Curious_Canid

That kind of seems like a win-win to me.

I’m 65 and I hate the generation labels. I genuinely think they were originally pushed as another propaganda mechanism to create further artificial divisions between people. There is no doubt that people of significantly different ages are often different in various ways, but the over simplicity of the named generations just provides another convenient way to stereotype people instead of understanding them as individuals.

I think I joined reddit in 2008. I’ve been involved in social media since the days of dial-up bulletin board systems in the late 70’s. (And I ran one of my own in the mid-80’s.) I had an email address on Bitnet in 1983 and was on Usenet in its early days. reddit was an interesting and open place for a while there and I enjoyed the variety, but most of it was becoming too cynical and tribal for me by the early 20’s. I discovered Lemmy a couple years before reddit’s API debacle, but that is what convinced me to drop reddit and focus on the Fediverse.

I like the decentralized model of the Fediverse. I think the idea that different servers can have different rules is healthy. I stay away from parts of it, but I have found plenty of communities that are friendly and interesting to me. After hanging out on several different servers, I joined Fedican and have been happy here. It’s a nice place to call my home online.

This is why we could, and should, replace most CEOs with AI. If someone is going to make bad decisions, we could at least avoid paying them hundreds of millions of dollars to do it.

1. I read a lot, mostly fantasy, science fiction, and mysteries, plus some non-fiction.
2. I play and run non-computer roleplaying games. I started in 1976 and have been at it ever since.
3. I have recently taken up playing the recorder, mostly tenor. My wife and a friend play with me.

I think the key to this is how you really feel about it. If you are genuinely happy with the arrangement, and aware you will eventually need to move on, that can be okay. If you start to feel any self-esteem issue, like you’re being taken advantage of, it’s time to get out and find something better. Always respect yourself.

I used to think it was a lack of self-awareness, but it has become clear that they simply don’t care if they are known to be inconsistent, dishonest, and cruel. There have yet to be any negative consequences for it. Their base doesn’t seem to care about anything but “winning”. The definition of “winning” changes from day-to-day, but that’s okay because very little of this is about issues. It is simply about the competition itself.

How is she ever going to learn chemistry if you keep shutting down her experiments?

My random Border Collie thanks you.

I write software for a living and I have worked directly with LLM backend code. You aren’t wrong about the exceptions, but I think they actually reinforce my main point. If you play with the parameters you can make all kinds of things happen, but all of those things are still driven by the existing information it already has or can find. It can mash things together in random new ways, but it will always work with components that already exist. There is no awareness of context or meaning that would allow it to make intelligent choices about what it mashes together. That will always be driven by the patterns it already knows, positively or negatively.

It’s like doing chemistry by picking random bottles from the shelf and dumping them into a beaker to see what happens. You could make an amazing discovery that way, but the chances of it happening are very, very low. And even if it does happen, there’s an excellent chance that you won’t recognize it.

I’m in favor of using LLMs for tasks that involve large-scale data analysis. They can be quite helpful, as long as the user understands their limitations and performs due diligence to validate the results.

Unfortunately what we are mostly seeing are cases where LLMs are used to generate boilerplate text or code that is assembled from a vast collection of material that someone who actually knew what they were doing had previously created. That kind of reuse is not inherently bad, but it should not be confused with what competent writers or coders do. And if LLMs really do take over a lot of routine daily tasks from people, the pool of approaches to those tasks will stagnate, and eventually degenerate, as LLMs become the primary sources of each others’ solutions.

LLMs may very well change the world, but not it in the ways most people expect. Companies that have invested heavily in them are pushing them as the solutions to the wrong problems.

LLMs are not capable of creating anything, including code. They are enormous word-matching search engines that try to find and piece together the closest existing examples of what is being requested. If what you’re looking for is reasonably common, that may be useful. If what you’re looking for is obscure, you may get things that don’t apply. And the LLM cannot tell the difference. They can be useful but, unlike an LLM, you need to understand the context to use them safely.

I think the most interesting thing about LLMs is actually what they tell us about the repetitive nature of most of what we do.

Fall is probably my favorite season, followed closely by winter. I do use full-spectrum lights to compensate for the shorter days, but overall I think my mood is better during that time. Winter in a forest is one of the most beautiful things in the world.

I stand with Alaric! Where can I buy a campaign button?