What I’m Reading on 04/21/2014

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What I’m Reading on 04/19/2014

  • “Johnny Depp, who’s built a brilliant career despite many of his lamentable film choices, may not be the first actor you think of to play a genius – much less humanity’s destroyer or savior. But he’s weirdly perfect in “Transcendence,” an inelegant, no doubt implausible (maybe not) science-fiction film about a futurist whose consciousness is uploaded onto the Internet. “

    tags: johnny depp transcendence nytimes bs

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What I’m Reading on 04/10/2014

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What I’m Reading on 04/05/2014

  • “For over eight years, ProgrammableWeb has served as the Web’s defacto journal of the API economy; offering news, advice, API directories, research data, and other information when it comes to the world of Internet-based APIs. Now, as a part of our continuing mission to serve as the world’s leading resource for developers, API providers and stakeholders, we’re announcing the the launch of ProgrammableWeb’s first-ever face-to-face conference; APIcon.”

    tags: bs api conference developers

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What I’m Reading on 04/04/2014

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What I’m Reading on 04/01/2014

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What I’m Reading on 03/31/2014

  • “GNU Octave is a high-level interpreted language, primarily intended for numerical computations. It provides capabilities for the numerical solution of linear and nonlinear problems, and for performing other numerical experiments. It also provides extensive graphics capabilities for data visualization and manipulation. Octave is normally used through its interactive command line interface, but it can also be used to write non-interactive programs. The Octave language is quite similar to Matlab so that most programs are easily portable.”

    tags: bs math octave

  • “The NAG Library for Python gives users of the Python language access to over 1,700 mathematical and statistical routines in the NAG Library. It has been enhanced in-line with Python2.7 and Python3, as well as an improved pythonic interface and a new python egg installer.”

    tags: bs python library nag

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For the Love of Big Data: What is Big Data?

Several weeks ago I was on the panel “Privacy and Innovation in the Age of Big Data” at the International Association of Privacy Professionals in Washington, DC USA. My role was to present the attraction and value of data but not to constantly interrupt myself with “but, but, but” for policy and privacy issues. That is, I was the set up for IBM‘s Chief Privacy Officer Christina Peters and Marty Abrams, Executive Director and Chief Strategist, Information Accountability Foundation, to talk policy. The audience was mainly privacy experts and attorneys.

I presented four slides and I previously posted those via SlideShare. Here and in three other posts I go through the bullets, providing more detail and points for discussion.

What is Big Data?

For the Love of Big Data: What is Big Data?

Big data is being generated by everything around us

I think many people are aware of the data that is available every time you do a transaction on the web or buy something in a store. In the latter case, even if you do not use a credit card, the purchase data can be used for restocking inventory, determining how well something is selling, and finding what items are often bought together. This could then be used in marketing and coupon campaigns.

Online, even more information is kept about what you did. Not only does a given vendor know what you bought, they know everything you ever bought from them. They may then guess what you will buy next. They possibly know how you rate an item and can offer you future deals based on your habits. They may also have some sense of your buying network, or “friends,” and can use this data to drive sales by giving extra incentives to those in the network who are the most influential.

Social data such as that in Twitter, Facebook, LinkedIn, and Pinterest is also used, though this is often highly unstructured. That is, it may be free text that must be interpreted. This is not always the case, however, because if you choose to specify the schools you went to from a given list, this data now has exact structure which can be mined.

Perhaps more interesting is the sensor data that is being created by the devices all around you. These include your phones, car, home, and appliances, plus wind turbines, factory machines, and many previously mechanical things that have become more electronic and increasingly connected into the Internet of Things.

Every digital process and social media exchange produces it

If a process is digital, that means data is involved. How much of that is saved and can be used for later analysis?

When you take part in a social network someone knows what you are saying, when you said it in context of your other updates, if it was part of a conversation, possibly what you you were discussing (“rotfl mebbe not”), and the influence structure of your extended network. That is, what you say is just the very beginning of a very long chain of direct and inferred collection of data.

Much of this data is actually metadata. When I do a status update on Twitter, my text is the data, but the time I tweeted and where I was when I did it are both examples of metadata.

When you use a mobile app, a lot of metadata is available too. It’s not just what you did, it’s the sequence in which you did things and with whom. This information can be used to improve the app for you, or allow the app provider to make its services, possibly paid, more attractive to you.

Systems, sensors and mobile devices transmit it

If something is connected to the Internet, it is possible for data to be transmitted and received. This might be via wifi or a cellular connection, although technologies like BlueTooth may be used for local data collection that is then later transmitted at higher bandwidth.

Not everything has to be connected all the time. Some remote machines like tractors allow farmers to employ USB sticks to periodically collect performance and diagnostic data. This may then be used for predictive asset maintenance: let me fix something as late as is reasonable but before it breaks down and causes expensive delays. In this case, the data from the USB stick might be analyzed too late, and a direct network connection would be better.

Big data is arriving from multiple sources at amazing velocities, volumes and varieties

So data is coming from everywhere, and I’ve seen estimates that the amount of metadata is at least ten times greater in size than the original information. So the data is coming in fast (velocity), there is a lot of it (volume), and it is very heterogeneous or even unstructured (variety).

As you you start making connections among all the data, such as linking “Bob Sutor” coming from one place with “R. S. Sutor” coming from another, the size can increase by another order of magnitude.

To extract meaningful value from big data, you need optimal processing power, storage, analytics capabilities, and skills

So with all this bigness, you have a lot of information and you need to process it quickly, possibly in real time. This may require high performance computing, divide-and-conquer techniques using Hadoop or commercial Map Reduce products, or streams. If you are saving data, you need a lot of storage. People are increasingly using the cloud for this data storage and scalable processing.

Now that you have the information, what are you going to do with it? Will you just try to understand what is happening, as in descriptive analytics? How about predictive analytics to figure out what will happen if trends continue or if you modify conditions? Can you optimize the situation to get the result you want? (You might want to see my short “Simple introduction to analytics” blog entry for more detail.)

Technologists are trying to get us closer to the “plug in random data and get exactly the insights you want with amazing visualizations” dream, though it may just be enough to get you started in your explorations. You need solid analytics to do valuable things with the data, and people with the skills to build new and accurate models that can then drive insights you can use.

IBM Watson Analytics is doing some interesting work in this space.

Next: Why do data scientists want more data, rather than less?

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For the Love of Big Data: Why do data scientists want more data, rather than less?

Several weeks ago I was on the panel “Privacy and Innovation in the Age of Big Data” at the International Association of Privacy Professionals in Washington, DC USA. My role was to present the attraction and value of data but not to constantly interrupt myself with “but, but, but” for policy and privacy issues. That is, I was the set up for IBM‘s Chief Privacy Officer Christina Peters and Marty Abrams, Executive Director and Chief Strategist, Information Accountability Foundation, to talk policy. The audience was mainly privacy experts and attorneys.

I presented four slides and I previously posted those via SlideShare. Here and in three other posts I go through the bullets, providing more detail and points for discussion.

Why do data scientists want more data, rather than less?

For the Love of Big Data: Why do data scientists want more data, rather than less?

It is there

This may seem simplistic, but if you are a statistician or someone looking for patterns via machine learning or data mining, you love data. A lot of data. More is better.

Data is the basis of the models we create to explain, predict, and affect behavior

Just like physics uses mathematical tools like partial differential equations to model the universe both large and small, data analytics uses other parts of mathematics like statistics, probability, and linear algebra to model what is happening by looking for patterns and behavior from the data we can discern.

Both kinds of models can vary from the very accurate to the really imprecise, depending on our skills, understanding, and information available. New techniques merge physical and data approaches to increase accuracy and decrease the computational load.

With more data, our models become more sophisticated and, we hope, more accurate

The more you know, the more you can fit together the pieces into a coherent whole. Modeling a city, for example, needs a lot of different kinds of data, and this information is often interdependent and redundant. It is non-trivial, however, to put models and simulations based on different techniques together and this often requires advanced, Ph.D.-level knowledge.

Do you know what the relationships are? That is data unto itself and improves the model. Separating the signal from the noise will help you pull out the important parts for analysis, but knowing why the noise is there will teach you about the accuracy of what you are measuring as well as how it is being measured.

How much data is too much data?

When Twitter was first available, people scoffed at the silliness of people talking about what they had for lunch, where, and with whom. Now this is called “social marketing data.”

We just don’t know what techniques we will develop tomorrow that can make better sense of the data we collect today. New work on statistical summarization can help reduce what we save, but it is best to err on the side of saving more data if you can. We might really need that detailed sales information and social media discussions going back five years to see patterns that can help your business grow tomorrow.

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For the Love of Big Data: What issues can analytics present?

Several weeks ago I was on the panel “Privacy and Innovation in the Age of Big Data” at the International Association of Privacy Professionals in Washington, DC USA. My role was to present the attraction and value of data but not to constantly interrupt myself with “but, but, but” for policy and privacy issues. That is, I was the set up for IBM‘s Chief Privacy Officer Christina Peters and Marty Abrams, Executive Director and Chief Strategist, Information Accountability Foundation, to talk policy. The audience was mainly privacy experts and attorneys.

I presented four slides and I previously posted those via SlideShare. Here and in three other posts I go through the bullets, providing more detail and points for discussion.

What issues can analytics present?

For the Love of Big Data: What issues can analytics present?

Are all aspects of privacy, anonymization, and liability understood by the practitioners?

Absolutely not, and that’s why you may need to get guidance from an attorney or a privacy professional. Look for precedent on your intended use just as much as you look for someone having done something technically similar before.

If you are a data scientist and not a privacy expert, don’t pretend to be one. It could be a stupid and a costly mistake.

Be especially careful when working with Personally Identifiable Information – data about people, often coming from HR systems within organizations.

If I tell you that you cannot look at some data but you can infer the information (e.g., gender) anyway, is that all right?

Generally, no.

This can be tricky: if you get a non-negative answer to questions about the number of weeks taken for maternity or paternity leave, you might infer the gender. Certain types of color blindness are 16 times more likely in men than women, so that and other hints might lead you to believe with high probability that someone is male.

Check local laws and policies before you engage in any sort of this “go around the rule” cleverness. It’s not just about gender. You must know privacy restrictions before you start playing with data.

It’s also not just about personal data. If I’m a farmer and you have data about what is growing in my fields, that is my data. I very possibly care what you do with it. This is not just an ownership question: does the data tell you more about me and how I operate than I want to share with you?

What are the rules for working with metadata and summarized data?

If I tweet something, the metadata about that includes when I tweeted it and maybe where I was (location data is not always available). Summarized data might be a statistical snapshot that gives you information about means, standard deviations, counts, and so on. Other technology can start with a very big data set and produce a smaller one that has many of the same statistical properties you care about.

Assume, to start, that data, metadata, and summarized data all have the same privacy restrictions. If I cannot move data out of an organization or a country, assume the same about the other two. From there, look to see if laws or contractual agreements soften this at all.

You may need to know where the data resides. If you put the data in a cloud, can you guarantee that it never leaves a country’s boundaries if that is a requirement?

How do we process static, collected data together with more real-time, rapidly changing information such as location?

This question is really asking about how we combine traditional structured information in databases—Systems of Record—with data and metadata coming from social, mobile, and Internet of Things interactions—Systems of Engagement.

While some analytics can be done in batch mode that is relatively non-urgent, some must be done in close to real time. If you are looking to make a stock transaction based on fluctuations in the market, you can’t wait 12 hours after you’ve crunched the numbers all night. If you need to adjust a patient’s treatment based on information streaming in from 5 different kinds of sensors, sooner rather than later will more likely guarantee a better result.

However, if you analyzing the sales results for the last year to better understand why revenue was up in some geographies yet down in others, that can be done in batch. This may mean you use something like Hadoop to break the problem into smaller pieces and then recombine the results at the end, but this is not the only technique. It really depends on the amount and type of data. Similarly, if you are doing healthcare analytics based on longitudinal studies of patients’ responses to treatment regimens, it does not have to be done in real time.

Analytics today often use a combination of static collected data with information that is coming in quickly. Techniques like map/reduce are combined with streams. Data may be put in traditional relational databases, social and network graph databases, other NoSQL databases, or just discarded after it is seen.

The trick is to combine the right underlying big data information management infrastructure with the right analytics and mathematical techniques to achieve the result you need.

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For the Love of Big Data: Approach to policy can determine outcomes

Several weeks ago I was on the panel “Privacy and Innovation in the Age of Big Data” at the International Association of Privacy Professionals in Washington, DC USA. My role was to present the attraction and value of data but not to constantly interrupt myself with “but, but, but” for policy and privacy issues. That is, I was the set up for IBM‘s Chief Privacy Officer Christina Peters and Marty Abrams, Executive Director and Chief Strategist, Information Accountability Foundation, to talk policy. The audience was mainly privacy experts and attorneys.

I presented four slides and I previously posted those via SlideShare. Here and in three other posts I go through the bullets, providing more detail and points for discussion.

Approach to policy can determine outcomes

For the Love of Big Data: Approach to policy can determine outcomes

Reductions in the amount and kinds of data can produce diminished or inaccurate results

I think this is obvious: if crucial data that could help define the context is missing, then the model will probably be incomplete. Therefore, it will be hard for you to produce results that have a high confidence level, or you will be missing factors that are needed for better prediction or optimization.

Think of all the data that is necessary to predict how a particular farm field of tomatoes will do during this next summer season. Geography with elevation, expected sun and rain amounts, wind, soil conditions, planned fertilization, and natural or irrigated water supply all have an effect on what will actually happen. If your model is missing these, your prediction or your ability to tweak the factors to maximize yield will be compromised.

Policy must take into account the value received by individuals for the use of their personal data

You as a consumer may happily give a coffee shop information about your  location in order to get a discount on your next beverage. This is not exactly being “off the grid.”

Increasingly people are willing to give up personal information in exchange for discounts, higher quality, and position within social networks. Formal policy must take into account that privacy is not a fixed idea and will vary over time from person to person as more lucrative items can be traded for it.

Enforced data localization may decrease analytical completeness unless we can move intermediate results or the site of computation

If I am forced to keep all my data, metadata, and derived results within some geographical boundaries, my ability to combine these with information elsewhere will be curtailed. Can we move those other results to the constrained site for more extensive computation? Indeed, can we move the computation to the data instead of the other way around?

These are issues of both policy and cloud technology. What we do and where we do it is limited by both, but as technology often seems to advance far faster than policy, there will be a mismatch between what we can (and should) do with what we are allowed to do.

Big Data is not just about the data. It is about the intended use and the location of that use. Privacy, security, and data ownership are all important considerations that must be factored in before we do the “science” with the data.

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What I’m Reading on 03/27/2014

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What I’m Reading on 03/24/2014

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What I’m Reading on 03/20/2014

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What I’m Reading on 03/19/2014

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What I’m Reading on 03/18/2014

  • “Like Mountain Lion (OS X 10.8) and Lion (OS X 10.7), Mavericks (OS X 10.9) doesn’t ship on a disc—it’s available only as an installer app downloadable from the Mac App Store, and that installer doesn’t require a bootable installation disc. But there are a good number of reasons you might want a bootable Mavericks installer on an external hard drive or a thumb drive (USB stick).”

    tags: bs mavericks osx

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What I’m Reading on 03/14/2014

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What I’m Reading on 03/13/2014

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What I’m Reading on 03/11/2014

  • “The Directorate for Computer and Information Science and Engineering (CISE) announces a nationwide search to fill the position of Director, Division of Information and Intelligent Systems (IIS). Formal consideration of interested applicants will begin on March 17, 2014 and continue until a selection is made. Appointment to this position may be under the Intergovernmental Personnel Act (IPA) provisions1. Alternatively, the incumbent may be assigned on a one- to three-year limited-term Senior Executive Service (SES) position.”

    tags: bs nsf

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What I’m Reading on 03/10/2014

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What I’m Reading on 03/07/2014

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Presentation: For the Love of Big Data

This is a presentation I gave yesterday at the International Association of Privacy Professionals in Washington, DC USA, on March 6, 2014. This short presentation was meant to stimulate ideas that would then be complemented by discussions about privacy policies as it relates to Big Data, and in that sense is not complete regarding all aspects of privacy that come from the issues discussed.

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What I’m Reading on 03/06/2014

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What I’m Reading on 03/03/2014

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What I’m Reading on 02/27/2014

  • “Lowe’s said on Wednesday that it has been gauging traffic at its almost 1,900 stores from space, scanning satellite images of its parking lots to find out how many shoppers it can expect at every hour of every day. It has also started syncing its parking lot observations with actual transaction counts to see how many people drove away without making a purchase.”

    tags: bs satellites lowes

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What I’m Reading on 02/25/2014

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What I’m Reading on 02/24/2014

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What I’m Reading on 02/23/2014

  • “I named my first opensim region Orcas after a real world island.  I decided to try and see if I could get the actual Orcas Island terrain into OpenSim to see how it looked and uncover any challanges one might face in bringing RL terrain into OpenSim.  This tutorial will walk you through the process I followed and and various software packages required to make this happen (done on Windows).  The net, net is I succeeded, but the results were uninspiring.”

    tags: opensim

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Virtual Life with Linux: Standalone OpenSim on Ubuntu 13.10

This post is a great example of why you should never say that you are starting a new series of blog entries. In February of 2010, I wrote a blog post called Virtual Life with Linux: Standalone opensim on Ubuntu 9.10 saying

As a complement to my Life with Linux blog series, I’m introducing another series which explores what I can do in virtual worlds and immersive Internet environments on Linux.

I wrote two entries, and that was it. Well, here is the third entry, notes from trying to install the latest version of OpenSim on Ubuntu Linux 13.10. I’m not going to go through all the steps involved, but mostly talk about some of the glitches I encountered and how I resolved them.

First, some notes on Ubuntu 13.10. I have a dual boot pc with Windows 7 and Ubuntu on it. I used to do a lot with Linux because it was my job and also because I loved the experience of trying all the distros, seeing what was new, and playing with the features. Well, I moved on to a job involving mobile and then running the math department in IBM Research, and I really did not touch Linux for a long time. Long as in the version of Ubuntu on my machine being from 2009.

I fired this up several weeks ago and started the upgrade process, which was excruciatingly slow. Somewhere in there I accidentally hit the power button on the computer and that pretty much wiped out the Ubuntu image. Don’t do that. I eventually burned a DVD of Ubuntu 13.10. Once again the updates were really slow.

This weekend I did the clever thing and did a web search for “slow Ubuntu updates.” The main suggestion was that I find a mirror closer to me, and this made a huge difference. I went into the Ubuntu Software Center, picked Edit | Software Sources, went into Download From, picked Other…, and found a mirror 40 miles from my house. Problem solved.

32 bit Libraries

I installed the 64 bit version of Ubuntu but you are going to need the 32 bit libraries. There’s a lot on the web about how to do this for older versions of Ubuntu, how you should use multiarch libraries, how you don’t need to do anything at all, and so on. Eventually I found this solution and it worked, from the forums for the Firestorm virtual world viewer. There are other ways to accomplish the same thing, but this does the job.

sudo apt-get install libgtk2.0-0:i386 libpangox-1.0-0:i386 libpangoxft-1.0-0:i386 libidn11:i386 libglu1-mesa:i386

sudo apt-get install gstreamer0.10-pulseaudio:i386

Mono

You need the complete mono package, not just what you install from the Ubuntu Software Center.

sudo apt-get install mono-complete

See the OpenSim build instructions for other platforms.

MySQL

Install the client and the server from the Ubuntu Software Center. You will be asked for a root password, so write it down somewhere.

Getting OpenSim

There are several ways of getting and installing OpenSim. When I last did this four years ago, I took a “from scratch” approach but I’m doing it more simply now. I used the popular Diva Distribution of OpenSim which comes set up for a 2×2 megaregion (that is 4 regions in a square that behave like one great big region). What you lose in some flexibility you gain in ease of installation and update. Once you download and expand the files, start reading the README.txt file and then the INSTALL.txt file. Other files will tell you more about MySQL and mono, but you did the hard work above.

Since I am not connecting this world to the Internet, I did not bother with the DNS name, I simply used localhost at 127.0.0.1.

Follow the instructions for configuring OpenSim and getting it started. You’ll need to give names for the four regions, which I’ll call R1, R2, R3, and R4. These are laid out in the following tile pattern:

R2
(northwest)
R4
(northeast)
R1
(southwest)
R3
(southeast)

You will need to know this if you decide to change the terrains for your world.

For example, suppose you had four terrain files called nw.raw, ne.raw, sw.raw, and se.raw in the terrains subdirectory of your OpenSim bin directory.

Then you would issue the following from within the OpenSim console to set the terrains for the regions:

change region R1
terrain load terrains/sw.raw
change region R2
terrain load terrains/nw.raw
change region R3
terrain load terrains/se.raw
change region R4
terrain load terrains/ne.raw

A web search will find you many options for terrains. Basically, they are elevation files for your region.

Getting a Browser

I believe that all the popular common browsers out there for OpenSim are evolutions of some major versions of the Second Life browser after they were open sourced. This OpenSim page has details on your options. If you have a choice, get a 64 bit browser if you are using a 64 bit Linux. I’ve had good luck with both Firestorm and Kokua.

Other Approaches

Maria Korolov extensively describes the different ways of getting an OpenSim region up and running in her article OpenSim 102: Running your own sims. In particular, she discusses New World Studio, and I’ll be trying to get that running on my MacBook.

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Second Life and OpenSim revisited

Several years ago I spent quite a bit of time in Second Life when it was the hot 3D social world. The promise was that you could build and visit worlds that had been uniquely constructed by the users. As such, it was dynamic environment that tended to be slow as all the shapes, buildings, and textures were loaded.

Second Life alter egoPeople can customize their in-world presences extensively, from body shape to the clothes and decorations worn. Indeed, you don’t even need to look like a person. Note, however, that you probably should not show up to a business meeting in Second Life in the form of a squirrel, as my now-retired IBM colleague Irving Wladawsky-Berger once said.

Over time, Second Life fell out of fashion as a world where businesses could set up sites where clients or interested people could visit, learn about products or services, and talk to real people, albeit in avatar form.

For internal business meetings, the lack of truly secure conversation was a problem. We used teleconferences for the voice, and Second Life for the environment. As meetings went on, participants often went inactive, or fell asleep, in Second Life, and we were back to phone meetings as usual.

Second Life lives on today as a social world. That’s never been much of an interest to me, but to each his or her own. It seems to be quite vibrant across a broad range of what “social” means.

My interest in it was always more in the construction aspects, and I’ve written extensively about the techniques involved. See Building in Second Life, By Example. I still get many links to this site from people looking to build moving doors, for example. I also had a long series of blog entries about how to do things in Second Life called My Second Life. Note that this is from 2006, so it is getting a bit old.

You can see all my writings on Second Life by going to the top of this page and entering “second life” in the search box on the right side.

Here is the net for me with Second Life: it is too expensive to be as slow as it is, especially if I only want to use it as an advanced 3D building environment. While new ways of building objects have been introduced, it’s hard to see a lot of difference from the way it was five years ago. I still visit from time to time, but I own no land and spend no money there.

OpenSimulator, or opensim for short, is a reimplementation of the Second Life server in open source. It is written in C#, so requires Microsoft Windows or the Mono environment on Linux. It does not include a browser, but several are available.

Other than the OpenSim site itself, the best source of information about the technology and the worlds built with it is Maria Korolov’s Hypergrid Business. It is excellent.

Some of the features of OpenSim include:

  • an active development community
  • better in-world programming options
  • the ability to host a world on your own computer, which is completely free
  • many online paid hosting options
  • the ability to connect your world to several choices of “grids,” or collections of worlds
  • teleporting from one world to another across a grid

This means that I could set up a world on my local computer, do all the building I want on it, save an image, and then transfer it to a hosted server. If you can and want to connect your computer to the Internet, you can host your world from there and have others visit it.

To see a modern use of OpenSim, read the article $250,000 project models cities in OpenSim.

Some of the potential downsides are:

  • hosting providers come and go, though some have been around for years
  • it may be more difficult to find assets you need at the quality you want, for example textures, but there are guides for finding free content
  • it is probably best if you have some technical chops or know someone who does

So Second Life costs money to own land and to buy some assets, and is more restrictive. OpenSim and the worlds and grids associated with it provide more freedom, but you are more on your own and there might be some long term risks related to hosting. For me, the freedom is worth the risk.

In 2010 I wrote a blog entry called Virtual Life with Linux: Standalone OpenSim on Ubuntu 9.10. I’ve recently gone through the experience of doing this on Ubuntu 13.10. I’ve published some notes on what I did this time to install on my pc in Virtual Life with Linux: Standalone OpenSim on Ubuntu 13.10.

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What I’m Reading on 02/21/2014

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What I’m Reading on 02/18/2014

  • “For RHEL6 and newer distributions tools are available to profile Python code and to generate dynamic call graphs of a program’s execution. Flat profiles can be obtained with the cProfile module and dynamic callgraphs can be obtained with pycallgraph.”

    tags: python

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Map and Elevation Data

For a small personal project I’m starting, I wanted to get elevation data for the area surrounding our property in upstate New York. A quick web search yielded the The National Map website, a service of the US Geological Survey.

NY Elevation MapThe information and products on the site are extensive, but for my purposes I followed the link to The National Map Viewer and Download Platform. From there I zoomed down to the area of our house, and started looking at what was available. After several experiments, I decided to download a portion of the National Elevation Dataset at 1 arc second resolution. The 1/3 arc version was also available, but, as expected, was 9 times bigger.

The readme.pdf file starts with the following:

The U.S. Geological Survey has developed the National Elevation Dataset (NED). The NED is a seamless mosaic of best-available elevation data drawn from a variety of sources. While much of the NED is derived from USGS Digital Elevation Models (DEM’s) in the 7.5-minute series, increasingly large areas are being obtained from active remote sensing technologies, such as LIDAR and IFSAR, and also by digital photogrammetric processes. Efficient processing methods were developed to filter production artifacts in the source data, convert to the NAD83 datum, edge-match, and fill slivers of missing data at quadrangle seams. NED is available in spatial resolutions of 1 arc-second (roughly 30 meters), 1/3 arcsecond (roughly 10 meters), and 1/9 arc-second (roughly 3 meters). The dataset is updated with “best available” elevation data on a two month cycle.

These digital elevation datasets are essential in understanding the Earth’s landscape: elevation, slope, and aspect (direction a slope faces.) NED is critical to identifying and modeling geologic features such as water drainage channels and basins, watersheds, peaks and pits, and movements such as avalanches. NED is used to create relief maps, 3-D visualizations, to classify land cover and to geometrically correct data from satellite or aircraft sensors (orthorectification). The fire community, natural resource managers, urban planners, conservationist, emergency responders, communication companies to name a few all rely on these elevation datasets. This data also supports The National Map.

Now I have to figure out how to process the file, which I’ll do by looking at the data dictionary elsewhere on the site and writing some Python code.

Update: Even though I zoomed down to a rectangular area less than one block on a side, the downloaded data contains a 1 second by 1 second square of elevation data.That’s more data than I was expecting and I’ll have to pull out a subset.

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What I’m Reading on 02/16/2014

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What I’m Reading on 02/13/2014

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What I’m Reading on 02/12/2014

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What I’m Reading on 02/11/2014

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What I’m Reading on 02/10/2014

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What I’m Reading on 02/07/2014

  • “When you get traction with software, you fire up new servers and scale your infrastructure. It is fast and cheap. And traction alone can get you funding. With hardware, traction is sales, or at least demand. Unfortunately, sales of physical things happen months after production. How do you finance it? How many units should you build? Can you afford to lose money or time?”

    tags: retail makers

  • Amazon has acquired a gaming studio called Double Helix Games, TechCrunch has learned, and Amazon now confirms. The deal was for both talent and IP, we understand. Financial terms have not been disclosed.”

    tags: amazon gaming

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A tale of two Aprils in the Adirondacks

This has been a long hard winter in the northeastern United States, and I don’t think we’re done yet. Earlier this week New York and Philadelphia got several inches of snow topped by ice. More upstate in New York where I live, we only got light fluffy snow, but we got a foot of it.

Being February and knowing that we have close to two months before we are likely to see the last of the snow, my thoughts often go to summer. In particular, to summer in the Adirondacks where we have a family place on Cranberry Lake.

I try to get up there in April to check the place out after the long winter, looking for downed trees and telephone lines. This is what it looked like last April 15:

Cranberry Lake in April 2013

The left front corner of the dock is pushed into the ice, which was still probably 8 to 10 inches thick. Later in the spring, the dock broke loose on the right side and swung around way to the left. I’m hoping that does not happen when the ice goes out this year.

In contrast, this was the dock a year and a day before the above photo, on April 14, 2012:

Cranberry Lake in April 2012

I don’t recall the exact temperature, but I’m guessing it was in the upper 40s or lower 50s F. The ice had been gone for nearly a month.

With our winter so far this year, I’m suspect that this April will look like last year at the lake. Being an optimist, I’m pulling for the warm, sunny, ice-free version.

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What I’m Reading on 02/06/2014

  • “Today no one dies from standard wars, not that you’d know it from Internet comments. But years, millions of dollars, and endless arguments are spent arguing about standards. The reason for our fights aren’t any different from those that drove Edison and Westinghouse: It’s all about who benefits – and profits – from a standard.”

    tags: standards

  • “People have all sorts of reasons for connecting their homes. Some people want to monitor the nanny, or keep an eye on things for security or safety reasons. Others just want to see what their pets do when they’re not around. I happen to fall into the latter camp.”

    tags: cats iot

  • “It might surprise you just how often large companies give away their code to the open source community. At that point, anyone can contribute, debug, or download the code from a repository on GitHub or the Apache Software Foundation—and then use it for themselves. “

    tags: open source

  • “He’ll arrive at the lab just in time to participate in a major new initiative aimed at doing just that. Project Lucy is a 10-year, $100 million effort by IBM to work with governments, universities and development organizations to address Africa’s grand challenges. A key element will be harnessing IBM Watson, which beat two grand-champions on the TV game show Jeopardy! IBM announced the initiative today while Chief Executive Ginni Rometty and members of her senior executive team were meeting with government and business leaders in Nigeria.”

    tags: project lucy africa ibm

  • “There are extensions that stand alone, and others that add value to existing apps and web services. Some are so useful that Chrome users should take a look and see what they are missing.”

    tags: chrome extensions

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What I’m Reading on 02/05/2014

  • “Computer scientists at IBM have already built a computer that can beat human contestants on the TV quiz show, “Jeopardy.” Now it appears they’re sharpening their intellectual knives to make a computer that might someday challenge the competitors on “Iron Chef.””

    tags: computers chefs

  • “”Dell has always been dedicated to driving practical innovation, which its individual business units have pursued organically and led in innovative areas such as iSCSI,” Jai Menon, vice president of research and innovation and head of Dell Research, told EE Times. “The new Dell Research organization is a recent addition to Dell’s innovation focus within the last six months, charged specifically with research and innovation from a long-range, disruptive, and pan-Dell perspective.””

    tags: dell research

  • “From Captain America and Spider-Man to Wolverine and Iron Man, Marvel Entertainment, a Disney subsidiary, has built an empire by bringing more than 8,000 characters to life through a diverse array of mediums, including comic books, movies and other entertainment properties. Now, it’s giving those characters a new medium to inhabit: the world of the API.”

    tags: marvel

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What I’m Reading on 02/04/2014

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Monthly disclaimer

The postings on this site are my own and don’t necessarily represent my employer’s positions, strategies or opinions.

Blog entries before 2010 are in my Archived Blog.

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What I’m Reading on 01/30/2014

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What I’m Reading on 01/28/2014

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What I’m Reading on 01/27/2014

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What I’m Reading on 01/25/2014

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What I’m Reading on 01/24/2014

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What I’m Reading on 01/23/2014

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What I’m Reading on 01/22/2014

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What I’m Reading on 01/20/2014

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Treadmill Desk

For several weeks my wife has been asking me to convert our old Proform treadmill into a treadmill desk. The idea, exercise-wise, is to be on the treadmill for several hours a day at speeds less than 2 mph.

Treadmill desk

This weekend my son and I did it, and the conversion was straight-forward. To start, we moved the treadmill into my wife’s home office and then removed the walking-pole like handles and the decorative guards where the hand supports connected to the treadmill console. This allowed the treadmill to fit in the space better and allowed us more access to attach the desk.

I then cut a 12 inch deep piece of 3/4 inch birch plywood that I happened to have in my shop, and cut it to the outside width between the handles. This is the actual desk and the 12 inches was sized to the necessary dimension to fit my wife’s MacBook Pro. I rounded off all the edges with a router and then sanded them to make them as smooth as possible.

To mount the desk, I drilled holes in the corners of the plywood approximately 1 inch in from each side. To make these smoother, I used a counter sink on both sides of each hole. I then use plastic corner ties to attach the wood to the bottom of the treadmill handles. The tie connectors were on the bottom side of the wood and the excess plastic straps were trimmed.

This mounting position was approximately the right the height for my wife. If you need it lower, you can put wooden strips or blocks between the desk and the handles. Similarly, if you want it higher, you can mount it on the top. The idea is to have the laptop keyboard at a comfortable height that you can use while walking.

The laptop screen is too low for comfortable use, so I added a 19 inch Samsung LED TV with an HDMI input and mounted it (VideoSecu TV Wall Mount Articulating Arm Tilt Swivel Bracket) on the bookcase/wall in front of the treadmill. While the mounting hardware is adjustable, I suspect I will be raising it an inch or two as my wife gets more experience in using the desk. It should be at a comfortable height so you can look straight ahead and not crane your neck.

Possible things yet to do: put a couple of coats of water-based polyurethane on the wooden desk, raise the TV, and strap down all cables.

Treadmill Desk, Front View

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What I’m Reading on 01/18/2014

  • “Spark wanted to show it could create an open-source Nest-like thermostat using Spark Core, its Arduino-compatible development platform for building Internet-connected hardware. The result isn’t an exact duplicate, but it’s not a bad approximation for a day’s worth of work. For example, instead of a glass and aluminum enclosure, which Nest uses, Spark opted for acrylic and wood for its prototype. The company put up step-by-step directions for people to build their own learning thermostats in a blog post published “

    tags: nest spark thermostat

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What I’m Reading on 01/17/2014

  • “This collaboration strengthens Red Hat‘s proven business model by extending the Red Hat open source development ecosystem. Red Hat anticipates that taking a role as a catalyst within the CentOS community will enable it to accelerate development of enterprise-grade subscription solutions for customers and partners, such as Red Hat Enterprise Linux, Red Hat Enterprise Linux OpenStack Platform, Red Hat Cloud Infrastructure, Red Hat Enterprise Virtualization, Red Hat JBoss Middleware, OpenShift by Red Hat, and Red Hat Storage.”

    tags: centos red hat

  • “That’s all changing with the news last week that CentOS will join Red Hat, said Karanbir Singh, CentOS project leader and one of four CentOS developers going to work for Red Hat as part of the new collaboration. For the first time, developers will work on CentOS professionally and that’s created a “paradigm shift” for the project and its contributors, he said.”

    tags: centos red hat

  • IBM is moving rapidly on its plans to spend heavily on cloud computing. It expects to spend $1.2 billion this year on increasing the number and quality of computing centers it has worldwide.”

    tags: ibm cloud

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What I’m Reading on 01/16/2014

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What I’m Reading on 01/15/2014

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Monday Dylan: Mr. Tambourine Man, Two Ways

This is a Dylan classic from 1965′s Bringing It All Back Home album.

This first video of the song is from the 1964 Newport Folk Festival where Dylan is introduced by Pete Seeger.

Move forward 26 years to 1990 and we have Dylan joining many of the original Byrds performing the song at a Roy Orbison tribute concert.

I’ve never been that thrilled with the Byrd’s versions of Dylan’s songs, but this is a fun take on it. There’s a lot of energy and excitement in the crowd when Bob walks out a couple of minutes into the song. Rolling Stone magazine has an article about the reunion.

Also see:

Previous: Thunder on the Mountain

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What I’m Reading on 01/07/2014

  • “Nowadays, devices and people are unceasingly uploading all kinds of information about the economy, locations, weather and even what sweater makes them happy. With this flood of data, some believe traditional ways of displaying information do not work well anymore. So there is a demand for Mr. Rodenbeck’s sort of creative thinking about the humble pie chart.”

    tags: maps makeover visualization

  • “Ghost is a platform dedicated to one thing: Publishing. It’s beautifully designed, completely customisable and completely Open Source. Ghost allows you to write and publish your own blog, giving you the tools to make it easy and even fun to do. It’s simple, elegant, and designed so that you can spend less time messing with making your blog work – and more time blogging.”

    tags: ghost open source blogging platform

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What I’m Reading on 01/06/2014

  • “”Her,” a movie about a man falling in love with a piece of voice software, has been in theaters for about three weeks. (The premise is more plausible than you think.) So it was inevitable that someone would ask Apple‘s own voice-command assistant: Are you her from ‘Her’?”

    tags: siri

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What I’m Reading on 01/04/2014

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What I’m Reading on 01/03/2014

  • “The term “DevOps” emerged from the fast-paced “agile” software development movement. Agile practices encourage short iteration cycles, frequent new function releases and close collaboration between development and business stakeholders. It’s made quick revisions a common practice, which in turn has increased the need to produce software in a way that delivers ideas to market in a much faster model. Both established companies and startups are racing to test their innovative ideas and provide value for their customers.”

    tags: startup devops

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What I’m Reading on 01/02/2014

  • “The new F-150 is expected to use 600 pounds of aluminum, replacing about 1,000 pounds of steel, according to industry consultant Ducker Worldwide. The move accounts for a big chunk of the 750 pounds that Ford has vowed to cut to improve fuel economy.”

    tags: ford aluminum

  • “Inspired by conversations on the FOOD52 Hotline, we’re sharing tips and tricks that make navigating all of our kitchens easier and more fun. Today, how to achieve personal fried-egg perfection. Emphasis on the personal.”

    tags: egg

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What I’m Reading on 01/01/2014

  • “If you have forgotten your Galaxy Note’s password, you can unlock the device without a factory reset, but only if you can answer your security question or if you have a Google Account set up on the phone. Note that the Google login prompt only displays after several unsuccessful attempts with your password. If you do not have a Google Account associated with the tablet or a security question configured on the device, you must do a factory reset to recover your device’s password.”

    tags: password galaxy note

  • “What follows are some of the easiest food-related resolutions you will ever make, from cooking big pots of grains and beans once a week, to buying frozen produce, to pickling things à la “Portlandia.” Committing to just a few of these, or even one, will get you moving in the right direction toward eating more plants and fewer animal products and processed foods. My suggestions are incremental, but the ease with which you can incorporate them into your normal shopping, cooking and eating routines is exactly what makes them sustainable and powerful.”

    tags: sustainable resolutions diet

  • “The shrimp in question are called Northern shrimp or, more locally, Maine shrimp. They are the southernmost appearance of a species, Pandalus borealis, that can also be found in Canadian and Icelandic waters, but the ones caught here in the Gulf of Maine tend to be at the bigger end of the species. They are usually caught in the winter, when females come close to shore to lay their eggs in cold water. They are smaller and typically sweeter than warm-water or farmed shrimp, with delicate, edible shells, and are popular in European and Scandinavian markets, although New England chefs use them, too.”

    tags: maine shrimp

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The postings on this site are my own and don’t necessarily represent my employer’s positions, strategies or opinions.

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What I’m Reading on 12/31/2013

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What I’m Reading on 12/28/2013

  • “The keys to this much-improved homemade Sriracha were a longer fermentation and the addition of smoked sea salt and xanthan gum. The change that made the biggest difference, however, was mixing in some green jalapeños and serranos. The milder green peppers mellowed out the up-front heat present in earlier versions, bringing balance to the sauce. 

The result is a sauce that is a bit hotter than the Huy Fong version, but with all the earthy complexities that make it so darn tasty.”

    tags: Sriracha

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What I’m Reading on 12/25/2013

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Monday Dylan: Thunder on the Mountain

I think this song has some of the best lyrics from the most recent phase of Dylan’s career:

I got the porkchops, she got the pie
She ain’t no angel and neither am I
Shame on your greed, shame on your wicked schemes
I’ll say this, I don’t give a damn about your dreams

Still Dylan being warm and fuzzy. Also, I wouldn’t have thought of the rhyme for “orphanages” that he uses here.

The song is from the Modern Times album, my pick from the 2000′s to start your Bob Dylan music collection.

The video is a collection of Dylan in performance and snippets from other videos through the years. It appears to be an official release from SONY and not a YouTube contributor amalgam.

Also see:

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What I’m Reading on 12/19/2013

  • “”The autonomous car’s first commercial appearance will not be at your local dealership,” Angle insists. “The obvious low-hanging fruit is package delivery, a $50 billion industry. Why not challenge UPS or FedEx, or sell your technology to those companies?””

    tags: google robot

  • “A little earlier we ran a story about a video that showed what appeared to be a Yahoo Siri competitor. “Sources familiar with Yahoo’s internal projects tell us that the video is fake,” we wrote. Well, it turns out that this isn’t the whole story. It’s true that Yahoo didn’t make the video itself, and it didn’t make the app, but that doesn’t mean Yahoo isn’t involved. The app was made by a natural language/speech recognition/navigation startup Robin Labs, in discussion with Yahoo.”

    tags: yahoo siri

  • “Could a Siri- and Google Now-like personal assistant be one of the results of the company’s labor? According to a report on Wednesday by Android Police, seems so. The Web site says that Yahoo is working on a voice-activated assistant, and the report has an accompanying video that shows an Android phone running the app the app branded with the familiar “Y!” logo.”

    tags: yahoo siri

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What I’m Reading on 12/18/2013

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What I’m Reading on 12/17/2013

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Monday Dylan: Things Have Changed

As a much later counterpoint to the album and song The Times They Are A-Changin’, this song was part of the soundtrack for The Wonder Boys film soundtrack in 2000 and is on the The Essential Bob Dylan album. I like it because of the song itself but also because it shows the significant change in direction Dylan took his music when he got older.

Also see:

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What I’m Reading on 12/15/2013

  • “In the past decade, philosophers and physicists have started to take the idea a bit more seriously, led by philosopher Nick Bostrom, who first published his paper “Are You Living in a Computer Simulation?” in Philosophical Quarterly in 2003. Basically, Bostrom argues that the exponential growth of computing power seems to indicate that one day we’ll be able to create a digital simulation of our entire universe. There’s also no reason to think multiple simulations wouldn’t be created once the capability is there.”

    tags: matrix science

  • “It’s not often that a year of cookbooks can be summed up in a single word. But in 2013, “uneven” fits. With a few exceptions, small books outshone the big ones. Lots of niches were explored. Vegetarians were treated to a rich buffet. While some restaurant chefs kept home cooks in mind, others seemed more interested in chronicling their impossibly perfect plates. We chose the ones we think you’ll learn from and pepper with sticky notes. Here are the Top Ten in alphabetical order, plus favorites among individual categories. See the full list “

    tags: cookbooks washington post

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What I’m Reading on 12/12/2013

  • “The system uses text mining, analytics, and statistical reasoning similar to that of the Watson system. Where the virtual chef differs with its cognitive cousin is not only in its understanding of food chemistry, but its ability to generate results not found in any data source. With existing recipes as a starting point, the team began weaving in algorithms that could one, select ingredients, and two, generate entirely unique recipes for we humans to then creatively cook.”

    tags: smarter planet ibm chef food

  • “Granting a flashlight app permission to use the device’s GPS has nothing to do with how the app operates, but everything to do with the app being free. Find out about the real cost. “

    tags: android gps flashlight permission

  • “There always seems be some shame in having breakfast for dinner. Every time someone scrambles up an egg, or plops some pancake batter on the griddle, there’s an accompanying feeling of not being a Proper Adult. PAs clearly know the difference between breakfast and dinner, and feed their family the appropriate meal for the hour (and also never, say, get past-due notices for their forgotten health insurance co-pays). But I argue that we should let go of those prejudices.”

    tags: kitchen

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