Tuesday, October 17, 2017

Seagull Century 2017 With Jeff and Gork

This ended up being a great Seagull Century, but we thought it was going to be a rain filled day until the night before.  It was 60% chance of rain when we went out to dinner and while we were having a few drinks, it dropped to partly cloudy with a 20% chance of rain.  The ride had the least wind that I can remember. 

Jeff, Gork and I did the 100 miles again this year.  We were joined by Gork's wife Connie and my wife Julie in Ocean City.  It was also Corvettes at the Beach, so it was a double win for me!   We all stayed at a 3 bedroom, two level condo at Sea Watch. 

What is really nice about doing a ride like the Seagull Century is that it is a great chance to get together with friends who you have known since the mid 1970s.  From a health standpoint, what is important about a 100 mile bike ride is that when you are in late 50s, like the three of us, you simply cannot show up and ride 100 miles.  You need to put in about 2,000 miles during the earlier part of the year in order to be in shape to do it.  This means that every time sitting on the couch passes through your mind, you get off your butt and go for a long bike ride.

We averaged between 15 and 19 during the first 85 miles.  My cyclemeter app somehow reset when it was in my jersey pocket at the 85 mile mark, so that is why you see two different maps below.  What was very nice this year was the new southern route that was the most picturesque Seagull Century that I have been on since 1998.  Jeff has been doing it since 1999 and he said the same think.  This is Gork's 4th Seagull and he thought the route was the best as well.

This was the best cycling times that I have ever had and I owed it to weighing 192 pounds (first time below 205 pounds in 19 years of riding the Seagull), much better diet and putting in more miles than I ever had in preparation for the 2017 Seagull Century.

Here is the link for the specifics on our riding during the first 85 miles.

Here is the link for the specifics on our riding during the second 17 miles. 

Below are some photos from our ride and that weekend.  I am bummed and feel like an idiot that I did not get photos of the five of us out to dinner.  We had very nice meals at Liquid Assets and Hooked in Ocean City.

Above is Gork, Jeff and me at the 2nd rest stop.  They have rest stops with food and drink every 20 miles.

Here we are at the finish line with our bikes and looking forward to having a beer before we head back to Ocean City to have dinner (first a shower :-) with Connie and Julie.

Above is what you gets you through the 100 miles when it can be raining or windy -- a nice cold beer at the end! :-)

Above is the view from our condo with a very nice sunset on Sunday night.  Gork, Connie and Jeff had to get going Sunday morning.  Julie and I stayed through Monday.

On Sunday, Julie and I went to our "goto" lunch place which is the Crabcake Factory at 120th Street on ocean side.

Above is my Seagull Century wall in my garage where I put my Seagull Century Numbers.

The Seagull Century in 2018 will be the 30th anniversary and will be on Saturday the 6th of October.  Should be a lot of fun next year!

Hopefully, the three of us can keep doing this Seagull for many years to come!

Friday, October 6, 2017

Photon - A Great Dog

Today is a very, very sad week for the Edstrom family.  Our 13 1/2 year old yellow lab, Photon, died on Wednesday.

We decided to get Photon in 2004 on a trip back to Minnesota.  We were driving in our van in the pouring rain when a big four door pickup looses control slides off the road and then slides back in front of us, luckily I missed hitting him.   After that incident I said we are getting a puppy and I am going to name it Photon.  We had two dogs at that time Spike and Toot.  Spike was our first dog in 1998 - a combination of a yellow lab and a golden retriever and Toot who was loaned to us from the breeder to help calm Spike down.

We got Photon in the summer of 2004 and he was the perfect dog.  Photon was an absolute sweetheart of a dog who looked like a white polar bear.  The most gentle dog I have ever witnessed, except for if another dog picked on Nero, our much younger black lab.  That happened twice that I can remember.  Photon absolutely loved to go for walks, even when the arthritis in his legs would barely keep his rear legs going.  He also loved following either Spike or Nero around our 1/2 acre lot going counter-clockwise around the fence as if they were in patrol mode.

I am really glad we had dogs for our three sons as I definitely believe it helps in the maturity of kids when they have to take care of pets.  The countless hours of pleasure that John, Michael, Tim, Julie and I got from Photon was simply priceless.  This past year I was in semi-retirement, so I got to spend much more time with Photon and go with Julie on walks with Photon and Nero.  You could just see how Photon’s spirit would lift when he would see us grabbing the leash.

Even though you know the day is coming, it is still one of the most heart-breaking things a person can do when you make the family decision that your beloved dog’s quality of life is not where you or your dog want it to be.  We were fortunate because Photon gave us a two week warning.  He completely collapsed two weeks ago with no movement whatsoever.  The next morning he was slowly moving again, much to the surprise of our vet.  Tons of tests revealed nothing that would explain the collapse.  We treated each day after that as it could be his last.  This past Wednesday he collapsed and then later passed away at home when I was on the phone with Michael.  It was like Photon knew this was a tough decision for us to make and he decided to go on his own terms - at home.

Here are some pictures of Photon over the years.  God bless Photon you were the perfect dog and now you’re with Spike…. 
 Photon was the cutest puppy.  Looked like a little polar bear.
Above is Photon and Spike pulling on Photons toy after Spike had an operation.

We tried to introduce Photon to our rabbit Bugs.  Bugs was not that thrilled with the introduction :-)

 Above is Spike with Photon on his right.   Photon loved Spike.
Below is Toot on the left, Photon in the middle and Spike on the right.  Toot was loaned to us by the breeder to try calm Spike down when he was a puppy.  Spike literally ate our grill, our couch and a chair.  He was the alpha's alpha dog :-)

Above is Photon, Nero (our black lab) and Spike on the right.
Below is something all three liked to do - lie at the front door.  Photon is near the door, Toot is in the middle and Spike is on the left.

Wherever Spike was, Photon wanted to be right next to him.  When Spike passed away, it was really hard on Photon, but luckily Photon had Nero.  Now Nero is alone as he will be our last dog.  Julie and I are getting too old for raising puppies.

 Above is Photon and Nero when Nero was much younger.

Above was taken in the past week.  Photon and Nero become good buddies.  Photon used to follow Spike around the yard and then he would follow Nero. 

Above is Michael with Photon when Photon was still growing.  Photon was really Michael's dog.

Above is John with Photon when he was a puppy.

Above is Tim with Photon.

Above is Julie taking Photon for one of his last walks.   God bless Photon you were the perfect dog and now you’re with Spike….

Tuesday, October 3, 2017

The Small Functions Debate In Computer Science

This blog post titled, Small Functions considered Harmful, by  Cindy Sridharan  addresses one of canonical principles in modern computer science - small functions.  As she points out below:

"The idea is simple — a function should only ever do one thing and do it well. On the face of it, this sounds like an extremely sound idea, in tune, even, with the Unix philosophy.

The bit where this gets murky is when this “one thing” needs to be defined. The “one thing” can be anything from a simple return statement to a conditional expression to a piece of mathematical computation to a network call. As it so happens, many a time this “one thing” means a single level abstraction of some (often business) logic."

This is a long blog post, but it is well written and for anyone who has written code, it challenges some of the principles.

Monday, October 2, 2017

Machine Learning and Security

This article helps dispel the "magic" of machine learning that is being hyped so much today.

There is an excellent article by in SD Times  really brings out the challenges with machine learning and is titled: 

Black Hat USA 2017: Machine learning is not a silver bullet for security

This article is well worth reading and Hyrum Anderson clearly states the challenges below:

"Hyrum Anderson, technical director of data science for cybersecurity provider Endgame, presented research on machine learning malware evasion at this week’s Black Hat USA 2017 conference in Las Vegas. 
“I want you to know I am an advocate of machine learning for its ability to detect things that have never been seen,” Anderson said. “[But] machine learning has blind spots and depending on what an attacker knows about your machine learning model, they can be really easy to exploit.”

Anderson explained, machine learning is not only just susceptible to evasion attacks, but it is susceptible to these attacks by other machine learning methods. Researchers at Endgame have learned it is not only enough to provide a cybersecurity system, they have to check and double check the product as well as test and think about how adversaries might exploit or evade them. “If an attacker has access to your machine learning model, he can actually ask it ‘What can I do to confuse you the most,’ and the model will tell them.”"

What is very interesting is what Engame is doing with open source and machine learning malware detector:

"As part of his research, Anderson is releasing a machine learning malware detector into open source as well as the framework users can use to improve the AI agent, improve the malware, or attack their own models to learn about their weaknesses. “The framework that we’re providing can be readily adapted to attack your own machine learning model. To be clear, there are easier ways to attack your machine learning model since you know everything about it. But this framework represents what we believe to be the most realistic attack that an adversary can launch and that can be used to understand your model’s blind spots,” he said.  "