The Rise of the Machines

Technology is improving at an exponential rate and becoming more ingrained in our lives. Few people can live without being connected to their phones. In one way it is good. I now can call for help or check the weather from almost anywhere. In other ways it bad, because besides being addicted to the connection, our privacy is being compromised as companies use the data to target advertising at us and to make us buy more stuff.

This past week I was at a conference in Vegas with 20,000 other like-minded geeks to discuss the latest technology trends and how to use this technology to improve our software to make it more cognitive. It was a good conference and I learned a lot. One of the main themes discussed was how to use artificial intelligence to pull meaningful information from the vast amount of data we all generate.  (By some estimates a person generates 1.7 MB of data per/min)

For those that remember, Watson was a computer system that won Jeopardy about 5 years ago. The main innovation of Watson was the ability to read natural speech and understand the main concepts behind it. This allowed it to answer complicated questions and learn from its mistakes so the more it read the smarter it got. Watson can tell the difference between Apple the company and apple the fruit based on the context of how it us used. This is a simple thing for us to do but very hard to do for software to do because of the way both process information.

The Watson on Jeopardy was a science project powered by hundreds of computers wired in parallel. Since then the software and technology has improved to the point that it is now has become a set of programming modules on the cloud. What that means is that anybody can wire up these modules and create some practical applications for only a few bucks.

At the conference I saw the Watson software being used to analyze the presidential candidates, help scientist analyze research papers, help support team reduce support calls, and much more. What started out as research project is now having real world impact and is going to bring in a new age of software that is going to make us even more dependent on them. I believe that in general that this will be beneficial for most of us. On the other hand there is a possibility that this will lead to Skynet  or Collossus so I’m making sure that all my software has a kill switch (just in case)

As part of the conference I did get a chance to see a presentation by the US Cycling Women’s Pursuit team.  The coach of the team was there, showing how IBM helped create an application to bring the data from the power, heart rate and muscle oxygenation sensors into a single view with in minutes after each training session. Normally compiling all this data use to take days. Now he is able to the view of the video of the training session along with the data and give immediate feedback. It was an interesting talked and I learned a lot about how power and heart rate sensors are used to improve training and performance overall. One of the most important thing the coach was able to get from all this data was W’ which is the amount of reserve energy a rider has. At the beginning of the race this will be 100% but as the rider pushes their power level above their max sustainable level this will go down. The idea is to be close to 0% by the end of the race but be careful use the reserve energy too early.

After the presentation I talked to the coach an asked him how much of this analysis would be useful for recreational riders like myself. He said that I would not want to go to the extreme that he does but that monitoring trends with heart rate and power could be useful. Power meters are still too expensive for the average recreational rider but as a result of this talk I may start collecting some data from my rides (heart rate, length, elevation gain, and a few other factors.) to see if I can use some of the tools I learned about at the conference to do some useful analysis. I know after doing a ride by myself today that I could use whatever help I can to get back to peak riding shape.