Hottest stocking stuffer this holiday season?

Google Cardboard, the under $10 device that allows you to experience virtual reality with you smartphone is my selection for the most popular gift this year. 

Everyone who sees it gets a big smile on their face followed by, "Oh my gosh" or "How does this work?" Or "Wow!"  

By leveraging the smartphone which already has a chip, accelerometer, GPS, hi-res display and app stores, Google has hit a home run almost like Chromecast. The price cannot hurt either. 

So what can you do with it?

1.  The Cardboard app has a some great use cases highlighted by the demo video. This is a great place to start. 

2.   VR reality apps like roller coaster experiences

3.   The palace of Versailles is a great example of a virtual tour guide. 

4.   Collection of great photospheres in the updated Google Street View app  I loved the Sagrada Familia and Machu  Pichu. 

5.  The NY times app (NYT VR) with its great refugee camp story and the incredible Mini Cooper memories video. 

6.  Watch 360 degree videos on YouTube (Android only for now). You can find this on the #360 Video channel. The resolution of these videos is nowhere near the NYT app

7.   The most crazy thing was seeing my own street in Google Streetview.  It was almost like standing there on the street looking at my house but I was playing with this inside the house.  The clash of RL and VR took my breath away for a second. The only thing that prevented it from being perfect was the Streetview was shot in the height of summer and right now it is the fall with almost no leaves left. 

It was a great experience and it is just the start of the journey. Looking forward to some great applications of this technology except we will probably see a spate of 3D selfies. 

Making sense of Wi-Fi Sense - Different implications of Home vs. Business!

With the roll out of Windows 10, the feature that is ruffling the most feathers is Wi-Fi sense.

What is Wi-Fi Sense? 

Wi-Fi Sense lets you "automatically" share your password to access Internet using your router with a "friend". Before you get all hot and bothered, there are a few caveats:

• You have to first tell Windows 10 that you do want to share that particular router's information
• You then have to select which group of contacts (outlook, skype or Facebook) will be able to get this information
• The contacts have to have a Windows 10 device
• The password that is shared is encrypted
• The contact cannot share the connection information with their contacts without knowing the actual password - which they don't because it is encrypted.
• They cannot connect with Wi-Fi Sense unless they themselves as shared one of their own connections.

What does this all mean in practical terms?

Setting 1 - Home

The most likely setting is when you have a friend visiting your home and needs Internet access.

Scenario 1.

If the following four conditions are met:

1. They have a Windows 10 device
2. They have WiFi Sense turned on and are sharing one of their own connections
3. You have WiFi Sense turned on and are sharing you own Internet connection
4. They are in your Outlook.com or Skype or FB contact lists

Then they will be automatically connected to the Internet without asking you for the password.

They will not be able to share this information with their own contacts (unless those contacts are also your contacts in one of the three groups listed above).

WiFi Sense options in Windows 10

Thus this scenario does not pose much of a concern for me.

Scenario 2.

There is the alternative scenario that is more bothersome.  Suppose you did NOT turn on WiFi Sense.  Then they will have to ask you for the password.  Often you will just tell them the password or write it down for them.  If they have a Windows 10 device, they can now share this information with their contacts.  This is because they just need to know you password when they elect to share the connection information.

So my suggestion:

If a friend has a Windows 10 device, do one of two things

1. Turn on WiFi Sense so they get an encrypted password.  The conditions listed above in Scenario 1. would still need to be met.  OR a lot simpler:
2. Offer to type in the password for them (without them seeing it) on their device and select
   'Not shared'.  If they ever want to turn sharing on, they will be asked for the password which they will not have.  

Setting 2 - Small Business

Now take a different setting - a small business for example
They could actually turn WiFi Sense on and tell people to connect with them on Facebook.
If they do, they would automatically get free WiFi!
This might become a great marketing tool once Windows 10 becomes more ubiquitous.
Of course the person would need to have to use their own Internet access to connect to Facebook first and then they would be able to get WiFi through the small business or they could have added them on Facebook ahead of time.
I am not sure if this would work right now for FB pages or just for FB friends.  But with this does seem quite possible in the not too distant future.

Creating 3D models with your SmartPhone

Creating a 3D digital representation of a real life physical object seemed like an impossible task for an amateur. But now this has become quite simple for anyone with a smartphone.

I tried my hand at this using 123D Catch (by Autodesk)  to explore the ease of use, quality of output and ability to share and export.  

Here is the link

To view the 3D rendering

1. Click on the image or link above
2. On the page that loads, click on 3D view (at the bottom of the image)
3. You can use your mouse for navigation control (click on "?" for instructions or see below)

What did I learn from this exercise?

1. The process was quite simple - all you need is the app and a smartphone
2. Make sure you take shots from about the same distance, with good lighting and follow the grid on the app.  It is a lot like photosphere or other similar apps
3. The upload and processing takes significant amount of time.  About 1-2 hours.
4. Once done, you can download the files for the model (*stl) 
5. You can make your model public and share with others.  You can tweet, Pin, etc.  You also get an embed code which for some reason did not work for this blog post.

Next steps:

Explore use of this tool for anatomy education!

Tips for navigation

1. Zoom in to the drummer - on touch pad you may have to use 2 finger slide, on mouse use scroll wheel
2. Pan to center the drummer - Shift + left click + Drag (slide on touch pad)
3. Rotate - Left Click + Drag (slide)

Google Photos - Machine Learning that is Insanely Good!

Google just released the new version of Google Photos for desktop, Android and iOS and after using it for just a few minutes I am completely blown away.

While it is many great features, the "search for photographs" is what took my breath away.  I started off searching for "Wedding", "Beach" etc and then moved on to specific landmarks like "Taj Mahal" and "Chichentiza" and it performed remarkably well.

Then I tried "cricket" and the results were stunning.
Here is a sample of what it found in my photo library:

1.  This was not a big deal - it had tons of clues that it was a cricket match

This was from a famous test match in England

2.  The next one was a screen capture from a smartphone of a scorecard from a cricket match

This had the word "Cricket" in the photo

 3.  This was when I started to really be amazed.  This was a screen capture I took of 3 women from Afghanistan celebrating a famous victory.  The only hint here was the score at the bottom.

Afghan women celebrating a famous victory

 4.  This one had few background clues to this being a cricket match.  It is possible since I had grabbed this from the web that Google had indexed it as being a game of cricket.

Cricket match in ice and snow.

5.  This one was totally amazing.  The FIFA trophy would make you think that Google would index this under soccer.  But the 2 people flanking the trophy are 2 famous cricket players.  Google recognized them and brought this up in the search for cricket.  

Tendulkar and Ganguly 

 6.  And lastly - this grainy shot of my TV showing a cricket match - all you can see is the helmet.

Cricket match on TV

Between the amazing experience with Skype translator and this one with Google Photos it seems that machine learning has reached beyond our wildest expectations.

Human Learning Needs in the Age of Machine Learning

Yesterday I experienced quite a coincidence that helped me crystallize my thoughts regarding machine learning; as I was scanning my Twitter and Google+ timelines and my Inoreader feeds each site had a post about machine learning. This post is about 2 common questions I get asked and how these posts helped me reflect on my responses to these questions.

Due to my work with the IBM Watson research team, I often get asked these 2 questions by other physicians:

•  The first question is if/when computers are going to make physicians redundant.  My response is that at present the vision is to create Artificial Intelligence systems that would help healthcare providers provide more efficient or better quality care and not to replace them.  Clearly, no one has a crystal ball and the expert opinions run the gamut from fear of AI to tremendous optimism.

From Newsweek

Peter Diamandis and Steven Kotler

• The second question is how to train our current generation of learners to prepare them for the future where they will work closely with artificial intelligence systems.  My response here is that students need to be part of building these systems in their disciplines.  Just like in high schools students take immersive experiences to learn foreign languages, our learners need to start doing electives in computer sciences and  data analytics departments or companies to leverage these technologies to solve problems in their disciplines.  Thus medical students should work with computer science students to use big data from wearable devices to improve health of a population for example.  This will not only help solve problems but they will learn first hand the limitations of these tools and recognize these in the future rather than just blindly relying on their recommendations.  

So what were the three posts?

1.  The Machine Vision Algorithm Beating Art Historians at Their Own Game

This is a post about a paper by researchers at Rutgers University who developed machine learning algorithms to help recognize styles and artistss of fine art paintings with a great deal of accuracy.  But the most important lesson was that when the algorithms failed to identify an artist correctly, there was a lesson to be learned.  There was a similarity in the paintings that was evidence of how the two artists (the correct one and the one wrongly identified by the algorithm) were similarly influenced.  Something that an art historian may not even have been aware of.

From: MIT Technology Review (Click image for web page)

2. Image Scaling Using Deep Convolutional Neural Networks

This amazing post describes in an (relatively speaking) easy to understand manner how a neural network was designed to process low resolution images to "fill in the missing pixels" to produce high-res images for Flipboard posts.  The post is a great one for our high school and college math students to see how concepts that they are learning have tremendous practical implications.

Courtesy Normal Tasfi via Flipboard

3.  a16z Podcast: Making Sense of Big Data, Machine Learning, and Deep Learning

This is a terrific 27 minute podcast the quotable quote being,

"Machine learning is to big data as human learning is to life experiences" 

It has a great story of how Larry Page talking with Google employees exhorts them to shorten the latency between entering a search term and getting the results.  When asked if what the final goal should be, whether it should be zero, he responds, "Why should we stop at zero?".  The goal should be that machines should be able to anticipate our needs not just respond to our requests.  Nguyen goes on to discuss why machine learning needs to be part of every app.

Sonal interviewing Christopher Nguyen CEO of Adatao

Given enough data, machine learning can identify patterns that humans cannot and will be able to predict problems before then happen.  Thus humans know that driving a car with poor brakes and wipers, very fast in rain on a curvy road often leads to disasters. 

We have an increasing torrent of data from medical literature, genomic analysis, electronic health records and wearable devices. When we start making this data available to appropriately programmed machines, patterns will emerge that may help predict or prevent heart attacks, strokes and cancers.  

This is what our learners need to get comfortable with so they know when to rely on these predictions and when to spot errors and learn from them.

Microsoft Strings Together an Amazing List of Innovations!

This has been an amazing year for Microsoft.  The list of hardware and software innovations that they have come out with is mind boggling.

1. Surface Pro 3 - probably the best single device I have owned - replaced my laptop and iPad and Android tablet in one fell swoop and added the functionality of the superb Stylus.
2. Office Mix - the easiest way to create content for flipped classrooms
3. HoloLens - the mixed reality headset that has huge potential in education
4. Surface Hub - Large "Smartboard" with video conferencing, OneNote and motion sensing built in.
5. Microsoft Band - for $200 a fitness tracker with ability to read notifications, tweets, text messages, email, calendar alerts, heart rate monitor, GPS etc.
6. Windows 10 with Microsoft Edge - a browser that lets you annotate the web
7. Skype Translator (in Preview) - instant translation between English, Spanish, Mandarin, Italian and other languages coming soon.

On top of this making all of Office apps available on both iOS and Android and also allowing developers to quickly convert their iOS and Android apps for Windows is a big shift in MS philosophy.

Competition is great for consumers and I am glad MS is back in the fray in a big way!

HoloLens for Anatomy Education

Office Mix Video

Surface Hub

Web Note feature of Microsoft Edge Browser

A Personal Learning Network becomes a Print Journal Issue: Why Academics Really use Twitter

Social Media allows a motivated and engaged learner to build connections that can enhance lifelong learning.  The connections become a learners Personal Learning Network or PLN.  The ability of social media to help a learner find and connect with the right people that might be otherwise impossible to "meet" in real life is one of its huge potential advantages.

This can be a difficult concept to convey to someone who may have a very negative attitude of Twitter.  One can hardly blame them for thinking that Twitter is a time waster, that there is a huge noise to signal ratio with very little tangible benefit.

A famous Nature study showed that very few academics use Twitter compared to sites like Google Scholar.  This led to a spoof by PhD Comics on "Why Academics Really use Twitter".  This is quite funny maybe because it has an element of truth for those who use Twitter.  At the same time infographics like this might unintentionally dissuade people from trying out Twitter as it may reinforce their beliefs about its lack of usefulness.

Now we have a great example of how a PLN created on Twitter led to an entire issue of a print journal.  The credit goes to Margaret Chisholm who was the editor of the special issue of "International Review of Psychiatry" and put together the issue with the help of a group of authors who mostly got to know each other first on Twitter and are part of a large PLN of health care social media users.

Granted, the special issue was regarding the use of Social Media but it could well have been any other topic in biomedical sciences where the scientists engage in social media.  This special issue of a print journal may be an excellent showpiece of the huge potential benefit of social media for academics - to create a PLN for lifelong learning.

Timelines to represent the history of medicine

"Those who do not study history are condemned to repeat it"

Understanding the history is critical to comprehending the current status of any political situation.  Thus one cannot even being to come to grips with the situation in the Middle East or in Nigeria without knowing how we got here.

The same holds true for medicine.  Using history helps teach our students about various complex  therapies like antibiotics, anti-lipid medications etc.

Thus whenever there is a situation what is difficult to grasp, studying the history of how we got here helps to understand it.  The fact that >90 years after the discovery of insulin by Banting and Bates this critical medication is still not available off patent is almost unbelievable.

An article in the NEJM highlights this by tracing the history of the various forms of insulin to clarify the current situation.

A timeline makes this easier to follow.  Making the timeline took less than 5 min on a free tool called Dipity.  It allows for addition of images or video and can be shared to encourage discussion.
Explore the timeline embedded below by clicking on blurbs or zooming in and out.

Insulin History on Dipity.

Getting students to work collaboratively to create timelines of major therapeutic advances in key areas of medicine can help them build a deeper understanding of the subject.  It can help them identify potential areas for research and quickly digest newer advances as they occur, by recognizing their place in history.

We know that we learn by doing, and thus, we should encourage students to create these timelines rather than just view timelines created by others.