The Evolving Landscape Of Recommendation Systems | TechCrunch #tech #products #digital #UX


Everyday decisions, from which products to buy, movies to watch and restaurants to try, are more and more being put in the hands of a new source: recommendation systems. Recommendation systems are changing the very ways we make up our minds, guiding us through a new digital reality whose evolution is bringing us closer to exactly what it is that we want — even if we ourselves don’t know it yet. Recommendation systems (or RS for short) are intelligent information filtering engines that narrow the decision-making process to just a few proposals, and they’ve become an integral part of the user experience within some of our favorite platforms. READ MORE: The Evolving Landscape Of Recommendation Systems | TechCrunch

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Google’s Dream Robot Is Running Wild Across the Internet | Gizmodo #images #algorithms #visualizations


Remember a few weeks back, when we learned that Google’s artificial neural network was having creepy daydreams, turning buildings into acid trips and landscapes into Magic Eye pictures? Well, prepare to never sleep again, because last week, Google made its “inceptionism” algorithm available to the public, and the nightmarish images are cropping up everywhere.

The “Deep Dream” system essentially feeds an image through a layer of artificial neurons, asking an AI to enhance and build on certain features, such as edges. Over time, pictures can become so distorted that they morph into something entirely different, or just a bunch of colorful, random noise.

Now that the code for the system is publicly available, anyone can upload a photo of their baby and watch it metamorphose into a surrealist cockroach, or whatever. If you need some inspiration, or an excuse to crawl back into bed, pull the covers over your face, and wait for the world to end, just check out the hashtag ‘DeepDream’ on your social media platform of choice. READ MORE: Google’s Dream Robot Is Running Wild Across the Internet | Gizmodo.

Also See: DeepDream – A Code Example for Visualizing Neural Networks | Google Research Blog

Inside Obama’s Stealth Startup | Fast Company #tech #government


There may not be many of you interested in government bureaucracy, operations and technology…but if you are, this long form article from FastCompany is a very good read! Its also a reminder of the sad state of government affairs in Canada and how important it is for a country to be run by an insightful leader focused on building and creating instead of an authoritarian focused on suffocating innovation, responsiveness and transparency. 

President Obama has quietly recruited top tech talent from the likes of Google and Facebook. Their mission: to reboot how government works. READ MORE: Inside Obama’s Stealth Startup | Fast Company | Business + Innovation.

New Article: “Supporting the Next-Generation ILS: The Changing Roles of Systems Librarians” | LJ INFOdocket


First Paragraph of Abstract:

This paper compares current responsibilities of systems librarians supporting the traditional ILS with anticipated responsibilities associated with supporting the next- generation ILS.

Read more and access a direct link to the journal article: New Article: “Supporting the Next-Generation ILS: The Changing Roles of Systems Librarians” | LJ INFOdocket.

This Scientist Uses The New York Times Archive To Eerily, Accurately Predict The Future | Co.Exist


The New York Times might be a widely respected chronicler of past events, but can we use it to divine the future? Kira Radinsky, a 27-year-old Israeli computer prodigy dubbed the “web prophet” says yes.

Radinsky, who appeared this year on MIT’s prestigious list of top 35 inventors under the age of 35 (previous winners include the likes of Mark Zuckerberg, Larry Page, and Sergey Brin), and who started university at the age of 15 and received her Ph.D. in computer science at 26, has developed a unique system which she claims has already predicted the first cholera epidemic in Cuba in many decades, many of the riots that started the Arab Spring, and other important world events.

The complex computer algorithms she wrote collect immense volumes of electronic data–most notably several decades of New York Times archives but also anything from Twitter feeds to Wikipedia entries–and processes it to extract little-known cause and effect patterns that can be used to predict future events.

Red more: This Scientist Uses The New York Times Archive To Eerily, Accurately Predict The Future | Co.Exist

To Predict The Future Of Technology, Figure Out How People Will Use It Illegally | Co.Exist


I find that it’s often useful to imagine the unintended, seedy, improper, or illicit uses of new tools and systems…Thinking along those lines can help to uncover the more subtle connections between a new technology and incumbent systems, spot hidden security flaws, or even reveal markets for a product that the developer had ignored.

Read: To Predict The Future Of Technology, Figure Out How People Will Use It Illegally | Co.Exist | ideas + impact.