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PaLM 2 Technical Report [pdf]

ai.google

181–190 of 297 posts

Re: PaLM 2 Technical Report [pdf]

#181
post #163
post #84

Earlier quoted context omitted.

why don't you just use chatGPT? from what i know it's running GPT3.5 and it's not that different (at least in terms of code quality)

When my 25 queries per 3 hours runs out I don't use openai at all. That's how bad chat gpt is in comparison to gpt4 in my use cases.

My biggest complaint is the speed. Watching it print out like 56k is pretty annoying when coding.

Re: PaLM 2 Technical Report [pdf]

#182
post #140

I don't understand how this can be considered a technical report. No information on model architecture, distributed training methodology, or optimizations. The "Training dataset" section is a pathetic 0.5 pages long. Come on, Google.

That will be the norm moving forward

LLM is going to make money, a lot of money, nobody is going to give away their secret sauce for free.

Prepare for the landscape to get really ugly and really soon. Maybe we will witness some epic legal battle around big techs.

Re: PaLM 2 Technical Report [pdf]

#183

Earlier quoted context omitted.

this is about the time that i expect sites to begin returning intentionally corrupt/incorrect/perhaps outright garbage (subtle or not, probably better subtle so they don't realize it until it's far too late) data in order to intentionally poison enemy wellscraping. where "ethics" dissolve into the inherent raw cannibalistic laws of capitalist ventures. then you can sell them back the TBs they scraped at a 1000x marku…

You might be right. What a dystopian future that will be. Make a few requests too many and the webserver might think you're scraping data so it gaslights you into reading bullshit.

Is this sarcasm? I can’t tell.

Re: PaLM 2 Technical Report [pdf]

#184
post #169

Earlier quoted context omitted.

Btw I've arrived at a different interpretation of the "Open" in OpenAI. It's open in the sense that the generic LLM is exposed via an API, allowing companies to build anything they want on top. Companies like Google have been working on language models (and AI more broadly) for years but have hid the generic intelligence of their models, exposing it only via improvements to their products. OpenAI bucked this trend an…

> Btw I've arrived at a different interpretation of the "Open" in OpenAI. I don't understand why people have to keep trying to wrap their head around the word 'Open' in OpenAI. If you ever saw a commercial like a product has a 'great new taste' but then you tried it and it tasted bad, would you twist yourself into knots trying to understand how you went wrong in your interpretation of 'great'? No that's ridiculous. S…

I think the strong connotation of the word "open" in the software community comes from "open source". If OSS was called "great new source" and a new closed source company called itself GreatNewAI you'd have a similar phenomenon of people taking apart the name.

Re: PaLM 2 Technical Report [pdf]

#185

Earlier quoted context omitted.

Btw I've arrived at a different interpretation of the "Open" in OpenAI. It's open in the sense that the generic LLM is exposed via an API, allowing companies to build anything they want on top. Companies like Google have been working on language models (and AI more broadly) for years but have hid the generic intelligence of their models, exposing it only via improvements to their products. OpenAI bucked this trend an…

Guess they should rebrand as AvailableAI then...

US healthcare should rebrand as “accessible”, even if it is not “affordable” by millions. With an interesting definition of accessible.

Re: PaLM 2 Technical Report [pdf]

#186

Earlier quoted context omitted.

Most of the GPT-4 benchmarks from their report were things like AP tests or leer code scores. Which aren’t benchmarks that can be compared by a different set of researchers as you don’t know the constituent parts of the test to run

GPT-4 report has MMLU score, which is believed to one of the most important metric for question answering task. GPT-4 MMLU score is slightly higher than PaLM 2(86 vs 81). Google didn't compare it in with PaLM 2 in this paper.

86 vs 81 is not slightly higher. It’s 26% fewer wrong answer.

Re: PaLM 2 Technical Report [pdf]

#187
post #137

Earlier quoted context omitted.

I've asked "are you using palm 3": It said: I am using the Palm 3 model. Palm 3 is a large language model... Don't believe it :) Also, In the technical report, It mentions multiple languages, I've asked in Turkish which was supposed to be supported, but wasn't able to answer. Even if its PaLM 2, its hard to trust to the model itself.

I asked it "are you using the palm 420 language model or the palm 2 language model?" It said "I am not using either the Palm 420 language model or the Palm 2 language model. I am using a different language model called Bard, which is a large language model from Google AI." Perhaps the people at Google saw this and made a manual correction? Hard to say, black boxes and all...

It doesn't have the capability to be corrected that easily. It's just lying.

Bard is very bad about this, it lies with the slightest encouragement. Try "compare and contrast captain planet and paptain clanet".

Re: PaLM 2 Technical Report [pdf]

#188
post #64

Earlier quoted context omitted.

Is it better than bing or phind though? Why would I use it over bing?

Bard is really fast. Faster than Bing and Phind.

Yeah fast, but also kinda garbage last time I tried it. Does it even show sources now?

Re: PaLM 2 Technical Report [pdf]

#189

Earlier quoted context omitted.

Is it better than bing or phind though? Why would I use it over bing?

It isn't Edge-specific which is good and I find it faster than Bing. Phind is way better than Bard, but verbose. I still find ChatGPT my first port of call. GPT-3.5 is blazing fast and very useful.

There is a web extension you can install to make it work on whatever browser you want.

Re: PaLM 2 Technical Report [pdf]

#190
post #4

"The PaLM 2 pre-training corpus is composed of a diverse set of sources: web documents, books, code, mathematics, and conversational data" I really want to know more about the training data. Which web documents, which books, code from where, conversational data from where?

I fully expect Discord to be a data source, if not already, then for a future version. I also expect that the only way the general public would ever find this out is via whistle-blower.

It'd be pretty easy to tell; you could just ask it to generate Discord chats and notice it works. Text models also like to memorize their inputs if they're big enough, so you could probably get specific ones.
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