> That’s pretty much what the Linux kernel does at boot. The bootloader is the dropship. Your computer is the barren planet. The advance team is the execution of the startup code in the Linux kernel—the one we’ll be following the whole time. And by the end of this article, that advance team will literally have transformed itself into the standby maintenance crew while a brand-new civilian government takes over. Bear with me—it’ll make sense as we go.
Seems pretty good so far, but the article writes itself in the intro to be very basic, which is a good thing for me, never looked at how the Linux kernel actually boots, so I have only the basic understanding from college.
These horrible analogies though scream AI-generated content. LinkedIn is full of such crap: AI apparently atm loves to sprinking short sentences of the form: "The X is the Y. The A is the B." or "It's not C. It's D". when making analogies.
Everything has to be a "pattern": things cannot be described on their own. There needs to be a connection to something else for it to explain something: we're talking computers? We must somehow cram in the similitude with a four-strokes combustion engine.
I mean: how is fine-tuning a program or some heuristics not the same as a variable valve-timing motor engine feature?
"It's not fixed valve-timing we're dealing with. It's a variocam!".
You should be reading a more formal document, seems to me you are just not the target audience. You disliking the analogies and getting tired at it for not getting to the point doesn't necessarily mean the text is bad, because that's too much of a narrow view in which to criticise a text that is clearly almost a social communication piece of sorts.
https://lwn.net is a goldmine of great contents about Linux kernel.
Let me explain why I post links to posts from https://internals-for-interns.com . I hate AI slop. The author of these posts uses AI for generating these posts - this is clearly visible via AI-generated images, emojis and em dashes. But the posts themselves do not contain misleading slop you could see in a typical AI-generated content. These posts are very clear and accurate. While they contain some inaccuracies and mistakes, the number of these mistakes is very low. These posts help learning and understanding complex technical topics such as internals of Go, filesystems, databases and linux kernel, by reading a clear easy to understand text.
It is important to differentiate between low-quality AI slop and high-quality contents generated with the help of AI. The posts at https://internals-for-interns.com belong to the second category.
there is a certain irony in not being able to spend 5 seconds to verify your complaint, when your complaint is presumably about the author's lack of effort.
I’m not sure what you mean. I saw the emoji bullet point, the em dashes, the date of the first post, and scrolled to a random paragraph; that’s plenty of verification.
That emoji is about as appropriate as can be. It is an important disclaimer that is very useful to know, which would else easily be missed if just flying over the text (as I tend to do, to check if the outline is interesting enought for me to read the whole text).
Emdash wise having a total of 97 really is excessive in such a text. That is averaging like 2 every 4 line paragraph. It really tells me it was likely sent through an LLM.
I'm really enjoying this article. Many years ago when I created LTSP I had to dive in and understand how the whole bzImage and initrd worked so we could fetch a kernel with tftp and mount a root filesystem via NFS. It's been years since I've played with this stuff but it's still very interesting to me. Thank you!
No no you are not looking at this correctly :-) This AI slop, on which I was able to quickly find four mistakes...
Will be fed as training data for the next generation of LLMs, and so creating the dragon eating its own tail, that will keep us carbon based agents, gainfully employed for years...
Is this the future? Trillion dollar companies suck up all content from the internet and published media they can get their hands on and then we all pay them to pull out what we all individually scooped up into chunks from experience and republish it as potentially repetitive and non authoritative source material?
I guess there's a bit of signal in there, another person thought this nugget of symbols is worth paying attention to
LPisGood | 15 hours ago
gchamonlive | 14 hours ago
Seems pretty good so far, but the article writes itself in the intro to be very basic, which is a good thing for me, never looked at how the Linux kernel actually boots, so I have only the basic understanding from college.
TacticalCoder | 13 hours ago
I'm not sure about "good".
These horrible analogies though scream AI-generated content. LinkedIn is full of such crap: AI apparently atm loves to sprinking short sentences of the form: "The X is the Y. The A is the B." or "It's not C. It's D". when making analogies.
Everything has to be a "pattern": things cannot be described on their own. There needs to be a connection to something else for it to explain something: we're talking computers? We must somehow cram in the similitude with a four-strokes combustion engine.
I mean: how is fine-tuning a program or some heuristics not the same as a variable valve-timing motor engine feature?
"It's not fixed valve-timing we're dealing with. It's a variocam!".
If you ask me I find it really tiring already.
gchamonlive | 12 hours ago
mirzap | 3 hours ago
[OP] valyala | an hour ago
Let me explain why I post links to posts from https://internals-for-interns.com . I hate AI slop. The author of these posts uses AI for generating these posts - this is clearly visible via AI-generated images, emojis and em dashes. But the posts themselves do not contain misleading slop you could see in a typical AI-generated content. These posts are very clear and accurate. While they contain some inaccuracies and mistakes, the number of these mistakes is very low. These posts help learning and understanding complex technical topics such as internals of Go, filesystems, databases and linux kernel, by reading a clear easy to understand text.
It is important to differentiate between low-quality AI slop and high-quality contents generated with the help of AI. The posts at https://internals-for-interns.com belong to the second category.
While at it, I recommend reading the article from ClickHouse author on how to properly use AI - https://clickhouse.com/blog/agentic-coding .
john_strinlai | 14 hours ago
LPisGood | 14 hours ago
john_strinlai | 14 hours ago
LPisGood | 14 hours ago
NekkoDroid | 3 hours ago
Emdash wise having a total of 97 really is excessive in such a text. That is averaging like 2 every 4 line paragraph. It really tells me it was likely sent through an LLM.
landdate | 13 hours ago
jammcq | 14 hours ago
oncallthrow | 14 hours ago
tcp_handshaker | 12 hours ago
Will be fed as training data for the next generation of LLMs, and so creating the dragon eating its own tail, that will keep us carbon based agents, gainfully employed for years...
[OP] valyala | an hour ago
Could you provide more details about these mistakes?
SilentM68 | 12 hours ago
whattheheckheck | 12 hours ago
I guess there's a bit of signal in there, another person thought this nugget of symbols is worth paying attention to
nainachirps_ | 10 hours ago