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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
  •  
    what is heavy is local, what is light is global, and increasingly manufacturing is being recreated along this principle
Tiberius Brastaviceanu

Innovation Canada: A Call to Action - Review of Federal Support to Research and Develop... - 1 views

  • Canada has a solid foundation on which to build success as a leader in the knowledge economy of tomorrow
  • innovation in Canada lags behind other highly developed countries
  • innovation is the ultimate source of the long-term competitiveness of businesses and the quality of life of Canadians
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  • We heard that the government should be more focussed on helping innovative firms to grow and, particularly, on serving the needs of small and medium-sized enterprises (SMEs)
  • greater cooperation with provincial programs
  • innovation support is too narrowly focussed on R&D – more support is needed for other activities along the continuum from ideas to commercially useful innovation
  • more productive and internationally competitive economy
  • whole-of-government program delivery vehicle – the Industrial Research and Innovation Council (IRIC)
  • SR&ED program should be simplified
  • includes non-labour costs, such as materials and capital equipment, the calculation of which can be highly complex
  • the base for the tax credit should be labour-related costs, and the tax credit rate should be adjusted upward
  • fund direct support measures for SMEs
  • promoting the growth of firms
  • facilitating access by such firms to an increased supply of risk capital at both the start-up and later stages of their growth.
  • building public–private research collaborations
  • National Research Council (NRC) should become independent collaborative research organizations
  • become affiliates of universities
  • create opportunity and demand for leading-edge goods
  • encouragement of innovation in the Canadian economy should become a stated objective of procurement policies and programs.
  • the government needs to establish business innovation as a whole-of-government priority
  • put innovation at the centre of the government's economic strategy
  • Innovation Advisory Committee (IAC) – a body with a whole-of-government focus that would oversee the realization of our proposed action plan, as well as serve as a permanent mechanism to promote the refinement and improvement of the government's business innovation programs going forward.
  • focus resources where market forces are unlikely to operate effectively or efficiently and, in that context, address the full range of business innovation activities, including research, development, commercialization and collaboration with other key actors in the innovation ecosystem
  • the closer the activity being supported is to market, and therefore the more likely it is that the recipient firm will capture most of the benefit for itself.
  • specific sectors
  • of strategic importance
  • concentrated in particular regions
  • succeed in the arena of global competition
    • Tiberius Brastaviceanu
       
      They don't go beyond the firm
    • Tiberius Brastaviceanu
       
      they are still stuck in the competitive paradigm
    • Tiberius Brastaviceanu
       
      Still stack with the old paradigm of the "knowledge economy"  http://en.wikipedia.org/wiki/Knowledge_economy  My opinion is that we're moving into a know-how economy. 
Tiberius Brastaviceanu

The New Normal in Funding University Science | Issues in Science and Technology - 1 views

  • Government funding for academic research will remain limited, and competition for grants will remain high. Broad adjustments will be needed
  • he sequester simply makes acute a chronic condition that has been getting worse for years.
  • the federal budget sequester
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  • systemic problems that arise from the R&D funding system and incentive structure that the federal government put in place after World War II
  • Researchers across the country encounter increasingly fierce competition for money.
  • unding rates in many National Institutes of Health (NIH) and National Science Foundation (NSF) programs are now at historical lows, declining from more than 30% before 2001 to 20% or even less in 2011
  • even the most prominent scientists will find it difficult to maintain funding for their laboratories, and young scientists seeking their first grant may become so overwhelmed that individuals of great promise will be driven from the field
  • anxiety and frustration
  • The growth of the scientific enterprise on university campuses during the past 60 years is not sustainable and has now reached a tipping point at which old models no longer work
  • Origins of the crisis
  • ederal funding agencies must work with universities to ensure that new models of funding do not stymie the progress of science in the United States
  • The demand for research money greatly exceeds the supply
  • the demand for research funding has gone up
  • The deeper sources of the problem lie in the incentive structure of the modern research university, the aspirations of scientists trained by those universities, and the aspirations of less research-intensive universities and colleges across the nation
  • competitive grants system
  • if a university wants to attract a significant amount of sponsored research money, it needs doctoral programs in the relevant fields and faculty members who are dedicated to both winning grants and training students
  • The production of science and engineering doctorates has grown apace
  • Even though not all doctorate recipients become university faculty, the size of the science and engineering faculty at U.S. universities has grown substantially
  • proposal pressure goes up
  • These strategies make sense for any individual university, but will fail collectively unless federal funding for R&D grows robustly enough to keep up with demand.
  • At the very time that universities were enjoying rapidly growing budgets, and creating modes of operation that assumed such largess was the new normal, Price warned that it would all soon come to a halt
  • the human and financial resources invested in science had been increasing much faster than the populations and economies of those regions
  • growth in the scientific enterprise would have to slow down at some point, growing no more than the population or the economy.
  • Dead-end solutions
  • studies sounded an alarm about the potential decline in U.S. global leadership in science and technology and the grave implications of that decline for economic growth and national security
  • Although we are not opposed to increasing federal funding for research, we are not optimistic that it will happen at anywhere near the rate the Academies seek, nor do we think it will have a large impact on funding rates
  • universities should not expect any radical increases in domestic R&D budgets, and most likely not in defense R&D budgets either, unless the discretionary budgets themselves grow rapidly. Those budgets are under pressure from political groups that want to shrink government spending and from the growth of spending in mandatory programs
  • The basic point is that the growth of the economy will drive increases in federal R&D spending, and any attempt to provide rapid or sustained increases beyond that growth will require taking money from other programs.
  • The demand for research money cannot grow faster than the economy forever and the growth curve for research money flattened out long ago.
  • Path out of crisis
  • The goal cannot be to convince the government to invest a higher proportion of its discretionary spending in research
  • Getting more is not in the cards, and some observers think the scientific community will be lucky to keep what it has
  • The potential to take advantage of the infrastructure and talent on university campuses may be a win-win situation for businesses and institutions of higher education.
  • Why should universities and colleges continue to support scientific research, knowing that the financial benefits are diminishing?
  • esearch culture
  • attract good students and faculty as well as raise their prestige
  • mission to expand the boundaries of human knowledge
  • faculty members are committed to their scholarship and will press on with their research programs even when external dollars are scarce
  • training
  • take place in
  • research laboratories
  • it is critical to have active research laboratories, not only in elite public and private research institutions, but in non-flagship public universities, a diverse set of private universities, and four-year colleges
  • How then do increasingly beleaguered institutions of higher education support the research efforts of the faculty, given the reality that federal grants are going to be few and far between for the majority of faculty members? What are the practical steps institutions can take?
  • change the current model of providing large startup packages when a faculty member is hired and then leaving it up to the faculty member to obtain funding for the remainder of his or her career
  • universities invest less in new faculty members and spread their internal research dollars across faculty members at all stages of their careers, from early to late.
    • Tiberius Brastaviceanu
       
      Sharing of resources, see SENSORICA's NRP
  • national conversation about changes in startup packages and by careful consultations with prospective faculty hires about long-term support of their research efforts
  • Many prospective hires may find smaller startup packages palatable, if they can be convinced that the smaller packages are coupled with an institutional commitment to ongoing research support and more reasonable expectations about winning grants.
  • Smaller startup packages mean that in many situations, new faculty members will not be able to establish a functioning stand-alone laboratory. Thus, space and equipment will need to be shared to a greater extent than has been true in the past.
  • construction of open laboratory spaces and the strategic development of well-equipped research centers capable of efficiently servicing the needs of an array of researchers
  • phaseout of the individual laboratory
  • enhanced opportunities for communication and networking among faculty members and their students
  • Collaborative proposals and the assembly of research teams that focus on more complex problems can arise relatively naturally as interactions among researchers are facilitated by proximity and the absence of walls between laboratories.
  • An increased emphasis on team research
  • investments in the research enterprise
  • can be directed at projects that have good buy-in from the faculty
  • learn how to work both as part of a team and independently
  • Involvement in multiple projects should be encouraged
  • The more likely trajectory of a junior faculty member will evolve from contributing team member to increasing leadership responsibilities to team leader
  • nternal evaluations of contributions and potential will become more important in tenure and promotion decisions.
    • Tiberius Brastaviceanu
       
      Need value accounting system
  • relationships with foundations, donors, state agencies, and private business will become increasingly important in the funding game
  • The opportunities to form partnerships with business are especially intriguing
    • Tiberius Brastaviceanu
       
      The problem is to change the model and go open source, because IP stifles other processes that might benefit Universities!!!
  • Further complicating university collaborations with business is that past examples of such partnerships have not always been easy or free of controversy.
  • some faculty members worried about firms dictating the research priorities of the university, pulling graduate students into proprietary research (which could limit what they could publish), and generally tugging the relevant faculty in multiple directions.
  • developed rules and guidelines to control them
  • University faculty and businesspeople often do not understand each other’s cultures, needs, and constraints, and such gaps can lead to more mundane problems in university/industry relations, not least of which are organizational demands and institutional cultures
    • Tiberius Brastaviceanu
       
      Needs for mechanisms to govern, coordinate, structure an ecosystem -See SENSORICA's Open Alliance model
  • n addition to funding for research, universities can receive indirect benefits from such relationships. High-profile partnerships with businesses will underline the important role that universities can play in the economic development of a region.
  • Universities have to see firms as more than just deep pockets, and firms need to see universities as more than sources of cheap skilled labor.
  • foundations or other philanthropy
  • We do not believe that research proposed and supervised by individual principal investigators will disappear anytime soon. It is a research model that has proven to be remarkably successful and enduring
  • However, we believe that the most vibrant scientific communities on university and college campuses, and the ones most likely to thrive in the new reality of funding for the sciences, will be those that encourage the formation of research teams and are nimble with regard to funding sources, even as they leave room for traditional avenues of funding and research.
Tiberius Brastaviceanu

Google Apps Script - introduction - 0 views

  • Use the Script Editor to write and run scripts, to set triggers, and to perform other actions such as sharing scripts.
  • start the Script Editor from a Google Site
  • declares a function called myFunction()
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  • You can perform the following tasks from the Script Editor.
  • pening, deleting, renaming, and saving scripts
  • Cutting, copying, and pasting text
  • Find and replace
  • Setting a time zone
  • scripts with time-based triggers
  • Running functions
  • Viewing log messages
  • revision history
  • write pseudocode first
  • When you're planning a script
  • narrative version of what the script needs to do.
  • A particular script is associated with one and only one Google Spreadsheet.
  • If you make a copy of the Spreadsheet, the script is also copied.
  • A particular Spreadsheet can have multiple scripts associated with it.
  • use the onOpen event handler in more than one script associated with a particular Spreadsheet, all scripts begin to execute when you open the Spreadsheet and the order in which the scripts are executed is indeterminate.
  • event handler is a function executed when a particular event takes place.
  • see Running Scripts in Response to an Event.
  • A script cannot currently call or create another script and cannot call functions in another script.
  • If you want to store the results of a function, you must copy them into a spreadsheet cell.
  • You can trigger Apps Script events from links that are embedded in a Google Site. For information about how to do this, see Using Apps Scrip in Your Ssite.
  • You can insert a script into a Site as a gadget.
  • you must grant permission for the script to run as a service.
  • You also designate whether only you can invoke the service or whether all members of your domain can invoke the service.
  • you can assign functions within the script any arbitrary name.
  • The instructions in a function must be enclosed within curly braces.
  • event handler
  • when a spreadsheet is opened,
  • when a script is installed
  • when a spreadsheet is edited
  • at times you choose
  • menu item
  • Using a drawing or button embedded in a Spreadsheet
  • Using a custom function that is referenced as a Spreadsheet function
  • Clicking the Run button
  • object-oriented programming languages
  • Google Apps Script uses the JavaScript language.
  • Operations
  • are performed using the objects and methods described in the API documentation.
  • An API provides pre-packaged code for standard tasks you need to accomplish in scripts or programs.
  • API includes objects that you use to accomplish tasks such as sending email, creating calendar entries
  • A method describes the behavior of an object and is a function attached to an object.
  • MailApp
  • use to create and send email
  • To send email, you invoke the sendEmail method and provide values for the method arguments.
  • Google Apps Script can access or retrieve data in different formats in different ways.
  • A custom function
  • is called directly from a cell in a Spreadsheet using the syntax =myFunctionName()
  • they cannot set values outside the cells
  • have some restrictions not shared by other functions
  • cannot send email
  • cannot operate on a Google Site
  • cannot perform any operations that require user authorization
  • cannot perform any operations that require knowledge of who the user
  • onInstall function
  • onOpen function
  • Other functions run when you run them manually or when they are triggered by clicking
  • Custom functions and formulas in the spreadsheet execute any time the entire Spreadsheet is evaluated or when the data changes in the function or formula's cell.
  • share the Spreadsheet
  • publish the script to the Script Gallery
  • spreadsheet template
  • the color coding for that line will not be correct
  • A script with incorrect syntax or other errors does not run.
  • The Script Editor includes a debugger.
  • view the current state of variables and objects created by a script while that script runs.
  • step through the code line by line as it executes or set breakpoints
  • The debugger does not work with custom functions, onEdit functions, event triggers, or scripts running as a service.
  • use the debugger to find errors in scripts that are syntactically correct but still do not function correctly.
  • Functions ending in an underscore (_), for example, internalStuff_(), are treated differently from other functions. You do not see these function in the Run field in the Script Editor and they do not appear in the Script Manager in the Spreadsheet. You can use the underscore to indicate that users should not attempt to run the function and the function is available only to other functions.
Tiberius Brastaviceanu

Citizen Weather Observer Program - 0 views

  •  
    "The Citizen Weather Observer Program (CWOP) is a public-private partnership with three goals: 1) to collect weather data contributed by citizens; 2) to make these data available for weather services and homeland security; and 3) to provide feedback to the data contributors so they have the tools to check and improve their data quality. In fact, the web address, wxqa.com, stands for weather quality assurance. "
Tiberius Brastaviceanu

Science and Technology Consultation - Industry Canada - 0 views

  • Under this strategy
    • Yasir Siddiqui
       
      Testing
    • Yasir Siddiqui
       
      testing
  • Genome Canada, the Canadian Institute for Advanced Research and the Canada Foundation for Innovation.
  • Still, Canadian businesses continue to underperform when it comes to innovation—a primary driver of productivity growth—when compared to other competing nations. The performance of business R&D is one oft-cited measure used to gauge the level of innovative activity in a country's business sector.
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  • Canadians have reached top tier global performance in reading, mathematics, problem solving and science, and Canada has rising numbers of graduates with doctoral degrees in science and engineering.
  • This valuable resource of highly qualified and skilled individuals needs to be better leveraged.
  • The ease and ability of the academic community to collaborate, including through research networks, is also well-recognized.
  • to develop technologies, products and services that add value and create high-paying jobs.
  • Canada has an impressive record when it comes to research and the quality of its knowledge base.
  • Still, the innovative performance of Canada's firms and the productivity growth continue to lag behind competing nations.
  • The government is also committed to moving forward with a new approach to promoting business innovation—one that emphasizes active business-led initiatives and focuses resources on better fostering the growth of innovative firms.
  • Achieving this requires the concerted effort of all players in the innovation system—to ensure each does what one does best and to leverage one another's strengths.
  • the government has invested more to support science, technology and innovative companies than ever before
  • Canada must become more innovative
    • Kurt Laitner
       
      problem statement
  • providing a new framework to guide federal ST&I investments and priorities. That is why the Government of Canada stated its intention to release an updated ST&I Strategy in the October 2013 Speech from the Throne.
    • Kurt Laitner
       
      exercise
  • seeking the views of stakeholders from all sectors of the ST&I system—including universities, colleges and polytechnics, the business community, and Canadians
  • written submissions from all Canadians on the policy issues and questions presented in this paper.
  • The government remains focused on creating jobs, growth and long-term prosperity for Canadians
  • encouraging partnerships with industry, attracting highly skilled researchers, continuing investments in discovery-driven research, strengthening Canada's knowledge base, supporting research infrastructure and providing incentives to private sector innovation.
  • has transformed the National Research Council, doubled its investment
  • supported research collaborations through the federal granting councils
  • created the new Venture Capital Action Plan
  • helping to promote greater commercialization of research and development
  • Our country continues to lead the G7 in spending on R&D
  • Canada has a world-class post-secondary education system that embraces and successfully leverages collaboration with the private sector, particularly through research networks
  • destination for some of the world's brightest minds
  • global race
  • businesses that embrace innovation-based strategies
  • post-secondary and research institutions that attract and nurture highly qualified and skilled talent
  • researchers who push the frontiers of knowledge
  • governments that provide the support
    • Tiberius Brastaviceanu
       
      Why a race? We need to change the way we see this!!! We need to open up. See the European Commission Horizon 2020 program  http://ec.europa.eu/programmes/horizon2020/en/ They are acknowledging that Europe cannot do it alone, and are spending money on International collaboration. 
    • Tiberius Brastaviceanu
       
      There is nothing about non-institutionalized innovation, i.e. open source! There is nothing about the public in this equation like the Europeans do in the Digital Era for Europe program  https://ec.europa.eu/digital-agenda/node/66731 
  • low taxes, strong support for new businesses, a soundly regulated banking system, and ready availability of financial services
  • reducing red tape
  • expanding training partnerships and improving access to venture capital.
  • Collaboration is key to mobilizing innovation
  • invest in partnerships between businesses and colleges and universities
    • Tiberius Brastaviceanu
    • Tiberius Brastaviceanu
       
      But the public and in people is still not in sight of the fed gov. 
  • Economic Action Plans (EAP) 2012 and 2013
  • provide incentive for innovative activity in firms, improved access to venture capital, augmented and more coordinated direct support to firms, and deeper partnerships and connections between the public and private sectors.
Kurt Laitner

NoFlo | Flow-Based Programming for JavaScript - 2 views

  •  
    interesting, possibly useful, especially in the metamaps context
  •  
    their Kickstarter fundraising campaign is a success: http://www.kickstarter.com/projects/noflo/noflo-development-environment
Yasir Siddiqui

Do accelerators help startups? Here's what we found | VentureBeat | Entrepreneur | by S... - 1 views

  •  
    As startup accelerators continue to propagate, founders are left wondering if these programs really help entrepreneurs achieve their goals. Is the effort worth giving away equity, investing time, and creating incremental costs? Step 1: When can Accelerator results be measured? Step 2: What results do Accelerators see? Step 3: Does the accelerator matter? How to evaluate an accelerator...
Tiberius Brastaviceanu

Welcome to Open Modelica - OpenModelica - 0 views

  •  
    modeling and simulation program
Tiberius Brastaviceanu

How To Export STL Files From Google Sketchup - 0 views

  •  
    This page will show you two different plugins that can be used to export STL files from Google Sketchup. Once exported, you may then open them in a CAM program for generating 3D G-code for your CNC machine. Two cheap examples of 3D capable CAM programs would be CamBam Plus and MeshCam.
Tiberius Brastaviceanu

Google Apps Script - introduction - 0 views

  • how to accomplish some common tasks
  • add a custom menu to a Spreadsheet and link specific functions in your script to menu items
  • the menu items, the functions pops up a message box.
  • ...11 more annotations...
  • you will want the custom menu to be displayed as soon as the Spreadsheet is opened. To do this,include an onOpen function in your script
  • array of objects
  • An array is a collection of elements that works something like a Spreadsheet. Each element in an array can be identified by its location in the array, called an index point.
  • Arrays
  • are zero-based
  • Arrays are a convenient way to store and manipulate data within a computer program or script.
  • Each menu item is placed inside curly braces, and this syntax defines each name-function name pair as an object.
  • After the definition of the menu entries comes the definition of the menu itself:
  • Here's generalized code for creating menu items and a menu.
  • The following code pops up a message box when a user selects a menu item on the new menu:
  • the generalized code
sebastianklemm

TADAMON - Empowerment for Poverty Reduction - 1 views

  •  
    The IsDB-ISFD-NGO Empowerment for Poverty Reduction is a partnership program sponsored by The Islamic Solidarity Fund for Development (ISFD), managed by The Islamic Development Bank (IsDB) and implemented by United Nations Development program (UNDP) and other strategic partners. TADAMON platform is a tool for improving CSOs (Civil Society Organizations) in 57 OIC (Organization of Islamic Cooperation) Member Countries by providing visibility, funding, capacity building and knowledge.
Tiberius Brastaviceanu

Beyond Blockchain: Simple Scalable Cryptocurrencies - The World of Deep Wealth - Medium - 0 views

  • I clarify the core elements of cryptocurrency and outline a different approach to designing such currencies rooted in biomimicry
  • This post outlines a completely different strategy for implementing cryptocurrencies with completely distributed chains
  • Rather than trying to make one global, anonymous, digital cash
  • ...95 more annotations...
  • we are interested in the resilience that comes from building a rich ecosystem of interoperable currencies
  • What are the core elements of a modern cryptocurrency?
  • Digital
  • Holdings are electronic and only exist and operate by virtue of a community’s agreement about how to interpret digital bits according to rules about operation and accounting of the currency.
  • Trustless
  • don’t have to trust a 3rd party central authority
  • Decentralized
  • Specifically, access, issuance, transaction accounting, rules & policies, should be collectively visible, known, and held.
  • Cryptographic
  • This cryptographic structure is used to enable a variety of people to host the data without being able to alter it.
  • Identity
  • there must be a way to associate these bits with some kind of account, wallet, owner, or agent who can use them
  • Other things that many take for granted in blockchains may not be core but subject to decisions in design and implementation, so they can vary between implementations
  • It does not have to be stored in a synchronized global ledger
  • does not have to be money. It may be a reputation currency, or data used for identity, or naming, etc
  • Its units do not have to be cryptographic tokens or coins
  • It does not have to protect the anonymity of users, although it may
  • if you think currency is only money, and that money must be artificially scarce
  • Then you must tackle the problem of always tracking which coins exist, and which have been spent. That is one approach — the one blockchain takes.
  • You might optimize for anonymity if you think of cryptocurrency as a tool to escape governments, regulations, and taxes.
  • if you want to establish and manage membership in new kinds of commons, then identity and accountability for actions may turn out to be necessary ingredients instead of anonymity.
  • In the case of the MetaCurrency Project, we are trying to support many use cases by building tools to enable a rich ecosystem of communities and current-sees (many are non-monetary) to enhance collective intelligence at all scales.
  • Managing consensus about a shared reality is a central challenge at the heart of all distributed computing solutions.
  • If we want to democratize money by having cryptocurrencies become a significant and viable means of transacting on a daily basis, I believe we need fundamentally more scalable approaches that don’t require expensive, dedicated hardware just to participate.
  • We should not need system wide consensus for two people to do a transaction in a cryptocurrency
  • Blockchain is about managing a consensus about what was “said.” Ceptr is about distributing a consensus about how to “speak.”
  • how nature gets the job done in massively scalable systems which require coordination and consistency
  • Replicate the same processes across all nodes
  • Empower every node with full agency
  • Hold this transformed state locally and reliably
  • Establish protocols for interaction
  • Each speaker of a language carries the processes to understand sentences they hear, and generate sentences they need
  • we certainly don’t carry some kind of global ledger of everything that’s ever been said, or require consensus about what has been said
  • Language IS a communication protocol we learn by emulating the processes of usage.
  • Dictionaries try to catch up when the usage
  • there is certainly no global ledger with consensus about the state of trillions of cells. Yet, from a single zygote’s copy of DNA, our cells coordinate in a highly decentralized manner, on scales of trillions, and without the latency or bottlenecks of central control.
  • Imagine something along the lines of a Java Virtual Machine connected to a distributed version of Github
  • Every time this JVM runs a program it confirms the hash of the code it is about to execute with the hash signed into the code repository by its developers
  • This allows each node that intends to be honest to be sure that they’re running the same processes as everyone else. So when two parties want to do a transaction, and each can have confidence their own code, and the results that your code produces
  • Then you treat it as authoritative and commit it to your local cryptographically self-validating data store
  • Allowing each node to treat itself as a full authority to process transactions (or interactions via shared protocols) is exactly how you empower each node with full agency. Each node runs its copy of the signed program/processes on its own virtual machine, taking the transaction request combined with the transaction chains of the parties to the transaction. Each node can confirm their counterparty’s integrity by replaying their transactions to produce their current state, while confirming signatures and integrity of the chain
  • If both nodes are in an appropriate state which allows the current transaction, then they countersign the transaction and append to their respective chains. When you encounter a corrupted or dishonest node (as evidenced by a breach of integrity of their chain — passing through an invalid state, broken signatures, or broken links), your node can reject the transaction you were starting to process. Countersigning allows consensus at the appropriate scale of the decision (two people transacting in this case) to lock data into a tamper-proof state so it can be stored in as many parallel chains as you need.
  • When your node appends a mutually validated and signed transaction to its chain, it has updated its local state and is able to represent the integrity of its data locally. As long as each transaction (link in the chain) has valid linkages and countersignatures, we can know that it hasn’t been tampered with.
  • If you can reliably embody the state of the node in the node itself using Intrinsic Data Integrity, then all nodes can interact in parallel, independent of other interactions to maximize scalability and simultaneous processing. Either the node has the credits or it doesn’t. I don’t have to refer to a global ledger to find out, the state of the node is in the countersigned, tamper-proof chain.
  • Just like any meaningful communication, a protocol needs to be established to make sure that a transaction carries all the information needed for each node to run the processes and produce a new signed and chained state. This could be debits or credits to an account which modify the balance, or recoding courses and grades to a transcript which modify a Grade Point Average, or ratings and feedback contributing to a reputation score, and so on.
  • By distributing process at the foundation, and leveraging Intrinsic Data Integrity, our approach results in massive improvements in throughput (from parallel simultaneous independent processing), speed, latency, efficiency, and cost of hardware.
  • You also don’t need to incent people to hold their own record — they already want it.
  • Another noteworthy observation about humans, cells, and atoms, is that each has a general “container” that gets configured to a specific use.
  • Likewise, the Receptors we’ve built are a general purpose framework which can load code for different distributed applications. These Receptors are a lightweight processing container for the Ceptr Virtual Machine Host
  • Ceptr enables a developer to focus on the rules and transactions for their use case instead of building a whole framework for distributed applications.
  • how units in a currency are issued
  • Most people think that money is just money, but there are literally hundreds of decisions you can make in designing a currency to target particular needs, niches, communities or patterns of flow.
  • Blockchain cryptocurrencies are fiat currencies. They create tokens or coins from nothing
  • These coins are just “spoken into being”
  • the challenging task of
  • ensure there is no counterfeiting or double-spending
  • Blockchain cryptocurrencies are fiat currencies
  • These coins are just “spoken into being”
  • the challenging task of tracking all the coins that exist to ensure there is no counterfeiting or double-spending
  • You wouldn’t need to manage consensus about whether a cryptocoin is spent, if your system created accounts which have normal balances based on summing their transactions.
  • In a mutual credit system, units of currency are issued when a participant extends credit to another user in a standard spending transaction
  • Alice pays Bob 20 credits for a haircut. Alice’s account now has -20, and Bob’s has +20.
  • Alice spent credits she didn’t have! True
  • Managing the currency supply in a mutual credit system is about managing credit limits — how far people can spend into a negative balance
  • Notice the net number units in the system remains zero
  • One elegant approach to managing mutual credit limits is to set them based on actual demand.
  • concerns about manufacturing fake accounts to game credit limits (Sybil Attacks)
  • keep in mind there can be different classes of accounts. Easy to create, anonymous accounts may get NO credit limit
  • What if I alter my code to give myself an unlimited credit limit, then spend as much as I want? As soon as you pass the credit limit encoded in the shared agreements, the next person you transact with will discover you’re in an invalid state and refuse the transaction.
  • If two people collude to commit an illegal transaction by both hacking their code to allow a normally invalid state, the same still pattern still holds. The next person they try to transact with using untampered code will detect the problem and decline to transact.
  • Most modern community currency systems have been implemented as mutual credit,
  • Hawala is a network of merchants and businessmen, which has been operating since the middle ages, performing money transfers on an honor system and typically settling balances through merchandise instead of transferring money
  • Let’s look at building a minimum viable cryptocurrency with the hawala network as our use case
  • To minimize key management infrastructure, each hawaladar’s public key is their address or identity on the network. To join the network you get a copy of the software from another hawaladar, generate your public and private keys, and complete your personal profile (name, location, contact info, etc.). You call, fax, or email at least 10 hawaladars who know you, and give them your IP address and ask them to vouch for you.
  • Once 10 other hawaladars have vouched for you, you can start doing other transactions because the protocol encoded in every node will reject a transaction chain that doesn’t start with at least 10 vouches
  • seeding your information with those other peers so you can be found by the rest of the network.
  • As described in the Mutual Credit section, at the time of transaction each party audits the counterparty’s transaction chain.
  • Our hawala crypto-clearinghouse protocol has two categories of transactions: some used for accounting and others for routing. Accounting transactions change balances. Routing transactions maintain network integrity by recording information about hawaladar
  • Accounting Transactions create signed data that changes account balances and contains these fields:
  • The final hash of all of the above fields is used as a unique transaction ID and is what each of party signs with their private keys. Signing indicates a party has agreed to the terms of the transaction. Only transactions signed by both parties are considered valid. Nodes can verify signatures by confirming that decryption of the signature using the public key yields a result which matches the transaction ID.
  • Routing Transactions sign data that changes the peers list and contain these fields:
  • As with accounting transactions, the hash of the above fields is used as the transaction’s unique key and the basis for the cryptographic signature of both counterparties.
  • Remember, instead of making changes to account balances, routing transactions change a node’s local list of peers for finding each other and processing.
  • a distributed network of mutual trust
  • operates across national boundaries
  • everyone already keeps and trusts their own separate records
  • Hawaladars are not anonymous
  • “double-spending”
  • It would be possible for someone to hack the code on their node to “forget” their most recent transaction (drop the head of their chain), and go back to their previous version of the chain before that transaction. Then they could append a new transaction, drop it, and append again.
  • After both parties have signed the agreed upon transaction, each party submits the transaction to separate notaries. Notaries are a special class of participant who validate transactions (auditing each chain, ensuring nobody passes through an invalid state), and then they sign an outer envelope which includes the signatures of the two parties. Notaries agree to run high-availability servers which collectively manage a Distributed Hash Table (DHT) servicing requests for transaction information. As their incentive for providing this infrastructure, notaries get a small transaction fee.
  • This approach introduces a few more steps and delays to the transaction process, but because it operates on independent parallel chains, it is still orders of magnitude more efficient and decentralized than reaching consensus on entries in a global ledger
  • millions of simultaneous transactions could be getting processed by other parties and notaries with no bottlenecks.
  • There are other solutions to prevent nodes from dropping the head of their transaction chain, but the approach of having notaries serve out a DHT solves a number of common objections to completely distributed accounting. Having access to reliable lookups in a DHT provides a similar big picture view that you get from a global ledger. For example, you may want a way to look up transactions even when the parties to that transaction are offline, or to be able to see the net system balance at a particular moment in time, or identify patterns of activity in the larger system without having to collect data from everyone individually.
  • By leveraging Intrinsic Data Integrity to run numerous parallel tamper-proof chains you can enable nodes to do various P2P transactions which don’t actually require group consensus. Mutual credit is a great way to implement cryptocurrencies to run in this peered manner. Basic PKI with a DHT is enough additional infrastructure to address main vulnerabilities. You can optimize your solution architecture by reserving reserve consensus work for tasks which need to guarantee uniqueness or actually involve large scale agreement by humans or automated contracts.
  • It is not only possible, but far more scalable to build cryptocurrencies without a global ledger consensus approach or cryptographic tokens.
  •  
    Article written by Arthur Brook, founder of Metacurrency project and of Ceptr.
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.
  • ...139 more annotations...
  • 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.
Francois Bergeron

Conference Detail for Industrial and Commercial Applications of Smart Structures Techno... - 0 views

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    "Three-axis distributed fiber optic strain measurement in 3D woven composite structures   Paper 8690-6 Time: 1:50 PM - 2:10 PM Author(s): Matt Castellucci, Evan M. Lally, Sandra Klute, Luna Innovations Inc. (United States); David Lowry, NASA Johnson Space Ctr. (United States) Hide Abstract Add to My Schedule  Recent advancements in composite materials technologies have broken further from traditional designs and require advanced instrumentation and analysis capabilities. Success or failure is highly dependent on design analysis and manufacturing processes. By monitoring smart structures throughout manufacturing and service life, residual and operational stresses can be assessed and structural damage identified. Composite smart structures can be manufactured by integrating fiber optic sensors into existing composite materials processes such as layup, filament winding and three-dimensional weaving. In this work optical fiber was integrated into 3D woven composite parts at a commercial woven products manufacturing facility. The fiber was then used to monitor the structures during a VARTM manufacturing process, and subsequent static and dynamic testing. Low cost telecommunications-grade optical fiber acts as the sensor using a high resolution commercial Optical Frequency Domain Reflectometer (OFDR) system providing distributed strain measurement at spatial resolutions as low as 2mm. Strain measurements using the optical fiber sensors are correlated to resistive strain gauge measurements during static structural loading."
kozak30k

Starter Kit for Arduino - Flex - SparkFun Electronics - 0 views

    • kozak30k
       
      Users want starter instructions/project cookbook, spec sheet, ideas for cool projects.
  • The package I received contained some warranty info, but not even a spec sheet for the Duo R3. I was hoping to have it programmed to make an LED blink today, but I’m at a dead end from the get go here.
  • Inventors Kit Guide too.
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    Feedback and comments from users for the Arduino Starter Kit
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    Nice discovery Tony
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