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MM1: Methods, Analysis and Insights from Multimodal LLM Pre-training

arxiv.org

11–20 of 65 posts

Re: MM1: Methods, Analysis and Insights from Multimodal LLM Pre-training

#11
post #4

The paper lists "first authors", "core authors", and "senior authors". My dream is to one day be listed on a seminal paper as "secondary forum reply author".

Similarly, I’d like the movie credit Second Assistant to the Second Second Assistant Director.

Re: MM1: Methods, Analysis and Insights from Multimodal LLM Pre-training

#12
post #5

This looks competitive against CLIP, and surprisingly great at VQA style prompts, but it doesn't seem like the paper supports comparing it to GPT-4. We don't see any tests for coding performance, math homework, legal document review, or any of the myriad other things that people use GPT-4 for on a daily basis.

Besides homework, all of these things seem to be professional uses of GPT-4. If they’re trying to bake this into a consumer platform like Siri, I don’t see why they’d need to focus on those use cases. Besides MDM/Enterprise, which will be curious if they try and attack this market or just their army of consumer devices.

Good insight. My comment was based on the headline that says "...Competing with ChatGPT".

Re: MM1: Methods, Analysis and Insights from Multimodal LLM Pre-training

#13
post #7

MM1 is a research paper, not a release of a competing product. I'm sure the paper is interesting and am looking forward to reading an analysis of it by someone who understands these things better than I do, but this is not that analysis, it's an extremely low-effort puff piece that is more interested in getting attention than in accurately describing a research paper. I don't usually say this, but TFA frankly feels l…

I believe most run-of-the-mill marketing language will sound like it is written in AI. The easiest thing to do for technology writing is to write the complete, factual article, then ask an LLM to dumb it down to whatever level you need for communication.

No, I agree this really does seem autogenerated, or at the very least written by somebody who doesn’t understand the topic at all and is going through the motions of padding things out to hit a hype / word count. It’s got that weird summary focusing on the wrong things and wild speculations dressed up as serious predictions vibe, like there are words saying things in places because there are supposed to be words there and not because it’s actually imparting useful information.

Re: MM1: Methods, Analysis and Insights from Multimodal LLM Pre-training

#14
post #4

The paper lists "first authors", "core authors", and "senior authors". My dream is to one day be listed on a seminal paper as "secondary forum reply author".

Similarly, I’d like the movie credit Second Assistant to the Second Second Assistant Director.

"Junior Assistant Vice-Dean" (or variants thereof) in academia. Those mostly exist to give a pay boost to administrators who've otherwise maxed out on pay.

I recall that my undergrad institution once invented a new deanship out of whole cloth for a coach who'd maxed out on the "professor" pay scale.

Even worse, the bastard didn't even win games!

Re: MM1: Methods, Analysis and Insights from Multimodal LLM Pre-training

#15

I wonder if this has anything to do with their acquisition of DarwinAI. After a decade of mediocrity, I'd love to see Siri get smarter. Any improvement would be welcome at this point.

I agree. The whole push to have Siri work on device was a noble one, but I’d rather have the option for a dumber on device Siri or a smarter in the cloud Siri.

Re: MM1: Methods, Analysis and Insights from Multimodal LLM Pre-training

#17

I wonder if this has anything to do with their acquisition of DarwinAI. After a decade of mediocrity, I'd love to see Siri get smarter. Any improvement would be welcome at this point.

Mediocrity is far too positive a word for the dumpster fire that is Siri.

Re: MM1: Methods, Analysis and Insights from Multimodal LLM Pre-training

#18

I wonder if this has anything to do with their acquisition of DarwinAI. After a decade of mediocrity, I'd love to see Siri get smarter. Any improvement would be welcome at this point.

Honest question: what do you (in the general sense, not specifically asking the parent) use Siri for? I think my main (only?) use case is setting a timer.

Maybe I find conversational UIs awkward, or maybe I just got jaded REALLY quickly from Siri’s lacking capabilities early on, but I have hardly used it in the decade or whatever that it’s been around.

Re: MM1: Methods, Analysis and Insights from Multimodal LLM Pre-training

#19

I wonder if this has anything to do with their acquisition of DarwinAI. After a decade of mediocrity, I'd love to see Siri get smarter. Any improvement would be welcome at this point.

Honest question: what do you (in the general sense, not specifically asking the parent) use Siri for? I think my main (only?) use case is setting a timer. Maybe I find conversational UIs awkward, or maybe I just got jaded REALLY quickly from Siri’s lacking capabilities early on, but I have hardly used it in the decade or whatever that it’s been around.

I use it almost daily for something that is simple but under appreciated I don’t know why it’s not in every marketing video: “Siri, remind me tomorrow at 10am to do X”

I outsource so much of my memory to the phone via Siri ALL THE TIME. It’s so useful. Even for things in 20m. I’ll easily forget if I don’t do this, and it’s reliable so it gives me confidence. It also keeps the notification present until I actually do the thing, so I have a kind of string around my finger until the task is accomplished. I can also snooze that notification as needed to rebring it up at the right time.

Every time I do this around non-tech people they go “wow I didn’t know you could do that.” I swear it’s literally life changing, particularly for anyone over 30.

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