Where to start, where to start? This Education and Digital Cultures course has opened so many doors, traveled so many paths and crossed so many lines of conversation, interaction and thought that’s it almost feels like an injustice simply summarising our rampant and energetic dive in to our world of digital influences, both real and unreal as it now exists into a synchronous set of weeks’ activity.
Our foray into the awakenings of AI and the lessons we (think we) should be heeding was a visual candy shop to kick off our EDC experience. Largely dystopian and seldom encouraging, only time will tell if we are indeed ready to articulate the delicate mandolin that is ever developing artificial intelligence, biomechanics and our inevitable march towards a post humanist and eventual transhuman state of being. Writings from the likes of Miller (2011), Hand (2008) and Hayles (1999) walk the path of either insightful readings of future trends or irrelevant commentary to be hurled on the trash pile of past inaccuracy. Only time will tell. And doubly so, we can only hope that whichever future does manifest, it does so in ways that benefits the human race profoundly more so that it does so currently without us sacrificing too much of our precious human compassion, consideration for our home and our ethical duty to help others. Baynes (2015) criticism of TEL resonated on several occasions where we were called to question the use of the digital medium.
The development of the MOOC for instance is at least one major stab at applying the benefits of a highly connected world to overcome the barriers to education though lack of resources, capabilities or institutional advantages granted by place of birth, race, or another means by which humans can be separated.
The dream of open education, although noble, is not without its challenges as was so deftly demonstrated in our ethnographic studies on the OER phenomenon. Open, as we have come to learn is not as ‘open’ as we imagine and participants in these free learning environments face a series of obvious and sometimes not-so obvious tests to achieving understanding, some of which are created through just being human (self-direction and motivation). EDC, in this case helped push me to consider so many more factors within the MOOC device that I had not even begun to consider before. Not only that, it exposed me to ways of visualising and communicating on these factors in innovative ways too that I believe was of benefit not just to me, but, to my fellow learners as well. And so too did their creative experiences enrich my understanding and achieve the core essence of the community basis of learning.
Lastly, the foray into the structured ,but, at the same time, somewhat manipulative world of the alogarithim and its cousin, learning analytics, aptly dissected by the likes of Siemens (2013) and Knox (2015) as well as Eynon, (2013) to reveal its growing influence in all parts of our lives, indicates that these phenomenon’s must be interrogated at every step for the sake of learners everywhere lest we be led by the proverbial nose down a path of good intentions that could also discriminate and exclude.
Coming to the end of this course on education and digital culture, with its array of immersive and portentive experiences I am drawn to the fact that although it is heavily imbued with layers, flows and currents of existing and future technology, it is human connectedness, feelings and perception that is still at the heart of what good teaching is all about. Even as we go about finding ways of trying to improve those elements across time, distance, culture or language, connecting with others to learn, to share and to experience should be at the heart of every single digital endeavour we embark on.
If you’re in the market for a prefab dwelling—either as a full-time home or backyard unit—optionsareaplenty. What L.A.-based startup Cover wants to add to the equation is a tech-driven efficiency that makes the whole design and building process a total breeze for the customer.
As detailed in a new profile on the company over on Co.Design, Cover sees itself as more of a tech company than a prefab builder. Indeed, whereas a typical prefab buying process would begin with choosing one of a few model plans and maybe then consulting with architects to tweak the design for specific needs, Cover turns the whole design process over to computer algorithms. Co.Design explains:
Once customers begin the design process, Cover sends them a survey of about 50 to 100 questions to inform the design. It asks about lifestyle–how many people typically cook a meal and what appliances are must-haves?–and structural needs, like should they optimize one view and block another one?
The company also use computer modeling to optimize window placement, cross-ventilation, and natural light, making use of zoning, sun-path, and geospatial data. All of these parameters are then sent to a proprietary computer program that spits out hundreds of designs that satisfy the requirements supplied.
Here are a couple of key things to know about Cover’s prefabs:
The company is specializing in the accessory dwelling unit, which is a secondary structure on a property with an existing single-family house. They can serve as guesthouses, in-law units, offices, yoga studios, and potentially a source of rental income.
While the computer will churn out a whole bunch of designs, Cover dwellings generally have a minimal modern look with an insulated steel structure, glass walls, and built-in storage.
When you order with Cover, the company takes care of the whole process, from coming up with a design, as described above (which takes three business days and $250), to acquiring necessary permits (two to five months, $20,000), to building and installation (12 weeks, final price contingent on the specific design). Some sample costs offered on the website are as follows: $70,000 for a guest room, $130,000 for a studio with a kitchenette, $160,000 for a one-bedroom unit, and $250,000 for a two-bedroom unit.
I would absolutely hate to be a celebrity. Can you just imagine the attention, constant harassment by fans, paparazzi, having to put up with photos pf your naked body all over the tabloids just because you decided to ‘let-go’ for the summer. No thanks!. But probably the worst part of the celebrity gig must be all the fan mail – mountains and mountains of it every day from fans who think you and them share some special bond, some that are total whack-jobs and a fair few, I bet, that want to interest you in a business deal.
These last few weeks of the EDC blogging process has been somewhat of a trench war against an unending barrage of spam, junk mail and totally unwanted commentary. Now, embarking on the clean up before presentation for assessment I have probably received at least three or four spam comments each day trying to sell me everything from Spanish condos, to french language lessons and even muscle gain formula (Has this bot been stalking my Facebook page?)
As educators we often don’t even begin to think about the daily grind that most students have to bear with in terms of the glut of internet marketing, five second intros, spam, junk email and its ilk. It hard enough to concentrate as it is but adding another layer of irritating marketing to the picture really chips away at the nerves after a while. Many folks just filter it out, but, when you really think about it this stuff is contributing to an animosity about the web that doesn’t particularly help in the field we are engaged in. Learners, particularly younger ones, can be disengaged at the best of times, so do we really need to think about how much they are exposed to?
Just like a break in cigarette marketing help to bring down rates of younger smokers could such a ban assist in creating more engaged learners, even if only by one or two percent?
The onslaught continues, but with my trusty spam reporting button in hand I may yet prevail against the tide of nonsensical spammage!
We Just Created an Artificial Synapse That Can Learn Autonomously
A team of researchers has developed artificial synapses that are capable of learning autonomously and can improve how fast artificial neural networks learn.
Mimicking the Brain
Developments and advances in artificial intelligence (AI) have been due in large part to technologies that mimic how the human brain works. In the world of information technology, such AI systems are called neural networks. These contain algorithms that can be trained, among other things, to imitate how the brain recognizes speech and images. However, running an Artificial Neural Network consumes a lot of time and energy.
Image Credit: Sören Boyn/CNRS/Thales physics joint research unit
In the human brain, synapses work as connections between neurons. The connections are reinforced and learning is improved the more these synapses are are stimulated. The memristor works in a similar fashion. It’s made up of a thin ferroelectric layer (which can be spontaneously polarized) that is enclosed between two electrodes. Using voltage pulses, their resistance can be adjusted, like biological neurons. The synaptic connection will be strong when resistance is low, and vice-versa. The memristor’s capacity for learning is based on this adjustable resistance.
This is all thanks to AI’s capacity to learn, the only limitation of which is the amount of time and effort it takes to consume the data that serve as its springboard. With the memristor, this learning process can be greatly improved. Work continues on the memristor, particularly on exploring ways to optimize its function. For starters, the researchers have successfully built a physical model to help predict how it functions. Their work is published in the journal Nature Communications.
Soon, we may have AI systems that can learn as well as out brains can — or even better
“Unpaywall” Is New Tool For Accessing Research Papers For Free
April 5, 2017by Larry Ferlazzo
As anyone who has tried to pursue even a little bit of academic research can attest, publishers charge an arm-and-a-leg to access studies if you are not part of an institution that subscribes to their journals. And the authors of those studies don’t even get any of that money!
Today we’re launching a new tool to help people read research literature, instead of getting stuck behind paywalls. It’s an extension for Chrome and Firefox that links you to free full-text as you browse research articles. Hit a paywall? No problem: click the green tab and read it free!
The extension is called Unpaywall, and it’s powered by an open index of more than ten million legally-uploaded, open access resources.
Apparently, many institutions now require their faculty upload their published papers to their libraries, and that is a primary source for Unpaywall research.
Two pairs of researchers from Cornell University and Adobe have teamed up and developed a “Deep Photo Style Transfer” algorithm that can automatically apply the style (read: color and lighting) of one photo to another. The early results are incredibly impressive and promising.
The software is an expansion on the tech used to transfer painting styles like Monet or Van Gogh to a photograph like the app Prisma. But instead of a painting, this program uses other photographs for reference.
“This paper introduces a deep-learning approach to photographic style transfer that handles a large variety of image content while faithfully transferring the reference style,” says the rather technical abstract of the Deep Photo Style Transfer paper.
Put more plainly: when you put in two photographs, the neural network-powered program analyzes the color and quality of light in the reference photo, and pastes that photo’s characteristics onto the second. This includes things like weather, season, and time of day—theoretically, a winter’s day can be turned into summer, or a cloudy day into a glorious sunrise.
The team’s early examples show the program in action. So this original photo:
Plus this reference photo:
Equals this final photo:
It’s important to note that the software does not alter the structure of the photo in any way, so there’s no risk of distorting the lines, edges or perspective. The entire focus is on mimicking the color and light in order to copy the “look” or “style” of a reference photograph onto a new shot.
Since this is a lot easier said than done, the program has to intelligently compensate for differences between the donor and receiving image. If there is less sky visible in the receiving image, it will detect this difference and not cause the sky to spill over into the rest of the original shot, for example.
The software even attempts to “achieve very local drastic effects,” such as turning on the lights on individual skyscraper windows, all without altering the original photo by moving windows around or distorting edges.
In the future, a perfected version of this technology could make its way into Photoshop as a tool, or run as a separate program or plug-in. Not that you should bank on this tech fixing the photos from your upcoming trip; like any other new technology, there is work to be done.
“The study shows that our algorithm produces the most faithful style transfer results more than 80% of the time,” the paper cautions. So maybe you can’t change Ansel Adam’s Moonrise, Hernandez to a Sunrise, Hernandez, but you get the picture (no pun intended) and it is very promising.