It's essentially a "Amazon and Google don't use this k thx."
Apple is the big laggard in terms of big tech and complex neural network models.
v. You will not use the Llama Materials or any output or results of the Llama Materials to improve any other large language model (excluding Llama 2 or derivative works thereof).
https://github.com/facebookresearch/llama/blob/main/LICENSE
Just like Google scrapes the internet to improve their models, it might make sense to ingest outputs from other models to improve their models. This licensing prevents them from doing that. Using Llama to improve other LLMs is specifically forbidden, but Google will also be forbidden from using Llama to improve any other AI products they might be building.
I understand trade-secrets are not free-speech but if the goal is to build better AI to serve the humanity the different bots should learn from each other. They should also criticize each other to find flaws in their thinking and biases.
Whose goal is that?
It’s not.
And they want to be very careful about labeling outputs as derivative works, because the moment they do that then they have no defense against the model being a derivative work of every single input.
> I wouldn't be surprised if Amazon does as well.
I would - they are not a very major player in this space.
TikTok also meets this definition and probably doesn't have LLM.
It is pretty ridiculous that they essentially just set a marketing team with no programming experience to write Bard, but that shouldn't fool anyone into believing they don't have capable models in Google.
If Deepmind were to actually provide what they have in some usable form, it would likely be quite good. Despite being the first to publish on RLHF (just right before OpenAI) and bring the idea to the academic sphere, they mostly work in areas tangential to 'just chatbots' (e.g. how to improve science with novel GNNs, etc). However, they're mostly academics, so they aren't set on making products, doing the janitorial work of fancy UIs and web marketing, and making things easy to use, like much of the rest of the field.
I'm pretty sure if google had something much better, the board and C-suite execs would have at least ensured we saw previews of it by now...
Google is getting the asses handed to them, badly. I figured that the code red would whip them into shape but the rot runs deep.
> they mostly work in areas tangential to 'just chatbots' (e.g. how to improve science with novel GNNs, etc)
Yes, Alphabet has poured tons of money into exotic ML research whereas Meta just kept pouring more money into more & deeper NLP research.
All the AlphaGo/AlphaFold stuff is very cool, but since no one has seen their LLMs this is about as convincing as my claiming I've donated billions to charity.
It seems it is not aware of the notion of historic development, perhaps its world-model is "static"?
Temporal reasoning is interesting , if you google for "news" do you get what was news last year because a website updated last year had a page claiming to contain "Latest News".
REF: https://www.stefanjudis.com/today-i-learned/property-order-i...
Google's publically available model isn't as capable. But they certainly have models that are far better already in house.
Gotta put products in the market, or it didn't happen...
Meta is definitely ahead of Google in terms of NLP expertise and has been for a while. I suspect that Google released their best model at the time with Bard.
TikTok has 1 billion monthly active users for instance
poor reading of the numbers. one guy at a bank pulled up similarweb and guesstimated 100m registered users and it went viral. whisper numbers were closer to 50m. but in the 6 months since they have certainly crossed 100m and probably are north of 500m, and only recently dipped.
