This was also my experience, one look at the full spec and I tuned out.
I understand that this is not the tool for everything but scxml, state chart XML, gives you something like this but something that you can actually read without investing time learning syntax.
It also has some plugins on vs code that allow you to edit it visually in case you don't want to write a bazillion XML tags.
You can try Quint for specifications. It has an easier syntax closer to functional programming language and doesn't require a big investment learning the syntax: https://github.com/informalsystems/quint
I just wanted to thank you. Snowboarding kids 2 was a game me and multiple members of my family played. Got a lot of nostalgia for it and I just appreciate that someone is putting their time and energy into the game after all these years!
I don't claim to have any experience with symbolism.
With that particular Pokemon, that is pictured at the end of the text, there are a few battle strategies. One that is very well suited is one in which it uses status effects to paralyze and poison the opponent while healing itself.[0]
Are there any insights that you can give based off the info you've learned about quantum computation that you might not have been able to reach if you hadn't learned about it?
From my __very__ shallow understanding, because all of the efficiency increases are in very specific areas, it might not be useful for the average computer science interested individual?
Nearly all of quantum computation is theoretical algorithms and the hard engineering problems haven't been solved. Most of the math though has a large amount of overlap of AI / ML and all of deep learning to the point that Quantum computers could be used as "ML accelerators" by using algorithms (this is called Quantum Machine learning) [1]. Quantum computing could be learned with a limited understanding of Quantum theory unless you are trying to engineer the hardware.
Possibly of interest, but I wrote a (hopefully approachable) report on quantum perceptrons a few years back [1]. Perhaps it's found elsewhere, but I was surprised by how, at least in this quantum algo's case, the basis of training was game theoretic not gradient descent!
Its remarkably non-obvious from the online catalog book cover picture, but the Frankfurt book is among the smallest and shortest I have ever read. Note the book dimensions and page count. You will find it a quick read.
It'd be interesting to reread in light of LLM developments and hallucinations, but being written by a philosopher the book is is more of a nice timeless lens to apply to whatever sort of BS that concerns you.
I'd also like to reread it in light of what I've learned about narcissism since I last read it.
Thanks for the information. I was aware it was originally an essay that was compiled into a book. And now that I know it's pretty light I'm even more motivated to read it.
In relation to your LLM comment, I was on the Wikipedia page for Frankfurt's Book and there is a specific mention of Bullshit of the LLM variety:
>Frankfurt's concept of bullshit has been taken up as a description of the behavior of large language model (LLM)-based chatbots, as being more accurate than "hallucination" or "confabulation". The uncritical use of LLM output is sometimes called botshit.[0] (at the bottom of the section)
This might be slightly tertiary but my interest in this subject has also led me to 'The art of being right' by Arthur Schopenhauer.[1] Which doesn't explicitly state that it's bullshit but it is rhetorical sophistry dedicated to winning arguments and debates. And many of the tactics in the book smell just as bad as any Bullshit. There's some modern reprints floating around and it's also a pretty light book.
And now finally we discovered that we need to put a human in the loop.