OPERATING : A CW (and life?) Lesson Learned

OPERATING : A CW (and life?) Lesson Learned

Last night, I worked Jack, W4TJE. He’s a great operator, and I always enjoy chatting with him. Later that evening, I got the following email:

Dan,

You mention on your QRZ.Com page how working Field Day in 2002 got you back into amateur radio. I have a similar story here. I’ve always been active, but was never much of a CW op. I just didn’t get it, never saw the attraction. But, at a Field Day around that same time, I watched an old WWII era ham, now SK, working CW at what sounded like machine gun speed, all while sipping coffee and with a cigarette dangling off his lips, and cracking jokes with us while he did it......

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OPERATING : Worked All Plymouth, AF3K/AF4K, DLM Antenna

OPERATING : Worked All Plymouth, AF3K/AF4K, DLM Antenna

About a week ago, Tom, KE8HUM, answered my CQ. He lives in Plymouth, MI, only 12 miles from me, according to QRZ.Com. He apologized, but I enjoy working guys no matter where they are. He’s a member of our club, a nice guy, and I have his QSL in my collection of QSL cards from stations whose call signs spell words.

About an hour and a half later, I was still down in the shack and worked Gary, K1YAN, Plymouth, MA. I joked with Gary that I was going for the “Worked All Plymouth” award, but, as it turns out, I have a long way to go. According to the Boston Globe, there are 30 cities in the U.S. alone with the name Plymouth.

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OPINION : Can the Jetson Nano Bring AI to Amateur Radio?

OPINION : Can the Jetson Nano Bring AI to Amateur Radio?

Arduinos are fun, and Raspberry Pis are cool, and hams have been quick to adopt these platforms and use them in amateur radio applications. The latest small computer—the NVIDA Jetson Nano—could take this to a whole new level.

The Nano is the newest and the smallest of the NVIDIA Jetson Series of machine learning (ML) enabled computer boards (shown below). It come is a DIMM package measuring only 70 x 45 mm. Despite the small size, the specs are very impressive:

  • 64-bit, quad-core ARM Cortex-A57 CPU complex

  • 128-CUDA-core Maxwell GPGPU designed to handle video streams as well as ML chores

  • 472 GFLOPS of performance.

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