My Java, .NET, Go, JavaScript/Typescript code running on serverless deployments, or low code/no code agentic tools, don't care what OS is powering the underlying type 1 hypervisor running their containers.
He's talking about philosophies in the article, one of which is that "text is the universal interface". LLMs are embracing this, as Unix did decades before.
That famous phylosophy only exists on a book that gets idolatred by some.
Go check the man pages of any commercial UNIX to see how many of the commands actually abid by such famous phylosophy that gets passed around, of each command doing a single thing well.
It is a endless list of options, and multiple capabilities for each of them.
> In that sense, LLMs are embodying the Unix philosophy. Of course, this analogy has holes so big you can easily ride a horse through. LLMs are neither small nor do they do one thing—you could even argue that some of the things they do, they certainly do not do well.
The biggest slow down on MacOS compared to Linux is the default filesystem APFS (but hey HFS and HFS+ were also slow). But not just that, the Linux dirent cache is optimised to within an inch of its life (it's deliberately sized to match CPU cachelines among other optimisations). And one of the chunks of that slow down is upper / lower case checks (Mac filesystems be default treat upper and lower case as the same thing when it comes to matching a filename).
Because of that Linux works so much faster with small files, and text files are small compared to audio, video, etc.
People love to say the Unix philosophy is "Write programs that do one thing and do it well". But this does not really seem to me to really match Unix practice. And it doesn't match LLMs either, as the article notes.
(So what is this article talking about? I guess it's talking mainly about "Write programs to handle text streams, because that is a universal interface".)
- parse command line arguments in a slightly different way from other tools
- parse some ad hoc input format specific to itself
- do one or more actual jobs
- produce output in its own ad hoc format
- produces a termination status; here there can be variations: tools written "void main" that return a nondeterministic status; tools that use multiple nonzero codes for multiple interesting non-success conditions.
This messy way of doing things has "won" in AI ecosystems, I suppose.
pjmlp | a day ago
RAM-bunctious | a day ago
pjmlp | a day ago
Go check the man pages of any commercial UNIX to see how many of the commands actually abid by such famous phylosophy that gets passed around, of each command doing a single thing well.
It is a endless list of options, and multiple capabilities for each of them.
vessenes | a day ago
But yes. That’s true.
datakan | a day ago
So the title is just clickbait
rambojohnson | a day ago
jt2190 | a day ago
meatmanek | a day ago
jt2190 | 10 hours ago
drak0n1c | a day ago
dionian | a day ago
tankenmate | a day ago
Because of that Linux works so much faster with small files, and text files are small compared to audio, video, etc.
Chinjut | a day ago
(So what is this article talking about? I guess it's talking mainly about "Write programs to handle text streams, because that is a universal interface".)
kazinator | a day ago
https://news.ycombinator.com/item?id=49393741
pjmlp | 17 hours ago
A famous book has this quote, and then some folks express the idea all the time, except as you well put it doesn't match practice.
One just needs to dig out the man pages for any commercial UNIX from the early 1990's.
zahrevsky | a day ago
No, users were used to it because that's how Google works.
kazinator | a day ago
- parse command line arguments in a slightly different way from other tools
- parse some ad hoc input format specific to itself
- do one or more actual jobs
- produce output in its own ad hoc format
- produces a termination status; here there can be variations: tools written "void main" that return a nondeterministic status; tools that use multiple nonzero codes for multiple interesting non-success conditions.
This messy way of doing things has "won" in AI ecosystems, I suppose.