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Wayne Radinsky
Attended University Of Colorado At Boulder
Lives in Denver
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Wayne Radinsky

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"StudentLife, an Android app a group of Dartmouth students designed, can estimate a grade point average within nearly one-fifth of a point by measuring factors like how often you exercise or when you go to sleep."

"What is innovative is the way in which this data was collected: Because StudentLife operates exclusively using machine learning, all of the data was gathered with little disturbance to students' routines."

"Using some of the Android's built-in tools -- such as audio collection, a light sensor and an accelerometer -- to gather observations on a situation, StudentLife then utilizes a decision tree to predict whether you're running, sleeping, or partying."
StudentLife, an Android app designed by Dartmouth students, can calculate GPA within nearly one-fifth of a point by measuring exercise or sleep.
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Bueller?!?!?
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"Digital Reasoning, a leader in cognitive computing, today announced that it has trained the largest neural network in the world to date with a stunning 160 billion parameters. Google's previous record was 11.2 billion, and Lawrence Livermore National Laboratory recently trained a neural network with 15 billion parameters." This is according to a press release from Digital Reasoning.
Get the scoop from around the Digital Reasoning universe. Check out our latest press releases, events we’ll be attending, and informative blog posts.
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Robot-related deaths are rare, and becoming rarer. "The killing of a technician by an industrial robot at a Volkswagen plant in Germany sparked a social media storm this week and raised fears about human safety in the coming era of robotics. But experts on artificial intelligence and automation said the incident near Kassel should be understood as an extremely rare industrial accident, rather than a warning about future threats."
The killing of a technician by an industrial robot at a Volkswagen plant in Germany sparked a social media storm this week and raised fears about human safety in the coming era of robotics. But experts on artificial intelligence and automation said
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Things rust 1.0 shipped without: null pointers, array overruns, data races, wild pointers, uninitialized, yet addressable memory, unions that allow access to the wrong field, ... and 23 other things.
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Pre-crastination is the opposite of procrastination. "Pre-crastination is the inclination to complete tasks quickly just for the sake of getting things done sooner rather than later. People answer emails immediately rather than carefully contemplating their replies. People pay bills as soon as they arrive, thus failing to collect interest income. And, people grab items when they first enter the grocery store, carry them to the back of the store, pick up more groceries at the back, and then return to the front of the store to pay and exit, thus toting the items farther than necessary. Familiar adages also warn of the hazards of pre-crastinating: Measure twice, cut once. Marry in haste, repent at leisure. Look before you leap."

"We first found striking evidence of pre-crastination in a laboratory study exploring the economics of effort."
Why we do some tasks before their time—and why pigeons do, too
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Douglas Adams was another big advocate, or put another way he was notorious for doing things last minute.
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So about that whole tech-eating-jobs thing... "'Robots Seem to Be Improving Productivity, Not Costing Jobs,' reports the Harvard Business Review. Total nonfarm payroll employment is far above where it was ten years ago. Even the age-adjusted employment-to-population ratio has, crucially, recovered almost two-thirds of its Great Recession losses. The trend is obvious. Yes, the tech-eating-jobs argument still seems to hold logical water. Yes, this may be a sharp cyclical rise masking a gradual structural decline. But right now the evidence indicates that 'tech is eating jobs!' is vaporware at best. Opinions are interesting, but evidence is what matters."
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We may soon get to the point where backlash against any argument for Basic Income invades the conservative press.
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IPv4 addresses have finally run out. I guess that means we'll start seeing services that you can't access if you haven't upgraded to IPv6.
Behind the quiet Internet revolution you've never heard of
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Wayne Radinsky

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Google's DeepStereo algorithm is learning to synthesize real world images. Give it two images of a scene and it will synthesize a third image from a different point of view. "They trained their algorithm, called DeepStereo, using 'images of street scenes captured by a moving vehicle.' Indeed, they use 100,000 of these sequences as a training data set. They then tested it by removing one frame from a sequence of Street View images and asking it to reproduce it by looking only at the other images in the sequence. Finally, they compare the synthesized image with the one that was removed, giving them a kind of gold standard to contrast it with."
Give Google’s DeepStereo algorithm two images of a scene and it will synthesize a third image from a different point of view.
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The giant magnetoresistance (GMR) effect, which is what makes hard drives work, has been directly observed using a method called ultrafast terahertz spectroscopy. Ultrafast terahertz spectroscopy uses a thousand billion oscillations per second, enabling the sub-100 femtosecond measurements that observing the GMR effect requires.
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For those of you who prefer the original German:

http://www.mpip-mainz.mpg.de/Ultraschnelle_Terahertz_Spektroskopie
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Animated GIF showing a map of the US re-scaled by total residential property value for each county.
After the last post, which looked at housing values across New York City, I thought it would be interesting to take a more granular look at housing values across the U.S.To create the map below, I took the total residential property value for every county in the U.S. (the contiguous 48 states), and substituted those values for each county’s land area. Total […]
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+Wayne Radinsky Yes, now I can see it.
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A quick puzzle to test your problem solving: Guess the rule that sequences of three numbers obey.
A short game sheds light on government policy, corporate America, and why no one likes to be wrong.
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I got it.

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Tested negative numbers, decimal, tried to break it and a whole bunch of increasing sequences.
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"In hopes of making the stereoscopic virtual-reality experience more like what you see in real life, the Stanford researchers built a headset that contains two LCDs placed one in front of the other, with a backlight behind them, a spacer between them, and lenses in front of them. It's connected to a computer that runs software necessary for the system to work."

"An algorithm uses the light fields to generate two images for each eye, and, for each eye, one of these images is shown on the rear LCD in the headset, while the other is shown on the front LCD. The images enter your pupils and are projected on your retinas."

"What you see, Wetzstein says, is an approximation of the light field that's being optically generated, which your eyes can freely move around and focus on where they want in virtual space."
Stanford researchers are building a light field stereoscope in hopes of making it easier to add realistic focus cues to virtual reality.
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Wayne's Collections
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Have him in circles
15,941 people
Naveed Ali's profile photo
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aditya koneru's profile photo
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Christine Taylor's profile photo
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Occupation
Software Design and Development
Employment
  • Software Design and Development, present
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Denver
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Denver - Silicon Valley, California
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Software Design Engineer
Introduction
I'm a software engineer specializing in great design of software -- every successful large software project ever made started out as a small software project that got larger. The key to a successful large project is knowing how to design software when it is small so it is capable of growing. Poor design in the early stages leads to high-entropy software that is difficult to maintain and add new features to years down the line. Good design in the initial stages allows new software features to be added easily. Good design doesn't take any more time than poor design, but you have to know how to do it.

Certain keys are very essential to good design. The beginning is the program's data structures, which form the foundation for any software project. The key to good data structure design is to make sure that the relationships between bits of data in your data structures are the same as the relationships between the objects or ideas that those data structures represent in the minds of your users. Any time these get out of sync, you are in for trouble -- but the trouble does not usually arrive immediately -- it can arrive months or years down the line. This delayed feedback cycle is one reason many software projects run late or fail. Any time the data structures are out of sync with the minds of users, there is the temptation to "patch" the problem by adding more data structures, that form a bridge between the existing data structures, and what you want to do. These "patches" are, unfortunately, "dirty hacks", that down the road will add complexity to your software. It is this complexity -- and more to the point, *unnecessary* complexity, that makes it more difficult to maintain or extend your software with new features in the future.

It is also extremely important to design the code structure correctly. It is very common to make basic errors like using global variables. Globals are very powerful, but should be used with care -- they connect separate components of the software with each other. (And be aware that many variables are global even when they are not called "global" in your particular programming language -- they can have other names). When you *want* something to apply "everywhere", globals are the right choice, because you change them in one place and the change is applied everywhere. But more often than not, globals are used when they shouldn't be, causing a change in one part of a program to cause another part of the program, that seems unrelated, to break.

Another minefield is object oriented programming. Objects are an extremely powerful and flexible programming metaphor -- and that's the problem. They are so flexible that they can mean almost anything, and they can make it easy for you to shoot yourself in the foot with excessive complexity. In reality, there is nothing wrong with non-object-oriented programming -- proper and thoughtful use of functions and libraries of functions -- so it is not necessary to use objects everywhere or make "everything" an object in your program. In particular, there is no advantage in doing "object-relational mapping" -- if you're doing this, it means you have designed all your data structures *twice* (once in the relational data model, and again in an object-oriented model), wasting effort. Furthermore, objects should only be used when they add *clarity* to a program, when they make it easier to understand how the program works, rather than more difficult. In certain situations, such as when polymorphism is needed to solve whatever problem your software needs to solve for the user, objects are a clear benefit, simplifying the design and adding clarity to the code. In many other situations, however, excess use of objects creates obfuscation, leading to maintainability problems and difficulty adding features to your software in the future.

And it is these complexity issues that impose limitations on how big your software can get, how many features it can have, and ultimately how well your business can grow and how well you can serve your customers.
Education
  • University Of Colorado At Boulder
    Computer Science
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