> Scholars believe that the Novgorod Republic had an unusually high level of literacy for the time, with literacy apparently widespread throughout different classes and among both sexes.
Yes, you are totally correct, but I believe this term is omitted from the cross-entropy loss function that is used in machine learning? Because it is a constant which does not contribute to the optimization.
To bring things full circle: the cross-entropy loss is the KL divergence. So intuitively, when you're minimizing cross-entropy loss, you're trying to minimize the "divergence" between the true distribution and your model distribution.
This intuition really helped me understand CE loss.
I go to the office almost everyday by choice. Free food, snacks, and coffee, gym, and medical clinics on campus. And it's just nice to get dressed and leave the house.
But it's really nice to have the flexibility to WFH when I need to, especially just mornings to skip traffic.
I grew up in Canada, but my family and I are first generation immigrants from Ukraine. The privilege of my peers left a huge, almost traumatizing, impression on me. My parents were constantly working overtime at their minimum wage jobs at a plastics plant to support us, while my brother and I were raised by my grandmother. Most of my peers had wealthy parents and it was hard to relate. The silver lining is that it really motivated me to work hard and escape that. I live in California now and make many times more than my parents ever made in their lives. My mom still works as a janitor for minimum wage.
Most people I know back in Canada get lots of support from their parents. Everyone I know who bought real estate had huge help from their parents. Canada is just too expensive otherwise and local jobs don't support the cost of living. It definitely feels unfair to those that don't have wealthy parents. They fall behind, and as housing prices rise, it becomes harder to catch up. Those definitely won demographic lottery, and I don't think many of them understand how lucky they are.
All that being said, given a global perspective, I am very lucky, too.
I slaughtered about 40 chickens once. I was probably around 19 at the time. My ex-girlfriend's dad just told me to get in the truck, asked his kids to stay at home, and took me to a chicken coop where him and his friend were raising chickens. I took them out of the coop, a few at a time, hung them upside down, and then killed them with a knife. After the first few, the rest in the coop began panicking even though they couldn't see what was going on. That really stood out to me. I'm sure they could hear or smell death. They knew what was coming.
One of my favourite economic paradoxes. It changes the way you think about efficiency and consumption.
My colleague introduced me to this idea. He had been studying ways to increase computing efficiency out of concern for the environment. Making programs more efficient would reduce energy consumption, right?
His advisor introduced him to Jevons paradox and he realized such efforts could have the exact opposite effect. So he dropped that research entirely. If you're worried about energy consumption, you need to make energy production more green, not machines more efficient.
Making data centers more efficient will probably cause us to build more data centers and use more power overall, not less.