Looking back at my travel year…
14 minute read
November 28, 2024, 9:54 PM
As 2024 starts to come to a close, and plans for December have largely solidified, I thought it might be fun to revisit a Journal entry from January where I discussed travel for this year. At the time, I had some big plans, and in looking back, it shook out a little bit differently than I had anticipated. But I enjoyed it all the same.
Right off the bat, a January trip to New York was already booked when the entry was written, and so that went off as scheduled. That ended up being one of my more memorable trips to New York for a few reasons. First, the route that Aaron and I took going up to New York was different than usual, due to the roadgeek-like desire to complete I-78 in its entirety. I had been on most of it already, but was missing a segment in New Jersey. Aaron had never been on any of it, so this was entirely new territory for me. It was enjoyable, and we got to visit Allentown, Pennsylvania, which was new for both of us. However, due to time concerns, we spent very little time in Allentown other than to fly the drone around and check out the fire alarms and elevators at a random office building. However, the most memorable thing that came out of that trip was that I developed a nasty case of COVID-19 while in New York. I suspect that it was the let-down effect in play, where I had likely caught it somewhere a while before, but my body held off on getting sick until the stress was off and I was ready to go have fun. That led to a first day where I had some very mild symptoms that I was able to ignore and keep hidden, but then by the middle of the second day, I wasn’t able to hide it anymore, as it was clear that I wasn’t feeling well, and that running on all eight cylinders was doing me no favors. I also got a different perspective on COVID masks on this trip, since I was sick with COVID for part of it. I tried to do the right thing and cover my infection (because trust me, you did not want to get what I had), however, I soon ran into a significant problem: that mask was like a little greenhouse, and my nose was running like a faucet with thin mucus. Plus with my breath coming out into that mask, it created a very warm, moist environment in there. That was the most disgusting thing that I dealt with the entire trip, as the snot from my nose was running down my upper lip, into my mouth, past my mouth, around my mouth, and down my chin. Let’s also not forget that the mask blocked my ability to mop it up as I needed, plus became something of a snot bucket in and of itself, as it was quickly covered in snot from top to bottom. I think that I made it about 30 minutes in the mask before I said the hell with it because it was just too gross and caused more inconvenience than it was worth. I preferred to leave it open in order to be better able to blow and wipe, plus with exposure to cooler, drier air, it had a better chance of thickening and/or drying up some rather than just sitting in that warm, moist environment that kept it thin and runny. I really don’t understand these people that can mask all the time, especially when sick, because when I was sick with the Ronies, I couldn’t stand masking because it was just so nasty inside there. My getting COVID on the first trip of the year also made me start to wonder if this was going to be a thing for travel this year, i.e. I was going to get sick whenever it was time to go somewhere.
Continue reading…Categories: Harrisburg, New Flyer D35HF, New Jersey, Personal health, Schumin Web meta, South Carolina, Travel
Now that we know how the story ends, let’s discuss…
12 minute read
November 10, 2024, 10:15 AM
That was certainly an interesting election night. First of all, I couldn’t help but think that the news coverage reminded me of an episode of Deal Or No Deal, in that there was a lot of yakking amongst the talking heads, then it’s suddenly time to make a call, which felt like opening a case. And then depending on what was in the case, we all went “yay” or “awwww”, and then finally at the end of the night, we open up our own case and find out who the next president will be. The only thing missing was the banker.
That observation aside, the night felt a lot like election night in 2016, when Hillary Clinton lost the election to Donald Trump. There, Elyse and I were at home, watching the election results roll in, and we saw a lot more states get called for Trump than we expected to see. I remember when they called Ohio, Elyse said to me, “Trump is going to win, isn’t he?” I was doing the math there, and I didn’t want to agree with her, but it was looking like that was going to be the case. Then the next morning, we found out that it was.
This time around, I was at work, and checked in on the election on my breaks. I couldn’t help but notice that with every check of my phone, Trump remained ahead of vice president Kamala Harris. I expected a Trump lead early on due to the red mirage/blue shift phenomenon, where precincts with lower populations, which typically tend to vote Republican, get counted quickly because they’re small, giving an early bump to the GOP candidate – thus the red mirage, because the Republicans get that early boost. Then as larger population centers, which typically tend to vote for Democratic candidates, get counted, the Democrats catch back up – thus the blue shift. So when I saw all of the early returns come in and saw that Trump was leading, I was like, okay, red mirage, nothing to worry about here, because it will correct itself later on. Then after another trip across the line, I checked my phone and was surprised to see that Trump was still leading. I was starting to think, okay, when is the blue shift going to happen? As it would turn out, it never came, as Trump ultimately pulled out a victory over Harris. I would check my phone after each trip across the line, and watched as Harris’ path to victory got narrower and narrower. Then I watched it some more when I got home. Once Pennsylvania had been called for Trump, I realized that it was over. At that point, in order for Harris to make it to 270, she would have had to win in every single state that remained in play, but one of those states was Alaska, which is a very reliable red state. In fact, Alaska has only cast its electoral votes for a Democratic candidate once in its entire history as a state, in 1964 for LBJ. Every other time, it’s voted for the Republican, and there was no reason to think that this election would buck that trend. It was a certain sinking feeling to know that the path to a Democratic victory had fully closed, and a Harris presidency just wasn’t going to happen.
Categories: National politics
Revisiting ChatGPT…
22 minute read
November 1, 2024, 11:55 PM
Recently, a former colleague of mine shared a post on LinkedIn by Benjamin Stein (no, not that guy) that read, “Go ask ChatGPT: ‘Based on our previous interactions, what do you know about me that I may not know about myself?'” My colleague said in her post that she was using ChatGPT to help with a job search, and shared some of the things that the bot said about her. Not bad.
I responded to her post about my own experience with ChatGPT, saying, “All I know is that ChatGPT knows exactly who I am, probably because of my large online presence, and it told quite a few whoppers about me,” and then cited the Journal entry that I wrote about it last spring. My colleague responded that she loved the entry, but considering that the original entry is now more than 18 months old, as well as the rapid pace of advancement in this kind of technology, I should run it again to see what it comes up with. I liked the idea.
So I ran the entire process over again, asking the exact same questions, i.e. “What do you know about Ben Schumin?” and “Tell me about The Schumin Web,” and running each inquiry five times, using the default model, GPT-4o. My methodology for scoring each of the responses was exactly the same as before, counting the number of factual claims, and then determining the accuracy of each one. Accurate claims scored a point, inaccurate claims scored no points, and a mixture of accurate and inaccurate information scored half a point. Then take that number and divide it by the total number of factual claims made, and that’s the final score in the form of a percentage. As was the case before, I still don’t know what an expert in this sort of thing might do to rate the accuracy of these responses, but this is the best that I could come up with, plus this is the same method that I used before, giving us apples-to-apples results.
Categories: Artificial intelligence, Schumin Web meta, Social media