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PaperclipPerfector  5d ago (text post)   25066 thread views

Culture War Roundup for the week of February 17, 2025

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No, parsing bits from a video file does happen practically instantly. Download a video file to your local disk, and play it from there, you’ll see. Even on YouTube, if you rewind back, it will have to represent the bytes again.

The reason it takes a while for YouTube stream to start is that this is what it takes for YouTube to locate the bytes you asked for and start streaming them to you.

Yes, and for the LLM to parse these bits, first youtube needs to locate them, then serve them to the llm. If the llm can convince youtube to serve the bits as fast as bandwidth will allow, it still needs to run those bits through some transcription algo -- which typically are borderline on lagging at 1x speed.

In the instant case, it would also need that algo to make some sort of judgement on the accent with which some of the words are being pronounced -- which is not a thing that I've seen. The fact that it goes ahead and gets this wrong (Cash pretty clearly says gam-bel-er in the video) makes it much more likely that the llm is looking at some timestamped transcript to pick up the word "gambler" in the context of country songs, and hallucinating a pronunciation.

which typically are borderline on lagging at 1x speed.

That's just not true. You see them running at 1x speed, because they only ever need to run at 1x speed. Running them faster is a waste of resources: what's the point of transcribing video in its entirety, if you are going to close the tab before it ends?

This is running on my home PC:

main: processing 'johny-cash-gods-gonna-cut-you-down.wav' (2739583 samples, 171.2 sec), 24 threads, 1 processors, 5 beams + best of 5, lang = en, task = transcribe, timestamps = 1 ...
(...)
[00:00:38.360 --> 00:00:52.120]   Go tell that long-tongued liar, go and tell that midnight rider, tell the rambler, the gambler, the backbiter, tell him that God's gonna cut him down.
(...)
whisper_print_timings:    total time = 67538.11 ms

That's 2.5x transcription speed, and it's just running on CPU, not even using GPU.

Look, guys, processing your stupid-ass text questions on a frontier LLM takes way more resources than speech transcription. Whisper on my CPU can do 400 GFLOPS, so the above 67 seconds run used something like 26,000 GFLOPs. For comparison, running a transformer model on a single token requires something like twice the number of parameters of the model worth of flops. So, for example, GPT-3, a junk tier model by today's standards, has 175B parameters, so just feeding it the lyrics of Cash's song would need 150,000+ GFLOPs, and that's before it even produces any output.

In the instant case, it would also need that algo to make some sort of judgement on the accent with which some of the words are being pronounced -- which is not a thing that I've seen.

Modern speech transcription models not only make judgements on accents as a normal course of operations, they actually understand the speech they are transcribing to some (limited) extent in the same sense as more general LLMs understand the text fed into them. It would actually be a pretty cool project for a deep learning class to take something like OpenAI Whisper, and fine tune it to make it into accent detection tool. It's all there inside the models already, you'd just need to get it out.

Just to be clear: I'm not arguing that Grok 3.0 does in fact do all of this with the Johnny Cash song. All I'm saying is that it could. The frontier LLMs are all multimodal, which usually means that they can process and generate image tokens in addition to text tokens. There's literally no technical reason why they couldn't add audio token type, and some of them probably already do that.

whisper_print_timings: total time = 67538.11 ms

OK? 67 seconds is not instant -- like, at all. Even 6.7s (assuming the resources assigned to this task were as you suggest) is not instant.

I'm not arguing that Grok 3.0 does in fact do all of this with the Johnny Cash song. All I'm saying is that it could.

Of course it could! But it doesn't, and the fact that it responded instantly is evidence of that. Do you really think Grok is spending resources (mostly dev time, really) to add features allowing the model to answer weird questions about song lyrics?

LLMs lie man -- we should get used to it I guess.

In case it wasn’t clear: it took 67 seconds to transcribe an entire 171 seconds long song on my home CPU. You don’t have to wait for it to finish either: it produces output as it goes. It takes less than 20 seconds to process the entire song on my 9 year old gamer GPU. It would take less than half a second on a single H100. On 5 H100s, transcribing the entire song would take less time that it would take you to blink an eye. X AI reportedly has 100,000 of H100s.

But it doesn't, and the fact that it responded instantly is evidence of that.

How is it any evidence? Responding to the question is at least an order of magnitude more computationally demanding task than transcribing the entire song.

Do you really think Grok is spending resources (mostly dev time, really) to add features allowing the model to answer weird questions about song lyrics?

That’s the amazing thing about multimodal LLMs: they wouldn’t even have to add any special feature, with multimodality you get it for free. For a multimodal LLM model that is trained on sound tokens as well as on text tokens, understanding the words in a song, and analyzing accents etc is literally the same task as answering text questions. When you ask Grok a question, it searches web, fetches websites, and processes the contents. Fetching and processing song is, again, exactly the same task to the multimodal LLM as processing text.

Sounds are not text though -- nothing is free, and nothing is instant.

Why don't you try it? Ask Grok to transcribe a song from a youtube link and see what it does -- preferably a song that differs from the published lyrics somehow, maybe a live version or something.

So you think it’s real? I think it’s an interesting question, possible either way. On the other hand, gambler is clearly pronounced with three syllables in the song, which suggests it’s clear some hallucination is going on.

Also, can’t this obviously be tested? Can’t we just see if it can accurately transcribe a 30 minute newly uploaded YouTube video in a couple of seconds? Idk.

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