Saturday evening, my wife and I were in our usual position – rocking chairs on the porch overlooking our neighbor’s hayfield and watching the lengthening shadows. Although we are nominally reading, we mostly look out at the waves across the hay. I happened to look up and saw a large bird high up in the air. It wasn’t flying like a vulture (which is a pretty common occurrence here). Then, I saw the white head and tail feathers – it was a bald eagle. We stood up and watched as it soared higher and higher until it flew west over Short Hill Mountain. It was only visible for about 30 seconds and if I hadn’t seen it in the 15 seconds it was visible from our chairs on the porch, we would have missed it.
We were in the right place at the right time.
We have had other bald eagles fly by – maybe twice a year. One time a couple of years ago, as I was walking back to the house, one flew over so low that I could hear the “swish” of its wings. It was only visible for about 10 seconds. Once again, the right place at the right time.
This is often the case with wildlife sightings around here. Except for the deer and groundhogs, most animals pass through pretty quickly. From our kitchen table, we have seen wild turkeys, weasels, foxes, and many non-native birds go by. Again, we had to be in the right place at the right time to see them.
The sighting yesterday struck me because I had just been thinking about how my career had been a case of being “at the right place at the right time.” That morning, I had gone to a monthly Linux meeting where the topic was “Artificial Intelligence and Machine Learning – AI/ML.” The presenter worked for Red Hat – a large software company which among other things has a lot of support for those who are migrating large projects to “The Cloud” (i.e., someone else’s big computer located somewhere else). She gave a good overview of the various types of AI/ML algorithms and what various Red Hat customers were doing with them, but it was clear that her feet had “never touched the ground.”
The final slide was all of the ways that Red Hat could support someone developing this type of application. The chart was like a multi-layer cake with maybe six levels of abstraction and each layer had maybe four or five sets of libraries. It was clear that with this sort of environment, it would be “Libraries all the way down.” No wonder she wasn’t real clear on the actual implementation details. After the presentation, someone asked if he could play with the techniques on his laptop or if he had to go onto “The Cloud.” The consensus was that the Cloud was necessary.
I am retired now, but most of my career has been in Embedded Systems. That is where there is a computer chip involved, but it doesn’t look like a computer. (did you know that there is a computer inside the removable LIon battery in your laptop? That was what I did in my last job).
When I started working, Embedded Systems didn’t exist as a “thing” and I was there at the start. I happened to start working at a smallish company which did mostly military signal processing and pattern recognition systems. Over the next 11 years, I worked on a large variety of projects from Radar signal processing ( to identify the type of plane targeted), sonar signal processing, translation of hand-sent Morse code – including the identity of the sender from his ‘Fist’ used in sending the code. We also developed one of the first speech recognition systems and I was responsible for developing an Operating System that allowed 4 simultaneous speakers to speak and be recognized,* potentially translated and output in a desired format which could be text or a speech synthesizer. There were several other classified projects, but I would have to kill you if I told you about them.
Now all of this was done on the minicomputers at the time with 32-64k bytes of memory, no real mass storage, and slow processors. That is, each was done on systems with much less capability than a modern laptop.
On each project, I had the overall responsibility for the data analysis, algorithm design, and coding/testing. If there was a problem, it was in something I had done and it was my responsibility to find it. I loved it.
The company was small enough that my contributions were recognized and I went through 11 title changes and promotions in 11 years. Again, the right place at the right time.
These days, programmers are doing much more with systems which are orders of magnitude more powerful than back then, but they seem to do them as parts of large teams – often distributed over several locations. And they are depending on libraries which have been developed by other large teams. In such large teams, it is very difficult for an individual contributor to get noticed.
I am not sure if I would thrive in the current environment and really do feel that I was in “The right place at the right time.”
I am not sure about other professions, but I have a feeling that medicine has hit the same sort of transition. We live near a small town where our Doctor had an office. It was basically him and a couple of nurses. When I went to see him, he spent a lot of time with me and was willing to answer all my questions. He retired not long after his practice was acquired by a large multi-office multi-state company. He started spending more time typing into a computer than actually examining me. Now when we call the ‘office’, the phone is answered at a switchboard in a city about 30 miles away and everything is even more computerized. I think the ‘sweet spot’ for medicine as a career – at least for a GP – is over.
What about you? Did you hit the “sweet spot” in your career? If not, what happened?
*Early speech systems like this required a limited vocabulary, trained to the speaker and with separation between words. Things have gotten much better in the last 50 years.Published in