On this blessed day we are all a girl.
On this blessed day we are all a girl.
Just stagger the classes not just by size and/or weight but also by motor type. For instance, a tax class for ultracompact cars could look like this:
(I basically went with Japan’s current definition of kei cars and replaced the displacement restriction with a weight restriction.)
Remember that each woman has a different experience. Some women have such a light period that they only notice it because they find spots in their underwear. On the other hand, a woman with endometriosis will probably start being in excruciating pain the day before the period starts and will know exactly how long it lasts.
Source: I know someone with endo. She also has a resistance to at least one OTC painkiller because she used to pop those things like candy. And a female coworker of hers (with a very light period) thinks that most women are exaggerating and that periods aren’t much of a problem…
Usually, when people talk about bees dying, they mean wild bees. Unlike honey bees they aren’t cultivated by us. They also tend to be better pollinators than honey bees, adapted to local plants that honey bees can’t handle well.
And the name of that hamster? Pikachu.
Why do you go for a MIRV if your warhead doesn’t even leave the atmosphere?
Seconded. As far as pens are concerned, Uniball is where it’s at.
I find that LLMs also tend to create very placative, kitschy content. Nuance is beyond them.
Back then Clippit was also memetically annoying. Perception of how him has actually improved over time thanks to nostalgia.
Welp, there goes the neighborhood. If they want to do an IPO they’ll probably enshittify the hell out of the platform and jettison all remotely raunchy communities. Because nothing says “good investment” than a service that just drove out a fair chunk of its user base.
That undersells them slightly.
LLMs are powerful tools for generating text that looks like something. Need something rephrased in a different style? They’re good at that. Need something summarized? They can do that, too. Need a question answered? No can do.
LLMs can’t generate answers to questions. They can only generate text that looks like answers to questions. Often enough that answer is even correct, though usually suboptimal. But they’ll also happily generate complete bullshit answers and to them there’s no difference to a real answer.
They’re text transformers marketed as general problem solvers because a) the market for text transformers isn’t that big and b) general problem solvers is what AI researchers are always trying to create. They have their use cases but certainly not ones worth the kind of spending they get.
The prep and recovery blocks are also team calls; everyone prepares and recovers together, moderated by the scrum master.
Because giving answers is not a LLM’s job. A LLM’s job is to generate text that looks like an answer. And we then try to coax framework that into generating correct answers as often as possible, with mixed results.
I remember talking to someone about where LLMs are and aren’t useful. I pointed out that LLMs would be absolutely worthless for me as my work mostly consists of interacting with company-internal APIs, which the LLM obviously hasn’t been trained on.
The other person insisted that that is exactly what LLMs are great at. They wouldn’t explain how exactly the LLM was supposed to know how my company’s internal software, which is a trade secret, is structured.
But hey, I figured I’d give it a go. So I fired up a local Llama 3.1 instance and asked it how to set up a local copy of ASDIS, one such internal system (name and details changed to protect the innocent). And Llama did give me instructions… on how to write the American States Data Information System, a Python frontend for a single MySQL table containing basic information about the member states of the USA.
Oddly enough, that’s not what my company’s ASDIS is. It’s almost as if the LLM had no idea what I was talking about. Words fail to express my surprise at this turn of events.
That’s why I’ll make damn sure they’ll make that second branch first.
Mind you, the most likely result is that I’ll still see branches with 50+ commits with meaningless names because nobody ever rebases anything.
I’m kinda planning on teaching my team how to use interactive rebases to clean the history before a merge request.
The first thing they’ll learn is to make a temporary second branch so they can just toss their borked one if they screw up. I’m not going to deal with their git issues for them.
It depends on how busy the day is, I guess. Today I arrived 5 minutes early and waited for less than a minute. But my GP is pretty good at scheduling anyway; I don’t think I’ve ever waited for more than 15 minutes.
Looks like Yotsuba with a skull for a head. Perhaps some 4chan thing?