Readit NewsI mean, a tty is just a file descriptor... there have been script(1), expect(1) and chat(8) since the 80ies. tmux is not really necessary.
I used it in a previous job to automate configuring thousands of network devices
So, having some experience with the project and how different x and wayland are, when I saw this commenter had brought up the idea of making the switch from x to wayland a patch, it made me laugh out loud. The idea of leaning even further into the borderline degenerate amount of patching already done with suckless software to the point where you're practically rewriting the majority of it was very funny, and so I was confused about the downvotes.
Most dynamics of the physical world are sparse, non-linear systems at every level of resolution. Most ways of constructing accurate models mathematically don’t actually work. LLMs, for better or worse, are pretty classic (in an algorithmic information theory sense) sequential induction problems. We’ve known for well over a decade that you cannot cram real-world spatial dynamics into those models. It is a clear impedance mismatch.
There are a bunch of fundamental computer science problems that stand in the way, which I was schooled on in 2006 from the brightest minds in the field. For example, how do you represent arbitrary spatial relationships on computers in a general and scalable way? There are no solutions in the public data structures and algorithms literature. We know that universal solutions can’t exist and that all practical solutions require exotic high-dimensionality computational constructs that human brains will struggle to reason about. This has been the status quo since the 1980s. This particular set of problems is hard for a reason.
I vigorously agree that the ability to reason about spatiotemporal dynamics is critical to general AI. But the computer science required is so different from classical AI research that I don’t expect any pure AI researcher to bridge that gap. The other aspect is that this area of research became highly developed over two decades but is not in the public literature.
One of the big questions I have had since they announced the company, is who on their team is an expert in the dark state-of-the-art computer science with respect to working around these particular problems? They risk running straight into the same deep, layered theory walls that almost everyone else has run into. I can’t identify anyone on the team that is an expert in a relevant area of computer science theory, which makes me skeptical to some extent. It is a nice idea but I don’t get the sense they understand the true nature of the problem.
Nonetheless, I agree that it is important!
Simplified 2021 example before 174:
100k Revenue
100k Software Dev Costs
No profit or tax
100k Revenue
100k Software Dev Costs
90k "profit"
18.9k taxes
Accountants: If I am wrong about the above, please correct me
long_fn() {
echo "$1"
sleep "$2"
}
to 1s long_fn "This has spaces in it" 5 #!/usr/bin/env bash
long_fn () { # this can contain anything, like OPs until curl loop
sleep $1
}
# to TIMEOUT_DURATION BASH_FN_NAME BASH_FN_ARGS...
to () {
local duration="$1"; shift
local fn_name="$1"; shift
export -f "$fn_name"
timeout "$duration" bash -c "$fn_name"' "$@"' _ $@
}
time to 1s long_fn 5 # will report it ran 1 secondNonetheless, yes we do know certain brain structures like your image net analogy but the way you describe it, sounds a little bit of.
Our virtual cortex is not 'just a layer' its a component i would say and its optimized of detecting things.
Other components act differently with different structures.
Where does one — who has no knowledge of these prerequisites or about LISP (except that the latter has been heard in programming circles as something esoteric, extremely powerful, etc.) — start, before reading this book?
https://www.cs.cmu.edu/~dst/LispBook/book.pdf