We Do Hard Things

Sure, we do hard things. But, why?

Our family has been blessed with pretty good brains, so almost all schoolwork (K-12) was pretty easy for each of us. As parents, we needed to find other tasks which created challenges and stresses for our kids. In short, hard things. We did not have a good name for it, we just wanted the kids to suffer a little.

Our granddaughter, age 7, is also very good at schoolwork. She has a good musical ear, so she likes to plink around on the piano. Her father took piano lessons for five years and played in competitions for several years.

Learning Starts Early

As you might guess, pretty soon our granddaughter was signed up for piano lessons, which is quite different from just plinking around. Playing the piano requires manual dexterity and strength, muscle memory, a good musical ear, the ability to read and memorize music. It’s hard for most people and piano teachers seem to be particularly strict. With private lessons, you cannot hide in the back row.

There is a secret to learning to play the piano, as told in this apocryphal story about the famous violinist and conductor Itzhak Perlman. A visitor to New York stopped Itzhak Perlman, asking for directions.

“How do you get to Carnagie Hall?” asked the visitor.

“Practice, practice, practice,”responded the famous violinist.

Shortly after his daughter began formal piano lessons, papa and daughter had a similar conversation.

“How is piano practice?” papa asked his daughter, after a particularly difficult session.

“It’s hard,” she complained.

“Yes. We do hard things,” explained papa in a flash of inspiration.

Learning Stays Late

A few years ago, while cleaning out some dusty old boxes, I came across my old notebooks on fuzzy logic and neural networks, taken from lectures by Carver Mead. A professor at Caltech for over 40 years, Carver Mead pioneered the development of neural nets and silicon VLSI technology.

I knew that the field of AI had advanced dramatically since the 1980s when I took those notes. My curiosity aroused, I wondered, “What are the machines thinking about?”

Eventually, I enrolled in the AI and Machine Learning track at Udacity, an online school. Often I got stuck and frustrated with the math, as my memories of calculus and statistics dated back to my college courses, about a million years ago. When I failed an exam online at Udacity, the screen occasionally offered words of encouragement:

Feeling stuck, frustrated, even irritated?

Great! Stay right there. That’s where the learning happens.

Given the amount of time I felt stuck, frustrated, and irritated, I must have learned a lot. Eventually, I passed the course and earned a nano degree in AI and Machine Learning. Now, I know what the machines are thinking about. And I learned that it is never too late to get stuck and frustrated.

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