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Nano-vLLM: How a vLLM-style inference engine works

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Re: Nano-vLLM: How a vLLM-style inference engine works

#11
post #5

Earlier quoted context omitted.

Funny, this reads even more AI written than the article itself.

The em dashes really aren't helping their case.

Wait—do people here really think the em dash was nonexistent before LLMs? It’s widely used by people like me who care about writing style. The reason LLMs use it is because they reflect care and concern about writing style.

Re: Nano-vLLM: How a vLLM-style inference engine works

#12

Earlier quoted context omitted.

The em dashes really aren't helping their case.

Wait—do people here really think the em dash was nonexistent before LLMs? It’s widely used by people like me who care about writing style. The reason LLMs use it is because they reflect care and concern about writing style.

Yeah, people do seem to think that em dashes are an indicator of GenAI. I have been accused of using AI to write my posts on a forum, precisely because of em dashes. That's how I found out about that particular sniff test people use.

Hasn't made me change the way I write, though. Especially because I never actually type an em dash character myself. Back when I started using computers, we only had ASCII, so I got used to writing with double dashes. Nowadays, a lot of software is smart enough to convert a double dash into an em dash. Discourse does that and that's how I ended up being accused of being an AI bot.

Re: Nano-vLLM: How a vLLM-style inference engine works

#13

Earlier quoted context omitted.

The em dashes really aren't helping their case.

Wait—do people here really think the em dash was nonexistent before LLMs? It’s widely used by people like me who care about writing style. The reason LLMs use it is because they reflect care and concern about writing style.

Nobody ever said that they were nonexistent before LLMs. When you are investigating and trying to determine if something is AI generated they are the number one indicator.

So if you're being accused of just spewing AI, then double down and spew what looks EVEN MORE like AI. What are you even doing?

Re: Nano-vLLM: How a vLLM-style inference engine works

#14
post #5
post #4

Earlier quoted context omitted.

Hi jbarrow, thanks for your feedback and the links you shared—they're great readings for me (and likely others too). That said, I need to clarify: the content was not written by AI, and certainly not generated from a database in one shot. If there's some agent + prompt that can produce what I wrote, I'd love to learn it—it would've saved me two weekends :) Before addressing your questions further, some context: I'm a…

Funny, this reads even more AI written than the article itself.

It does, but what does that say about the state of communication in our industry? I've seen a lot of writing that reads like an AI produced it in contexts where I could be pretty sure no AI was involved. We want to sound professional, so we sanitize how we write so much that it becomes... whatever this current situation is.

No offense intended to @yz-yu, by the way. I miss the times when more people wrote in an eccentric style -- like Steve Yegge -- but that doesn't detract from what you wrote.

Re: Nano-vLLM: How a vLLM-style inference engine works

#15

Earlier quoted context omitted.

Wait—do people here really think the em dash was nonexistent before LLMs? It’s widely used by people like me who care about writing style. The reason LLMs use it is because they reflect care and concern about writing style.

Yeah, people do seem to think that em dashes are an indicator of GenAI. I have been accused of using AI to write my posts on a forum, precisely because of em dashes. That's how I found out about that particular sniff test people use. Hasn't made me change the way I write, though. Especially because I never actually type an em dash character myself. Back when I started using computers, we only had ASCII, so I got used…

Shouldn't a double dash result in an en dash and only a triple in an em dash?

Re: Nano-vLLM: How a vLLM-style inference engine works

#17
post #2

The whole thing feels AI written, generated from the codebase.* *this is incorrect per the author’s response, my apologies. For instance, it goes into (nano)vLLM internals and doesn’t mention PagedAttention once (one of the core ideas that vLLM is based on)[1]. Also mentions that Part 2 will cover dense vs MoE’s, which is weird because nanovllm hardcodes a dense Qwen3 into the source. Here are better (imo) explainers…

Actually I thought it was a great example clarity, focus, and economy of words that AI is not capable of at this point in time.

Re: Nano-vLLM: How a vLLM-style inference engine works

#18
post #5
post #4

Earlier quoted context omitted.

Hi jbarrow, thanks for your feedback and the links you shared—they're great readings for me (and likely others too). That said, I need to clarify: the content was not written by AI, and certainly not generated from a database in one shot. If there's some agent + prompt that can produce what I wrote, I'd love to learn it—it would've saved me two weekends :) Before addressing your questions further, some context: I'm a…

Funny, this reads even more AI written than the article itself.

One thing to keep in mind is that a lot of non-native English speakers use LLMs to translate to English, or to polish their English prose; they may not realize that it causes the translation to come out in a very LLM-style tone. Not sure if that's the case here, but it looks like OP is a native Chinese speaker so may be using tools to translate to English.

Re: Nano-vLLM: How a vLLM-style inference engine works

#19

Earlier quoted context omitted.

The em dashes really aren't helping their case.

Wait—do people here really think the em dash was nonexistent before LLMs? It’s widely used by people like me who care about writing style. The reason LLMs use it is because they reflect care and concern about writing style.

No, people think humans use it a lot less often than AI, because it’s true. Especially for casual writing.

The contrast might become even greater because some humans that did use them have stopped to avoid false accusations.

Re: Nano-vLLM: How a vLLM-style inference engine works

#20
post #5

Earlier quoted context omitted.

Funny, this reads even more AI written than the article itself.

It does, but what does that say about the state of communication in our industry? I've seen a lot of writing that reads like an AI produced it in contexts where I could be pretty sure no AI was involved. We want to sound professional, so we sanitize how we write so much that it becomes... whatever this current situation is. No offense intended to @yz-yu, by the way. I miss the times when more people wrote in an eccen…

The comments here turned out much more interesting than I expected—this has become a great place to discuss the difference between AI-generated, AI-written, and AI-assisted content.

So let me start from @jbarrow's comment: "AI written, generated from the codebase."

My actual learning process looked like this:

1. I walked through the nano-vLLM codebase, asking Claude Code some high-level questions to warm up. 2. Then I asked detailed questions one by one, let it explore, and double-checked the code myself. As someone without an ML background, it sometimes took hours to understand a single concept. 3. Once I felt I understood enough, I started drawing Excalidraw diagrams to explain what I learned.

Does this count as "generated from the codebase"? I don't think so.

Where we might disagree is the writing process.

As a non-native English speaker, my workflow looks like this:

1. Write a short paragraph (Is this "AI-written"? I'd call it "AI-assisted." Every idea in every sentence is mine. Honestly, things like "em dashes" never stood out to me when reviewing. I suspect that's common for non-native speakers.

I wrote this comment the same way. The LLM fixed 14 grammar mistakes that I think would distract readers more than any LLM-ish phrasing.

That said, I'm open to suggestions on how to improve my writing process :)

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