So, I asked Bard if it's using PaLM 2 and it did confirm it. My initial results are super promising. Highly recommend checking it out again.
It's a language model, FFS. Ask it whether it uses PaLM 1 and it will confirm it as well.
PaLM 2 Technical Report [pdf]
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Re: PaLM 2 Technical Report [pdf]
#152Re: PaLM 2 Technical Report [pdf]
#153Earlier quoted context omitted.
Agreed. I'm not entirely sure that the person you're replying to is not joking
I'm pretty sure they're trying to suggest that LLMs in general are not useful because they can't do this type of thing. It's just the next iteration of goal post moving and should effectively be ignored. Many artists and such that I've spoken to about AI work have similar comments about these systems because of the disdain for their existence. The number of times I hear an argument like "well, they can never taste th…
Re: PaLM 2 Technical Report [pdf]
#154The paper begins with: Language modeling has long been an important research area since Shannon (1951) estimated the information in language with next word prediction. Man, I wonder what Claude Shannon would think of all this if he were alive today...
Re: PaLM 2 Technical Report [pdf]
#155personal experience - I'm using GPT4 for writing code especially in python. After using bard today, I feel bard is doing quite well considering its free. I will keep using it and if its keep doing well, I will cancel GPT4 $20/month subscription.
You can use gpt-4 for free (toggle "Use best model"), and it'll search the internet and state sources on https://phind.com No idea when they'll start charging, but it's replaced a lot of my googling at work
Re: PaLM 2 Technical Report [pdf]
#156PaLM 2 on HumanEval coding benchmark (0 shot): 37.6% success GPT-4: 67% success Not even close, gpt4 miles ahead
HellaSwag: GPT-4: 95.3%, PaLM 2-L: 86.8%
MMLU: GPT-4: 86.4%, Flan-PaLM 2-L: 81.2%
ARC: GPT-4: 96.3%, PaLM 2-L: 89.7%
(from: GPT-4 paper: https://arxiv.org/pdf/2303.08774.pdf)
Re: PaLM 2 Technical Report [pdf]
#157So, I asked Bard if it's using PaLM 2 and it did confirm it. My initial results are super promising. Highly recommend checking it out again.
Well, I tried it, and this is how dumb it is. I ask it what's the context length it supports. It said that PaLM 2 supports 1024 tokens and then proceeds to say that 1024 tokens equals 1024 words, which is obviously wrong. Then I changed the prompt slightly, and it answered that it supports 512 tokens contradicting its previous answer. That's like early GPT-3.0 level performance, including a good dose of hallucination…
Re: PaLM 2 Technical Report [pdf]
#158Earlier quoted context omitted.
In that sense, it's very similar to the GPT-4 Technical Report. The era of being "open" about LLMs or other "secret sauce" models in published papers may be over, since these things have become existential threats to companies.
I wonder how special these architectures are compared to what's published. The "secret sauce" may just be getting 2 pages (~200) worth of engineers collaborating and either rolling out your own cloud service or spending $$$ at someone else's. Also not sure how much it matters other than academic interest of course. Realistically, there's only 4-5 (US) companies with the human resources and capital to roll something s…
And because of this I don’t buy that AI is an existential threat to Google at this point. If they were really worried they could spend a tiny portion of their ~280 billion dollars in revenue to train a bigger model.
Re: PaLM 2 Technical Report [pdf]
#159Earlier quoted context omitted.
I wonder how special these architectures are compared to what's published. The "secret sauce" may just be getting 2 pages (~200) worth of engineers collaborating and either rolling out your own cloud service or spending $$$ at someone else's. Also not sure how much it matters other than academic interest of course. Realistically, there's only 4-5 (US) companies with the human resources and capital to roll something s…
I think the secret sauce is just bucket loads of cash to spend on compute. And because of this I don’t buy that AI is an existential threat to Google at this point. If they were really worried they could spend a tiny portion of their ~280 billion dollars in revenue to train a bigger model.
I wasn't aware autoregressive LLMs were still considered an existential threat to Google. What's the threat supposed to be, ChatGPT is just going to keep eating Google search market share burning Microsoft capital on infra a la the Uber model or do they make money off of that at some point?
Seems farfetched OpenAI can compete with Google's resources, vertical integration down to the TPU and access to significantly more training data.
Re: PaLM 2 Technical Report [pdf]
#160Earlier quoted context omitted.
Yeah, everybody agrees on what a character is, right? It's just {an ASCII byte|a UTF8 code unit|a UTF16 code unit|a Unicode code point|a Unicode grapheme}.
And we think tokens solve that problem? Spoiler alert: they don’t https://www.reddit.com/r/OpenAI/comments/124v2oi/hindi_8_tim...