As someone who doesn't really follow the LLM space closely, I have been consistently turning to Anthropic when I want to use an LLM (usually to work through coding problems)
Beside Sonnet impressing me, I like Anthropic because there's less of an "icky" factor compared to OpenAI or even Google. I don't know how much better Anthropic actually is, but I don't think I'm the only one who chooses based on my perception of the company's values and social responsibility.
Yea, even if they're practically as bad, there's value in not having someone like Altman who's out there saying things about how many jobs he's excited to make obsolete and how much of the creative work of the world is worthless.
I mean, he's certainly acting as if he's entitled to train on all of it for free as long as it's not made by a big enough company that may be able to stop/sue him. And then feels entitled to complain about artists tainting the training data with tools.
He has a very "wealth makes right" approach to the value of creative work.
> Last year, Google committed to invest $2 billion in Anthropic, after previously confirming it had taken a 10% stake in the startup alongside a large cloud contract between the two companies.
Well, there you go. These companies are always closer than they seem at first glance, and my preference for Anthropic may just be patting myself on the back.
Funny, I use Mistral because it has 'more" of that same factor, even in the name!
They're the only company who doesn't lobotomize/censor their model in the RLHF/DPO/related phase. It's telling that they, along with huggingface, are from le france - a place with a notably less puritanical culture.
do you feel the less censorship yourself from their instruction tuned model, or is there some public reference to showcase? (i haven't used mistral model before). It's interesting if a major llm player adopt a different safety / alignment goal.
Personally, I find companies with names like "Anthropic" to be inherently icky too. Anthropic means "human," and if a company must remind me it is made of/by/for humans, it always feels less so. E.g.
The Browser Company of New York is a group of friendly humans...
Second, generative AI is machine generated; if there's any "making" of the training content, Anthropic didn't do it. Kind of like how OpenAI isn't open, the name doesn't match the product.
I actually agree with your principle, but don't think it applies to Anthropic, because I interpret the name to mean that they are making machines that are "human-like".
More cynically, I would say that AI is about making software that we can anthropomorphize.
> Anthropic means "human," and if a company must remind me it is made of/by/for humans
Why do you think that that's their intended reading? I had assumed the name was implying "we're going to be an AGI company eventually; we want to make AI that acts like a human."
> if there's any "making" of the training content, Anthropic didn't do it
This is incorrect. First-gen LLM base models were made largely of raw Internet text corpus, but since then all the improvements have been from:
• careful training data curation, using data-science tools (or LLMs!) to scan the training-data corpus for various kinds of noise or bias, and prune it out — this is "making" in the sense of "making a cut of a movie";
• synthesis of training data using existing LLMs, with careful prompting, and non-ML pre/post-processing steps — this is "making" in the sense of "making a song on a synthesizer";
• Reinforcement Learning from Human Feedback (RLHF) — this is "making" in the sense of "noticing when the model is being dumb in practice" [from explicit feedback UX, async sentiment analysis of user responses in chat conversations, etc] and then converting those into weights on existing training data + additional synthesized "don't do this" training data.
I read Anthropic as eluding to the Anthropic Principle as well as the doomsday argument and related memeplex[0] mixed with human-centric or about humans. Lovely naming IMHO.
We both assumed, so I didn't expect to need to back up my thoughts, but their own website ticks the "for humans" trope checkbox: Their "purpose is the responsible development and maintenance of advanced AI for the long-term benefit of humanity."
I acknowledge and appreciate Anthropic's addition to the corpus of scraped data, but that data (both input and output) is still ultimately from others; if it did not exist, there would be no product. This is very different from a video editing tool, which I purchase or lease with the understanding that I will provide my own content, or maybe use licensed footage for B-roll
> I acknowledge and appreciate Anthropic's addition to the corpus of scraped data, but that data (both input and output) is still ultimately from others; if it did not exist, there would be no product.
There’s a Ship of Theseus thing going on here with the training corpus, though.
Consider the progression of DeepMind’s game-of-go-playing model from AlphaGo to AlphaZero. AlphaGo needed a training corpus of real human games of Go. But AlphaZero was trained by playing against the already-trained AlphaGo model; and then, after that, against earlier versions of itself. AlphaZero never saw any training corpus authored by humans; it only reacted to an agent that knew such a corpus (at the bootstrapping phase) — and since it was treating that agent as a black box to play against, it didn’t actually matter where that other agent’s knowledge of go came from.
Another analogy might be to compilers. The first version of a (systems) programming language’s compiler must necessarily be written in some other language. But usually, a compiler is then written in the language itself, and the non-self-hosted compiler is then used to compile the self-hosted compiler.
Would it be common sense to say that AlphaZero, or the self-hosted compiler, is derived from data “ultimately from others”? IMHO no. Why? I think because, in both cases,
1. the “bootstrap data” is a fungible commodity — many possible datasets (go plays, host languages) are “good enough” to make the bootstrap phase work, with no particular need to be picky; and
2. the particulars of the original “bootstrap data” become irrelevant as soon as the bootstrapping phase is complete, no longer having any impact on further iterations of the product.
———
Now, mind you, I’m not saying that LLMs fit this mental model perfectly.
LLMs have a certain structure to their connections that, like AlphaZero, could be (and at this point, likely has been) fully Ship of Theseus-ed with a replacement dataset.
But LLMs also know specific things — the concrete associations that hang off the structure — and that data does need to come from somewhere; a single company has no hope of ever just “internally sourcing” an Encyclopedia Galactica worth of knowledge.
My argument is that this dataset can eventually be Ship-of-Theseus-ed as well — not by “internally sourced” data, but rather by ethically sourced data.
Consider one of those AI “character” chatbot websites — but one where they not only shove a click-wrap disclaimer in your face that your responses will be used for training, but in fact advertise that as the premise of the site. And in a way that will make people actually interested in giving their “explicit, enthusiastic consent” to participating in model training.
Can’t picture that? Imagine the site isn’t owned by a company trying to capture the data to build a proprietary model, but rather is owned by a co-op you implicitly join when you agree to participate, where your ownership stake in the resulting model / training dataset is proportionate to your contributed training data, and where you can then earn royalties from any ML companies that want to license the training dataset for use [probably along with many other such licensed training datasets] in training an “ethically-sourced” model on top of their Theseus-ed core.
Beside Sonnet impressing me, I like Anthropic because there's less of an "icky" factor compared to OpenAI or even Google. I don't know how much better Anthropic actually is, but I don't think I'm the only one who chooses based on my perception of the company's values and social responsibility.