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.
Come on, Google.
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.
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 similar to these models out for what is most likely a complete write-off?
They could claim whatever they wanted and it would be near impossible to validate.
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.
DeepMind's RETRO paper https://arxiv.org/abs/2112.04426 mentions a dataset called MassiveText, which includes 20 million books of 3T tokens. So we know Google is using Google Books, since there is simply no other source of 20 million books. Also as far as I know 3T tokens is more than publicly known to be used by anyone so far: Google could train on more data than anyone else, solely from Google Books, even without using its web crawl.
Edit: it was 2005(!), so it is possible that many of you haven't heard of this. George Dyson, in Turing's Cathedral written in 2005 says:
> My visit to Google? Despite the whimsical furniture and other toys, I felt I was entering a 14th-century cathedral: not in the 14th century but in the 12th century, while it was being built. Everyone was busy carving one stone here and another stone there, with some invisible architect getting everything to fit. The mood was playful, yet there was a palpable reverence in the air. "We are not scanning all those books to be read by people," explained one of my hosts after my talk. "We are scanning them to be read by an AI."
https://www.edge.org/conversation/george_dyson-turings-cathe...
Read the whole thing. It is not an accident Google got Google Books to train AI. That was the plan from the start.
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 and exposed an API to generic LLMs.
https://venturebeat.com/social/facebook-insignia-hoodie/
In the end they just shat all over RSS etc.
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. Same with 'Open' in 'OpenAI'. It's just some letters that form part of the name that they chose for themselves when they filled the form to incorporate their company.
What difference does it make for a non-public company? They can pay themselves more salary either way. The shares aren't really valuable until then.
As to a charity - if you really believe so. It doesn't even enter the books. Have you not seen an in-person donation site? Someone gives $100, the staff keeps the $100, takes out $50, records $50 and puts that in the donation box. After a few more layers the actual donation could be just $1. I've seen these at your regular big name charities - all the time.
And let's not get started on the sponsor a child that doesn't exist options...
Did they have a lot of goodwill attached to their company? What did that give them?
Because of that framing, they poached a lot of very good talent and built one of the best AI teams that has ever been assembled. Then they perverted their corporate structure to be effective for-profit, and renegaded on open access to their trained models, turning into a bog standard service-oriented company.
> "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.
> Your comment also tries to side step the issue ..
We disagree. Narrowly directed and addressing the "issue", in fact.
Salvaging your business from that sort of tantrum by working with MS is called surviving.
But there is a PaLM API: https://developers.generativeai.google/
Of course this is a reaction to the OpenAI API.
FTFY
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.
What this is an instance of is Google's approach to academic publishing of releasing a paper that contains almost no actionable information, but which is considered important and publishable solely because it came from Google and therefore is used in industry. This has been exhibited many times before--e.g. see the original Spanner paper, which was so light on details and confusing that they needed to release a followup paper several years later to explain what the system was even using the atomic clocks for!
I should have worded it better, in hindsight.
This is (IMO) quite different from, e.g., the cases of academics publishing misleading benchmarks, which is more often just being wedded to a bad idea because you spent years of work on it and your position is at risk if you didn't end up outperforming existing approaches. Often I can still get a lot out of papers with misleading benchmarks, even if what I get is "don't try this technique, it doesn't work." Whereas I frequently get nothing at all out of Google publications. If I had to describe the way Google seems to view academic publishing in one word, it would be "marketing"--it's advertising for people to either come work at Google or use their products, not something written with the intent of advancing the wider state of the art, or even the less noble goal justifying the time and money they put into whatever they're writing about.