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

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

#31

Post by csnweb »

bombcar wrote: post #22
Aqua_Geek wrote: post #18

Earlier quoted context omitted.

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.

If Siri could do the following reliably (meaning not having to ask again, not having to repeat, having it work 99% of the time) it would be golden: 1. Find my phone via Siri on homepod 2. Set a simple timer 3. Add to a list 4. Send a text message to one of a few contacts It can and sometimes does do all of those things, but horribly unreliably.

For me it really is extremely close to 100% for timers, I barely remember it being wrong and I use it several times per day. Finding my phone via the HomePod also works pretty much every time, may be 90% for me but it doesn’t recognize my wife so for her it basically never works. The others I don’t use enough. But timers and reminders work really well for me and it’s also what I need to most from an assistant.

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

#32

Post by AJRF »

refibrillator wrote: post #8

Biggest model is 30b MoE trained on 100b tokens, max sequence length 4096. A bit underwhelming compared to recent announcements like the open source Large World Model [1]. Absolutely no benchmarks against GPT4 present in the paper. Notably they used instruction response pairs generated from GPT4 for supervised fine tuning. Which has always felt like an experimental hack to me, but that’s how many folks are bootstrapp…

> Absolutely no benchmarks against GPT4 present in the paper.

Table 4 on page 14 shows comparisons to GPT4V

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

#33

Post by [deleted] »

erulabs wrote: post #23

If it’s going to take general artificial intelligent to get a voice assistant that can remember not one, but two entirely separate cooking timers, then so be it. Imagine the GPUs required! I’m still baffled at Siri and Google assistant. Virtually zero innovation in a decade. I just want to be able to turn on BBC radio while my hands are wet, is that really so hard?!

[deleted]

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

#34

Post by CharlesW »

Rinzler89 wrote: post #26
samatman wrote: post #24

Earlier quoted context omitted.

> that can remember not one, but two entirely separate cooking timers You're in luck! Siri will do that right now. Just tried it. Works.

OMG, 2 cooking timers?! Pinnacle tech right there. Knowing Apple, I was expecting one base timer, with every other timer being a $200 upgrade.

https://www.tomsguide.com/how-to/how-to-set-up-and-manage-mu...

“How many timers can you have going at one time? […] …I had 26 timers going at once, and the only reason I didn't have more running was because I got bored.”

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

#35

Post by Rinzler89 »

CharlesW wrote: post #34
Rinzler89 wrote: post #26

Earlier quoted context omitted.

OMG, 2 cooking timers?! Pinnacle tech right there. Knowing Apple, I was expecting one base timer, with every other timer being a $200 upgrade.

https://www.tomsguide.com/how-to/how-to-set-up-and-manage-mu... “How many timers can you have going at one time? […] …I had 26 timers going at once, and the only reason I didn't have more running was because I got bored.”

I wonder if the maximum number of timers is an 8 bit, 16 bit or 32 bit int.

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

#36

Post by bombcar »

csnweb wrote: post #31
bombcar wrote: post #22

Earlier quoted context omitted.

If Siri could do the following reliably (meaning not having to ask again, not having to repeat, having it work 99% of the time) it would be golden: 1. Find my phone via Siri on homepod 2. Set a simple timer 3. Add to a list 4. Send a text message to one of a few contacts It can and sometimes does do all of those things, but horribly unreliably.

For me it really is extremely close to 100% for timers, I barely remember it being wrong and I use it several times per day. Finding my phone via the HomePod also works pretty much every time, may be 90% for me but it doesn’t recognize my wife so for her it basically never works. The others I don’t use enough. But timers and reminders work really well for me and it’s also what I need to most from an assistant.

I’ve seen similar. They really don’t have two person houses down pat - timers work great for me (as long as I never have to ask how much remaining; I’d die for a “count down from 30 seconds”) - but for the wife; nothing.

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

#37

Post by CharlesW »

lolinder wrote: 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…

Out of curiosity, where are you seeing this? It's not in the abstract or the paper.

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

#38

Post by JimDabell »

CharlesW wrote: post #37
lolinder wrote: 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…

Out of curiosity, where are you seeing this? It's not in the abstract or the paper.

Some of these comments were originally made in response to this spammy submission:

https://news.ycombinator.com/item?id=39726156

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

#39

Post by CharlesW »

epaga wrote: post #17
a_vanderbilt wrote: post #2

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.

The characterization of "mediocre" is fair, but we're transiting a household to Siri from Alexa (because Alexa doesn't work locally, and because of Amazon's track record on privacy), and it's not noticeably worse.

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

#40

Post by CharlesW »

JimDabell wrote: post #38
CharlesW wrote: post #37

Earlier quoted context omitted.

Out of curiosity, where are you seeing this? It's not in the abstract or the paper.

Some of these comments were originally made in response to this spammy submission: https://news.ycombinator.com/item?id=39726156

Ah! Makes sense now, thank you.
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