not to give, the fruits of my work to you, as a ‘user’ of that work, and for you, as a user, to accept or reject the terms I place on that gift.”
  • O’Reilly opposed this agenda: “I completely support the right of Richard [Stallman] or any individual author to make his or her work available under the terms of the GPL; I balk when they say that others who do not do so are doing something wrong.”
  • The right thing to do, according to O’Reilly, was to leave developers alone.
  • According to this Randian interpretation of open source, the goal of regulation and public advocacy should be to ensure that absolutely nothing—no laws or petty moral considerations—stood in the way of the open source revolution
  • Any move to subject the fruits of developers’ labor to public regulation
  • must be opposed, since it would taint the reputation of open source as technologically and economically superior to proprietary software
  • the advent of the Internet made Stallman’s obsession with licenses obsolete
  • Many developers did stop thinking about licenses, and, having stopped thinking about licenses, they also stopped thinking about broader moral issues that would have remained central to the debates had “open source” not displaced “free software” as the paradigm du jour.
  • Profiting from the term’s ambiguity, O’Reilly and his collaborators likened the “openness” of open source software to the “openness” of the academic enterprise, markets, and free speech.
  • “open to intellectual exchange”
  • “open to competition”
  • “For me, ‘open source’ in the broader sense means any system in which open access to code lowers the barriers to entry into the market”).
  • “Open” allowed O’Reilly to build the largest possible tent for the movement.
  • The language of economics was less alienating than Stallman’s language of ethics; “openness” was the kind of multipurpose term that allowed one to look political while advancing an agenda that had very little to do with politics
  • highlight the competitive advantages of openness.
  • the availability of source code for universal examination soon became the one and only benchmark of openness
  • What the code did was of little importance—the market knows best!—as long as anyone could check it for bugs.
  • The new paradigm was presented as something that went beyond ideology and could attract corporate executives without losing its appeal to the hacker crowd.
  • What Raymond and O’Reilly failed to grasp, or decided to overlook, is that their effort to present open source as non-ideological was underpinned by a powerful ideology of its own—an ideology that worshiped innovation and efficiency at the expense of everything else.
  • What they had in common was disdain for Stallman’s moralizing—barely enough to justify their revolutionary agenda, especially among the hacker crowds who were traditionally suspicious of anyone eager to suck up to the big corporations that aspired to dominate the open source scene.
  • linking this new movement to both the history of the Internet and its future
  • As long as everyone believed that “open source” implied “the Internet” and that “the Internet” implied “open source,” it would be very hard to resist the new paradigm
  • Telling a coherent story about open source required finding some inner logic to the history of the Internet
  • “If you believe me that open source is about Internet-enabled collaboration, rather than just about a particular style of software license,”
  • everything on the Internet was connected to everything else—via open source.
  • The way O’Reilly saw it, many of the key developments of Internet culture were already driven by what he called “open source behavior,” even if such behavior was not codified in licenses.
  • No moralizing (let alone legislation) was needed; the Internet already lived and breathed open source
  • apps might be displacing the browser
  • the openness once taken for granted is no more
  • Openness as a happenstance of market conditions is a very different beast from openness as a guaranteed product of laws.
  • One of the key consequences of linking the Internet to the world of open source was to establish the primacy of the Internet as the new, reinvented desktop
  • This is where the now-forgotten language of “freedom” made a comeback, since it was important to ensure that O’Reilly’s heroic Randian hacker-entrepreneurs were allowed to roam freely.
  • Soon this “freedom to innovate” morphed into “Internet freedom,” so that what we are trying to preserve is the innovative potential of the platform, regardless of the effects on individual users.
  • Lumping everything under the label of “Internet freedom” did have some advantages for those genuinely interested in promoting rights such as freedom of expression
  • Forced to choose between preserving the freedom of the Internet or that of its users, we were supposed to choose the former—because “the Internet” stood for progress and enlightenment.
  • infoware
  • Yahoo
  • their value proposition lay in the information they delivered, not in the software function they executed.
  • The “infoware” buzzword didn’t catch on, so O’Reilly turned to the work of Douglas Engelbart
  • to argue that the Internet could help humanity augment its “collective intelligence” and that, once again, open source software was crucial to this endeavor.
  • Now it was all about Amazon learning from its customers and Google learning from the sites in its index.
  • The idea of the Internet as both a repository and incubator of “collective intelligence”
  • in 2004, O’Reilly and his business partner Dale Dougherty hit on the idea of “Web 2.0.” What did “2.0” mean, exactly?
  • he primary goal was to show that the 2001 market crash did not mean the end of the web and that it was time to put the crash behind us and start learning from those who survived.
  • Tactically, “Web 2.0” could also be much bigger than “open source”; it was the kind of sexy umbrella term that could allow O’Reilly to branch out from boring and highly technical subjects to pulse-quickening futurology
  • O’Reilly couldn’t improve on a concept as sexy as “collective intelligence,” so he kept it as the defining feature of this new phenomenon.
  • What set Web 2.0 apart from Web 1.0, O’Reilly claimed, was the simple fact that those firms that didn’t embrace it went bust
  • find a way to harness collective intelligence and make it part of their business model.
  • By 2007, O’Reilly readily admitted that “Web 2.0 was a pretty crappy name for what’s happening.”
  • O’Reilly eventually stuck a 2.0 label on anything that suited his business plan, running events with titles like “Gov 2.0” and “Where 2.0.” Today, as everyone buys into the 2.0 paradigm, O’Reilly is quietly dropping it
  • assumption that, thanks to the coming of Web 2.0, we are living through unique historical circumstances
  • Take O’Reilly’s musings on “Enterprise 2.0.” What is it, exactly? Well, it’s the same old enterprise—for all we know, it might be making widgets—but now it has learned something from Google and Amazon and found a way to harness “collective intelligence.”
  • tendency to redescribe reality in terms of Internet culture, regardless of how spurious and tenuous the connection might be, is a fine example of what I call “Internet-centrism.”
  • “Open source” gave us the “the Internet,” “the Internet” gave us “Web 2.0,” “Web 2.0” gave us “Enterprise 2.0”: in this version of history, Tim O’Reilly is more important than the European Union
  • For Postman, each human activity—religion, law, marriage, commerce—represents a distinct “semantic environment” with its own tone, purpose, and structure. Stupid talk is relatively harmless; it presents no threat to its semantic environment and doesn’t cross into other ones.
  • Since it mostly consists of falsehoods and opinions
  • it can be easily corrected with facts
  • to say that Tehran is the capital of Iraq is stupid talk
  • Crazy talk, in contrast, challenges a semantic environment, as it “establishes different purposes and assumptions from those we normally accept.” To argue, as some Nazis did, that the German soldiers ended up far more traumatized than their victims is crazy talk.
  • For Postman, one of the main tasks of language is to codify and preserve distinctions among different semantic environments.
  • As he put it, “When language becomes undifferentiated, human situations disintegrate: Science becomes indistinguishable from religion, which becomes indistinguishable from commerce, which becomes indistinguishable from law, and so on.
  • pollution
  • Some words—like “law”—are particularly susceptible to crazy talk, as they mean so many different things: from scientific “laws” to moral “laws” to “laws” of the market to administrative “laws,” the same word captures many different social relations. “Open,” “networks,” and “information” function much like “law” in our own Internet discourse today.
  • For Korzybski, the world has a relational structure that is always in flux; like Heraclitus, who argued that everything flows, Korzybski believed that an object A at time x1 is not the same object as object A at time x2
  • Our language could never properly account for the highly fluid and relational structure of our reality—or as he put it in his most famous aphorism, “the map is not the territory.”
  • Korzybski argued that we relate to our environments through the process of “abstracting,” whereby our neurological limitations always produce an incomplete and very selective summary of the world around us.
  • nothing harmful in this per se—Korzybski simply wanted to make people aware of the highly selective nature of abstracting and give us the tools to detect it in our everyday conversations.
  • Korzybski developed a number of mental tools meant to reveal all the abstracting around us
  • He also encouraged his followers to start using “etc.” at the end of their statements as a way of making them aware of their inherent inability to say everything about a given subject and to promote what he called the “consciousness of abstraction.”
  • There was way too much craziness and bad science in Korzybski’s theories
  • but his basic question
  • “What are the characteristics of language which lead people into making false evaluations of the world around them?”
  • Tim O’Reilly is, perhaps, the most high-profile follower of Korzybski’s theories today.
  • O’Reilly openly acknowledges his debt to Korzybski, listing Science and Sanity among his favorite books
  • It would be a mistake to think that O’Reilly’s linguistic interventions—from “open source” to “Web 2.0”—are random or spontaneous.
  • There is a philosophy to them: a philosophy of knowledge and language inspired by Korzybski. However, O’Reilly deploys Korzybski in much the same way that the advertising industry deploys the latest findings in neuroscience: the goal is not to increase awareness, but to manipulate.
  • O’Reilly, of course, sees his role differently, claiming that all he wants is to make us aware of what earlier commentators may have overlooked. “A metaphor is just that: a way of framing the issues such that people can see something they might otherwise miss,
  • But Korzybski’s point, if fully absorbed, is that a metaphor is primarily a way of framing issues such that we don’t see something we might otherwise see.
  • In public, O’Reilly modestly presents himself as someone who just happens to excel at detecting the “faint signals” of emerging trends. He does so by monitoring a group of überinnovators that he dubs the “alpha geeks.” “The ‘alpha geeks’ show us where technology wants to go. Smart companies follow and support their ingenuity rather than trying to suppress it,
  • His own function is that of an intermediary—someone who ensures that the alpha geeks are heard by the right executives: “The alpha geeks are often a few years ahead of their time. . . . What we do at O’Reilly is watch these folks, learn from them, and try to spread the word by writing down (
  • The name of his company’s blog—O’Reilly Radar—is meant to position him as an independent intellectual who is simply ahead of his peers in grasping the obvious.
  • “the skill of writing is to create a context in which other people can think”
  • As Web 2.0 becomes central to everything, O’Reilly—the world’s biggest exporter of crazy talk—is on a mission to provide the appropriate “context” to every field.
  • In a fascinating essay published in 2000, O’Reilly sheds some light on his modus operandi.
  • The thinker who emerges there is very much at odds with the spirit of objectivity that O’Reilly seeks to cultivate in public
  • meme-engineering lets us organize and shape ideas so that they can be transmitted more effectively, and have the desired effect once they are transmitted
  • O’Reilly meme-engineers a nice euphemism—“meme-engineering”—to describe what has previously been known as “propaganda.”
  • how one can meme-engineer a new meaning for “peer-to-peer” technologies—traditionally associated with piracy—and make them appear friendly and not at all threatening to the entertainment industry.
  • O’Reilly and his acolytes “changed the canonical list of projects that we wanted to hold up as exemplars of the movement,” while also articulating what broader goals the projects on the new list served. He then proceeds to rehash the already familiar narrative: O’Reilly put the Internet at the center of everything, linking some “free software” projects like Apache or Perl to successful Internet start-ups and services. As a result, the movement’s goal was no longer to produce a completely free, independent, and fully functional operating system but to worship at the altar of the Internet gods.
  • Could it be that O’Reilly is right in claiming that “open source” has a history that predates 1998?
  • Seen through the prism of meme-engineering, O’Reilly’s activities look far more sinister.
  • His “correspondents” at O’Reilly Radar don’t work beats; they work memes and epistemes, constantly reframing important public issues in accordance with the templates prophesied by O’Reilly.
  • Or take O’Reilly’s meme-engineering efforts around cyberwarfare.
  • Now, who stands to benefit from “cyberwarfare” being defined more broadly? Could it be those who, like O’Reilly, can’t currently grab a share of the giant pie that is cybersecurity funding?
  • Frank Luntz lists ten rules of effective communication: simplicity, brevity, credibility, consistency, novelty, sound, aspiration, visualization, questioning, and context.
  • Thus, O’Reilly’s meme-engineering efforts usually result in “meme maps,” where the meme to be defined—whether it’s “open source” or “Web 2.0”—is put at the center, while other blob-like terms are drawn as connected to it.
  • The exact nature of these connections is rarely explained in full, but this is all for the better, as the reader might eventually interpret connections with their own agendas in mind. This is why the name of the meme must be as inclusive as possible: you never know who your eventual allies might be. “A big part of meme engineering is giving a name that creates a big tent that a lot of people want to be under, a train that takes a lot of people where they want to go,”
  • News April 4 mail date March 29, 2013 Baffler party March 6, 2013 Žižek on seduction February 13, 2013 More Recent Press I’ve Seen the Worst Memes of My Generation Destroyed by Madness io9, April 02, 2013 The Baffler’s New Colors Imprint, March 21, 2013
  • There is considerable continuity across O’Reilly’s memes—over time, they tend to morph into one another.
Tiberius Brastaviceanu

Innovative schemes for open innovation and science 2.0 INSO-4-2015 - 0 views

  • Topic: Innovative schemes for open innovation and science 2.0 INSO-4-2015
  • open innovation and science 2.0
  • assist universities to become open innovation centres for their region in cooperation with companies, realising the ERA priorities, and to enable public administrations to drive innovation in and through the public sector.
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  • help universities, companies and public authorities to enhance their capacity to engage in science 2.0 and open innovation.
  • effective linkages for innovation between universities and companies and other employment sectors, and provide freely accessible innovation training platforms, including digital platforms. 
  • consortia
  • adopt innovative ways to create new knowledge, new jobs and promote economic growth
  • a). Inter-sectoral mobility
  • b) Academia- Business knowledge co-creation
  • c) Innovation leadership programme for public administrations and researchers
  • a policy of double nominations
  • a policy to further and recognise inter-sectoral mobility
  • This challenge can be addressed through different sets of actions:
    • Tiberius Brastaviceanu
       
      the sub-sections are not addressed at once.
  • develop or (further) implement open innovative schemes to strengthen linkages between academia, industry and community
  • Research institutions together with companies are expected to build sustainable structures which help to absorb needs of users and thereby become co-creators of new solutions.  SMEs should be encouraged to participate.
  • Gender aspects need to be taken into account.
    • Tiberius Brastaviceanu
       
      This is something that really fits SENSORICA. We've been working on this for 2 years now. 
  • developing curricula and providing freely through online platforms, possibly combined with other delivery mechanisms, innovation training for public administrations and researchers.
  •  
    "Topic: Innovative schemes for open innovation and science 2.0 INSO-4-2015"
Tiberius Brastaviceanu

Digital Agenda for Europe - European Commission - 0 views

  • Open Innovation 2.0 Conference and The Dublin Innovation Declaration:
  • The Dublin Innovation Declaration was co-created at the Open Innovation 2.0 Conference
  • he challenges faced in Europe and beyond are too large to tackle in isolation and thus a new approach to innovation is required
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  • create new shared value through innovation
  • creative destruction model where the failure of old approaches fuels the motivation for change and shapes the future
  • quadruple helix model of innovation where civil society joins with business, academia, and government sectors to drive changes far beyond the scope of what any one organization can do on their own. 
Tiberius Brastaviceanu

Business model 2.0 - Google Drive - 0 views

  •  
    a business model for open value networks implemented by SENSORICA
Kurt Laitner

Digital Reality | Edge.org - 0 views

  • When you snap the bricks together, you don't need a ruler to play Lego; the geometry comes from the parts
  • first attribute is metrology that comes from the parts
  • digitizing composites into little linked loops of carbon fiber instead of making giant pieces
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  • In a 3D printer today, what you can make is limited by the size of the machine. The geometry is external
  • is the Lego tower is more accurate than the child because the constraint of assembling the bricks lets you detect and correct errors
  • That's the exponential scaling for working reliably with unreliable parts
  • Because the parts have a discrete state, it means in joining them you can detect and correct errors
  • detect and correct state to correct errors to get an exponential reduction in error, which gives you an exponential increase in complexity
  • The next one is you can join Lego bricks made out of dissimilar materials.
  • The last one is when you're done with Lego you don't put it in the trash; you take it apart and reuse it because there's state in the materials. In a forest there's no trash; you die and your parts get disassembled and you're made into new stuff. When you make a 3D print or laser cut, when you're done there's recycling attempts but there's no real notion of reusing the parts
  • The metrology coming from the parts, detecting and correcting errors, joining dissimilar materials, disconnecting, reusing the components
  • On the very smallest scale, the most exciting work on digital fabrication is the creation of life from scratch. The cell does everything we're talking about. We've had a great collaboration with the Venter Institute on microfluidic machinery to load designer genomes into cells. One step up from that we're developing tabletop chip fab instead of a billion dollar fab, using discrete assembly of blocks of electronic materials to build things like integrated circuits in a tabletop process
  • a child can make a Lego structure bigger than themself
  • There's a series of books by David Gingery on how to make a machine shop starting with charcoal and iron ore.
  • There are twenty amino acids. With those twenty amino acids you make the motors in the molecular muscles in my arm, you make the light sensors in my eye, you make my neural synapses. The way that works is the twenty amino acids don't encode light sensors, or motors. They’re very basic properties like hydrophobic or hydrophilic. With those twenty properties you can make you. In the same sense, digitizing fabrication in the deep sense means that with about twenty building blocks—conducting, insulating, semiconducting, magnetic, dielectric—you can assemble them to create modern technology
  • By discretizing those three parts we can make all those 500,000 resistors, and with a few more parts everything else.
  • Now, there's a casual sense, which means a computer controls something to make something, and then there's the deep sense, which is coding the materials. Intellectually, that difference is everything but now I'm going to explain why it doesn't matter.
  • Then in turn, the next surprise was they weren't there for research, they weren't there for theses, they wanted to make stuff. I taught additive, subtractive, 2D, 3D, form, function, circuits, programming, all of these skills, not to do the research but just using the existing machines today
  • What they were answering was the killer app for digital fabrication is personal fabrication, meaning, not making what you can buy at Walmart, it’s making what you can't buy in Walmart, making things for a market of one person
  • The minicomputer industry completely misread PCs
  • the Altair was life changing for people like me. It was the first computer you could own as an individual. But it was almost useless
  • It was hard to use but it brought the cost from a million dollars to 100,000 and the size from a warehouse down to a room. What that meant is a workgroup could have one. When a workgroup can have one it meant Ken Thompson and Dennis Ritchie at Bell Labs could invent UNIX—which all modern operating systems descend from—because they didn't have to get permission from a whole corporation to do it
  • At the PC stage what happened is graphics, storage, processing, IO, all of the subsystems got put in a box
  • To line that up with fabrication, MIT's 1952 NC Mill is similar to the million-dollar machines in my lab today. These are the mainframes of fab. You need a big organization to have them. The fab labs I'll tell you about are exactly analogous to the cost and complexity of minicomputers. The machines that make machines I'll tell you about are exactly analogous to the cost and complexity of the hobbyist computers. The research we're doing, which is leading up to the Star Trek Replicator, is what leads to the personal fabricator, which is the integrated unit that makes everything
  • conducting, resistive, insulating.
  • The fab lab is 2 tons, a $100,000 investment. It fills a few thousand square feet, 3D scanning and printing, precision machining, you can make circuit boards, molding and casting tooling, computer controlled cutting with a knife, with a laser, large format machining, composite layup, surface mount rework, sensors, actuators, embedded programming— technology to make technology.
  • Ten years you can just plot this doubling. Today, you can send a design to a fab lab and you need ten different machines to turn the data into something. Twenty years from now, all of that will be in one machine that fits in your pocket.
  • We've been living with this notion that making stuff is an illiberal art for commercial gain and it's not part of the means of expression. But, in fact, today, 3D printing, micromachining, and microcontroller programming are as expressive as painting paintings or writing sonnets but they're not means of expression from the Renaissance. We can finally fix that boundary between art and artisans
  • You don't go to a fab lab to get access to the machine; you go to the fab lab to make the machine.
  • Over the next maybe five years we'll be transitioning from buying machines to using machines to make machines. Self-reproducing machines
  • But they still have consumables like the motors, and they still cut or squirt. Then the interesting transition comes when we go from cutting or printing to assembling and disassembling, to moving to discretely assembled materials
  • because if anybody can make anything anywhere, it challenges everything
    • Kurt Laitner
       
      great quote (replace challenges with changes for effect)
  • Now, the biggest surprise for me in this is I thought the research was hard. It's leading to how to make the Star Trek Replicator. The insight now is that's an exercise in embodied computation—computation in materials, programming their construction. Lots of work to come, but we know what to do
  • And that's when you do tabletop chip fab or make airplanes. That's when technical trash goes away because you can disassemble. 
  • irritated by the maker movement for the failure in mentoring
  • At something like a Maker Faire, there's hall after hall of repeated reinventions of bad 3D printers and there isn't an easy process to take people from easy to hard
  • We started a project out of desperation because we kept failing to succeed in working with existing schools, called the Fab Academy. Now, to understand how that works, MIT is based on scarcity. You assume books are scarce, so you have to go there for the library; you assume tools are scarce, so you have to go there for the machines; you assume people are scarce, so you have to go there to see them; and geography is scarce. It adds up to we can fit a few thousand people at a time. For those few thousand people it works really well. But the planet is a few billion people. We're off by six orders of magnitude. 
  • Next year we're starting a new class with George Church that we've called "How to Grow Almost Anything", which is using fab labs to make bio labs and then teach biotech in it. What we're doing is we're making a new global kind of university
  • Amusingly, I went to my friends at Educause about accrediting the Fab Academy and they said, "We love it. Where are you located?" And I said, "Yes" and they said, "No." Meaning, "We're all over the earth." And they said, "We have no mechanism. We're not allowed to do that. There's no notion of global accreditation."
  • Then they said something really helpful: "Pretend."
  • Once you have a basic set of tools, you can make all the rest of the tools
  • The way the Fab Academy works, in computing terms, it's like the Internet. Students have peers in workgroups, with mentors, surrounded by machines in labs locally. Then we connect them globally by video and content sharing and all of that. It's an educational network. There are these critical masses of groups locally and then we connect them globally
  • You still have Microsoft or IBM now but, with all respect to colleagues there, arguably that's the least interesting part of software
  • To understand the economic and social implications, look at software and look at music to understand what's happening now for fabrication
  • There's a core set of skills a place like MIT can do but it alone doesn't scale to a billion people. This is taking the social engineering—the character of MIT—but now doing it on this global scale.
  • Mainframes didn't go away but what opened up is all these tiers of software development that weren't economically viable
  • If you look at music development, the most interesting stuff in music isn't the big labels, it's all the tiers of music that weren't viable before
  • You can make music for yourself, for one, ten, 100, 1,000, a million. If you look at the tracks on your device, music is now in tiers that weren't economically viable before. In that example it's a string of data and it becomes a sound. Now in digital fab, it's a string of data and it becomes a thing.
  • What is work? For the average person—not the people who write for Edge, but just an average person working—you leave home to go to a place you'd rather not be, doing a repetitive operation you'd rather not do, making something designed by somebody you don't know for somebody you'll never see, to get money to then go home and buy something. But what if you could skip that and just make the thing?
    • Kurt Laitner
       
      !!!
  • It took about ten years for the dot com industry to realize pretty much across the board you don't directly sell the thing. You sell the benefits of the thing
  • 2016 it's in Shenzhen because they're pivoting from mass manufacturing to enabling personal fabrication. We've set Shenzhen as the goal in 2016 for Fab Lab 2.0, which is fab labs making fab labs
  • To rewind now, you can send something to Shenzhen and mass manufacture it. There's a more interesting thing you can do, which is you go to market by shipping data and you produce it on demand locally, and so you produce it all around the world.
  • But their point was a lot of printers producing beautiful pages slowly scales if all the pages are different
  • In the same sense it scales to fabricate globally by doing it locally, not by shipping the products but shipping the data.
  • It doesn't replace mass manufacturing but mass manufacturing becomes the least interesting stuff where everybody needs the same thing. Instead, what you open up is all these tiers that weren't viable before
  • There, they consider IKEA the enemy because IKEA defines your taste. Far away they make furniture and flat pack it and send it to a big box store. Great design sense in Barcelona, but 50 percent youth unemployment. A whole generation can't work. Limited jobs. But ships come in from the harbor, you buy stuff in a big box store. And then after a while, trucks go off to a trash dump. They describe it as products in, trash out. Ships come in with products, trash goes out
    • Kurt Laitner
       
      worse actually.. the trash stays
  • The bits come and go, globally connected for knowledge, but the atoms stay in the city.
  • instead of working to get money to buy products made somewhere else, you can make them locally
    • Kurt Laitner
       
      this may solve greece's problem, walk away from debt, you can't buy other people's (country's) stuff anymore, so make it all yourself
  • The biggest tool is a ShotBot 4'x8'x1' NC mill, and you can make beautiful furniture with it. That's what furniture shops use
  • Anything IKEA makes you can make in a fab lab
  • it means you can make many of the things you consume directly rather than this very odd remote economic loop
  • the most interesting part of the DIY phone projects is if you're making a do-it-yourself phone, you can also start to make the things that the phones talk to. You can start to build your own telco providers where the users provide the network rather than spending lots of money on AT&T or whoever
  • Traditional manufacturing is exactly replaying the script of the computer companies saying, "That's a toy," and it's shining a light to say this creates entirely new economic activity. The new jobs don't come back to the old factories. The ability to make stuff on demand is creating entirely new jobs
  • To keep playing that forward, when I was in Barcelona for the meeting of all these labs hosted by the city architect and the city, the mayor, Xavier Trias, pushed a button that started a forty-year countdown to self-sufficiency. Not protectionism
  • I need high-torque efficient motors with integrated lead screws at low cost, custom-produced on demand. All sorts of the building blocks that let us do what I'm doing currently rest on a global supply chain including China's manufacturing agility
  • The short-term answer is you can't get rid of them because we need them in the supply chain. But the long-term answer is Shenzhen sees the future isn't mass producing for everybody. That's a transitional stage to producing locally
  • My description of MIT's core competence is it's a safe place for strange people
  • The real thing ultimately that's driving the fab labs ... the vacuum we filled is a technical one. The means to make stuff. Nobody was providing that. But in turn, the spaces become magnets. Everybody talks about innovation or knowledge economy, but then most things that label that strangle it. The labs become vehicles for bright inventive people who don't fit locally. You can think about the culture of MIT but on this global scale
  • My allegiance isn't to any one border, it's to the brainpower of the planet and this is building the infrastructure to scale to that brainpower
  • If you zoom from transistors to microcode to object code to a program, they don't look like each other. But if we take this room and go from city, state, country, it's hierarchical but you preserve geometry
  • Computation violates geometry unlike most anything else we do
  • The reason that's so important for the digital fabrication piece is once we build molecular assemblers to build arbitrary systems, you don't want to then paste a few lines of code in it. You need to overlay computation with geometry. It's leading to this complete do-over of computer science
  • If you take digital fab, plus the real sense of Internet of Things—not the garbled sense—plus the real future of computing aligning hardware and software, it all adds up to this ability to program reality
  • I run a giant video infrastructure and I have collaborators all over the world that I see more than many of my colleagues at MIT because we're all too busy on campus. The next Silicon Valley is a network, it's not a place. Invention happens in these networks.
  • When Edwin Land was kicked out of Polaroid, he made the Rowland Institute, which was making an ideal research institute with the best facilities and the best people and they could do whatever they want. But almost nothing came from it because there was no turnover of the gene pool, there was no evolutionary pressure.  
  • the wrong way to do research, which is to believe there's a privileged set of people that know more than anybody else and to create a barrier that inhibits communication from the inside to the outside
  • you need evolutionary pressure, you need traffic, you need to be forced to deal with people you don't think you need to encounter, and you need to recognize that to be disruptive it helps to know what people know
  • For me the hardest thing isn't the research. That's humming along nicely. It's that we're finding we have to build a completely new kind of social order and that social entrepreneurship—figuring out how you live, learn, work, play—is hard and there's a very small set of people who can do that kind of organizational creation.
    • Kurt Laitner
       
      our challenge in the OVN space
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    what is heavy is local, what is light is global, and increasingly manufacturing is being recreated along this principle
mayssamd

The MediLedger Network - 1 views

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    The MediLedger Network is the industry network 2.0 for the life sciences and healthcare industry, that runs solutions for real-time alignment, rule enforcement and settlement of transactions directly between trading partners
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