Understanding the Linux Kernel: The Linux Kernel Startup(internals-for-interns.com) |
Understanding the Linux Kernel: The Linux Kernel Startup(internals-for-interns.com) |
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...
Could you provide more details about these mistakes?
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.
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.
I guess there's a bit of signal in there, another person thought this nugget of symbols is worth paying attention to
C. "...using initramfs. The call to prepare_namespace() must be skipped. This means that a binary must do all the work. Said binary can be stored into initramfs either via modifying usr/gen_init_cpio.c or via the new initrd format, an cpio archive. It must be called “/init”. This binary is responsible to do all the things prepare_namespace() would do..."
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.
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 .