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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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A microscopic storage system that encodes every bit with a single atom -- allowing them to fit a kilobyte in a space under 100 nanometers across has been created. "That translates to a storage density of about 500 terabits per square inch. For comparison, those 4-terabyte hard drives you can buy today are about 1 terabit per square inch."
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The read/write process would be complex, if they succeed in making it as fast as today's tech, then I would really be fascinated!
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Prisma's neural net-powered photo app arrives on Android. "The big deal is the use of cloud-based machine learning to turn humdrum photos into hyper-stylized pieces of art -- vivid brush strokes and pencil lines appear out of nowhere."
Everyone can see how machine learning spruces up their shots.
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Hmm.
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Two planets in a star system 40 light years from earth have been determined to be terrestrial planets with compact atmospheres like Earth, Venus, and Mars, and not gas giants like Jupiter. The determination was made by catching a double transit of both planets in front of the star by the Hubble Space Telescope. The atmospheric composition has not yet been determined.
Two potentially habitable planets in nearby system are confirmed to be rocky.
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Certain? Based on what?
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NYC Flow: New York City in slow motion as seen through neural-style deep learning art filters.
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How much everyone working on a $200 million movie earns.
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"OpenAI, which was created to do basic AI research, is reprogramming robots developed by Fetch Robotics, a company that supplies warehouse automation hardware."

"In April, OpenAI recruited Pieter Abbeel, a professor at the University of California, Berkeley, and a leading expert on robot learning. Abbeel has shown how robots can use a machine-learning approach called deep reinforcement learning to acquire completely new skills that would be hard to program by hand, such as folding towels or retrieving items from a refrigerator."

"Abbeel's robots learn tasks from scratch, using a neural network that receives sensor input and controls physical movement."
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Wayne Radinsky

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"On Monday, Yahoo! Inc.'s years-long fight to survive as a standalone company will draw to a close. Verizon Communications Inc. will announce plans to buy Yahoo's core assets for a bit more than $4.8 billion before the market opens, said two people with direct knowledge of the situation who asked not to be identified because the information isn't public." Well, it is now. Public, that is. Although it could be just a rumor.
On Monday, Yahoo! Inc.’s years-long fight to survive as a standalone company will draw to a close.
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A year in the life of planet earth, as seen from Lagrange point 1 (L1).
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"Bubble Zoom is a new feature for comic books in Google Play that uses machine learning to identify speech bubbles in comics and make it easy to read digital versions on smartphones and tablets. The system uses the same machine learning technology that recognizes items in photos -- dogs, hugs, people's faces -- and applies it to dialogue on a page of a comic."

Now you can zoom into each speech bubble one tap at a time while still enjoying the full page experience, and not losing the artwork.
Artificial intelligence may not always be on humanity's side in the movies, but machine learning can improve the digital comic book experience.
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China: A Prisma tale. China as seen through the Prisma app, which uses neural-style deep learning art filters.
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Beautiful
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Google sprints ahead in AI building blocks. By which they mean TensorFlow. As judged by GitHub stars. "Since emerging, TensorFlow has become the most popular AI programming project on software code sharing service GitHub, leapfrogging well-regarded systems created by universities and corporate rivals."

"On launch day, TensorFlow had around 3,000 'stars' on GitHub, meaning that number of programmers had bookmarked the code, indicating interest. As of July 13, it had 27,873. Two other popular AI software projects, Theano and Torch, have less than a fifth of that following. In 2014, Torch was the leader. A Microsoft tool called CNTK, released for free in January, and Amazon's free DSSTNE, which rolled out in May, have so far failed to dent Google's lead much."
There’s a high-stakes race under way in Silicon Valley to develop software that makes it easy to weave artificial intelligence technology into almost everything, and Google has sprinted into the lead.
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I am not sure star ratings will sway me. I have Microsoft's but have been to busy to implement it. Tbh Afford.net has far more subscribers but the new guys offer the popular toys. It may be entry is easier on tensor or more digestible API. I have a goal of evaluating CNTK by September to see how applicable it is to replace afford.net. Time will tell if they are all different flavors of the same basic toolset. 
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What if humans evolved to survive low-impact car crashes? Meet Graham, a model designed to show that.
As much as we like to think we’re invincible, we’re not. But what if our bodies were to change to cope with the impact of a car accident? Meet Graham at www.meetgraham.com.au
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Think I ran into that guy at Walmart. Um, not with a car.
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Have him in circles
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Work
Occupation
Software Design and Development
Employment
  • Software Design and Development, present
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Currently
Denver
Previously
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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Male