241–250 of 297 posts
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In chat history you can see which model generated each request - for me it’s always LaMDA
It just says "Bard", even if I click on "Details". Are you, perhaps, using some kind of internal preview?
I'm based in the UK, I wonder if that makes any difference
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In chat history you can see which model generated each request - for me it’s always LaMDA
I don't see which model generated each request, where exactly do you see this?
Here's a screenshot: https://imgur.com/a/sgtVt2O
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The name 3.5-turbo sounds to me like it implies distillation. The release notes at the time also hinted at it IIRC.
Well, that's why I said public. Personally, I don't think release notes https://help.openai.com/en/articles/6825453-chatgpt-release-... hinted at any such thing, and I think quantization is more likely than distillation.
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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.
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…
But there is a PaLM API: https://developers.generativeai.google/
Of course this is a reaction to the OpenAI API.
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Yeah, this is a holdover from where LLMs grew out of: academia. "Technical report" is what you reach for when you don't want to compare to actual competitive baselines.
I'm sorry, this is nonsense. Technical reports exist to fill in information that is useful for readers but not necessary to understand the key contributions of the work, and/or that don't fit within the journal or conference's page limit. I'm not sure where you got the idea that it is something people do to avoid competitive baselines; IME, the peer-reviewed portion of the publication is far more likely to contain mi…
I should have worded it better, in hindsight.
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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.
Here is their Chat Playground for PaLM 2 https://console.cloud.google.com/vertex-ai/generative/langua... (you have to be logged in to Google Cloud Console I think) Anyone know what parameters are best for code generation? I tried something simple for Node.js and it wasn't horrible but not working. Maybe I used the wron parameters. I tried using 0 for the temperature and turning everything else down like I do with the…
Isn't Chat-Bison-001 Palm 1? Edit: It seems I can't use my free credits on Vertex APIs... Not nice.
Versions Resource ID Release date Release stage Description text-bison@001 2023-05-10 Public Preview Quality improvements and restage -001 as the first stable base model release
https://console.cloud.google.com/vertex-ai/publishers/google...
"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?
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You mean when they filled out a form to incorporate their non-profit. Which they later turned into a for-profit company after reaping all the goodwill. The “Open” used to mean something.
All non-profit means is a different tax status. Don't assume they actually don't make money.
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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.
'Open Systems' predate 'Open Source' by a decade. https://en.wikipedia.org/wiki/Open_system_(computing) https://en.wikipedia.org/wiki/The_Open_Group
> "open source" marketed as trumping "open system".
Common use and understanding of the use "open" evolved decades ago.
Your comment also tries to side step the issue at heart people are annoyed and frustrated by. The founding principles of the OpenAI foundation laid out exactly what that usage of "Open" meant for their organization and they have since backtracked on their own principles.