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Meet “Claude”: Anthropic’s rival to ChatGPT

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Re: Meet “Claude”: Anthropic’s rival to ChatGPT

#71

Semi offtopic, but for some time I have been dreaming of training chatbot to communicate in cuneiform or hieroglyphs to bring some old languages back alive. Could it be possible, using old tablets as training data?

That's basically the problem of unsupervised machine translation using mainly monolingual corpora. It means giving a machine learning model tons of text in two languages and let it figure out how to do translation between some old language X and e.g. english. There's no need to feed it a parallel corpora, i.e. examples of sentences in X languages and their translations in english.

In some situations, this seemingly impossible task is doable and can yield good results. Researchers sometimes need to kickstart their models by giving them a mapping between words of the two languages (for english french: "cat" "chat", "book" "livre" and so on). That's just simple vocabulary. While it's technically possible to learn this mapping from scratch, it's too difficult as for now.

Do you know of the Encoder-Decoder architecture? You feed something (image, text) to the encoder which compresses it to a very dense representation, and the decoder try to use the resulting dense vector to do useful stuff with it. The input could a sentence in english, the encoder then encodes it and the decoder tries to use the output of the encoder to generate the same sentence but in french. These architectures are useful because directly working with "plaintext" to learn how to do translation is way too expensive. I mean, that's one of the reasons.

What the encoder does is mapping a "sparse" representation of a sentence (plaintext) to a dense representation in a well-structured space (think of word2vec which managed to find that "king" + "woman" = "queen"). This space is called the "latent space". Some say it extracts the "meaning" of the sentence. To be more precise, it learns to extract enough information from the input and present it to the decoder in such a way that the decoder becomes able to solve a given task (machine translation, text summarizing etc).

One of the main assumption of the unsupervised models using monolingual data only is that both languages can be mapped to the same latent space. In other words, we assume that every sentences/texts in english has its exact french (or whatever) equivalent, that the resulting translated sentences contain exactly the same information/meaning as the original ones.

That's quite the dubious assumption. There's obviously some ideas, some stuff that can be expressed in some languages but can't be exactly expressed in some others. While theoretically unsound, however, these models were able to achieve pretty damn good results in the last couple of years.

Re: Meet “Claude”: Anthropic’s rival to ChatGPT

#72

Imagine an android connected to the vast network of information (ChatGPT-like). The android could generate various responses in real-time, just by vocalizing the approriate text. It might be clunky at first, but it's a good starting base to improve upon. The android could, for example, store common and everyday responses in it's RAM, making it semi-capable of autonomous speech. Then, it could use that information to…

Yeah I am alrwady to able to Imagine, the android welcoming me and suggesting me what I should buy with its sweet words, based on my past interactions with it.

also sounds like a world where items are subscription based.

If you desire a luxury colour like blue; you have pay monthly credits otherwise your clothes items are downgraded to brown.

Re: Meet “Claude”: Anthropic’s rival to ChatGPT

#73

Earlier quoted context omitted.

IIRC the ChatGPT paper actually says the verbosity is an unintended effect of the human raters preferring longer/more detailed answers. Long answers from GPT are unusually obnoxious because of a way the decoder works; it emits words with a much more constant rate of perplexity than human text does (this is how GPT-vs-human detectors work) which makes it sound stuffy and monotone.

There is a paper?

The grandparent is probably talking about the InstructGPT paper? But I don't remember seeing a preference for longer responses in that paper.

Re: Meet “Claude”: Anthropic’s rival to ChatGPT

#74
post #64

Earlier quoted context omitted.

I am not saying that all languages have a shared structure, but from the Bayesian variational learning perspective, as long as the new data shares some structure with what the model has previously encountered, the prior training data contributes to understanding the new information i.e. few-shot . This is in the information theoretic sense, I am not stating any theories about the underlying semantics or grammar. I kn…

Is there any reason to assume any shared structure for unrelated languages though? Written language is just an encoding for information. There is a good candidate for a test. Someone will probably already work on it. Minoan as written in Linear A has only survived in a few thousand tokens and despite thousands of man years of effort, natural intelligence has made virtually no progress in understanding it. That's stil…

There is no reason to, as stated before, it is however a necessary assumption. It is also possible that the assumption is entirely wrong, and the LLM generates a plausible explanation to their language that we cannot falsify. If the shared structure hypothesis is incorrect, then it is no different from dealing with an alien language. (Note we can also feed in related information like where it was found, what the nearby pottery shards at the excavation site are etc. I am lumping all of these under the "shared structure" banner of the LLM's model of humanity/human languages)

Re: Meet “Claude”: Anthropic’s rival to ChatGPT

#75
post #61

Earlier quoted context omitted.

Assuming all human languages have a common shared semantic meaning in latent space (I am flipping cause and effect here, but our purposes it doesn't really matter), and assuming that human languages largely follow the same pattern (this assumption is based on the fact that we can trace the roots of modern languages back to the Phoenician script), it is reasonable to assume that we can fine-tune a self supervised mode…

I think you may be on to something here. For example ChatGPT is perfectly capable of "understanding" and speaking Polish while the amount of training data in this language definitely wasn't a lot. It is not as eloquent as in English, but still for a model that has not been trained for translation tasks, this is very cool.

Its Lithuanian is awful, I'd expect that any language further removed from that which the majority of it's training is in would be worse without a significant punt of data in that language. Its possible having that could affect it's English speaking capability, but that's just speculation on my part.

Re: Meet “Claude”: Anthropic’s rival to ChatGPT

#76

Earlier quoted context omitted.

IIRC the ChatGPT paper actually says the verbosity is an unintended effect of the human raters preferring longer/more detailed answers. Long answers from GPT are unusually obnoxious because of a way the decoder works; it emits words with a much more constant rate of perplexity than human text does (this is how GPT-vs-human detectors work) which makes it sound stuffy and monotone.

There is a paper?

[deleted]

Re: Meet “Claude”: Anthropic’s rival to ChatGPT

#77

Hello HN — I’m the coauthor of this post. You may remember me as that guy who spent most of 2022 posting GPT-3 screenshots to Twitter, most famously prompt injection and “You are GPT-3”. Happy to answer any questions about Claude that I can.

Thanks for being here to answer questions.

One possibly difficult topic others also may be interested in, after reading Claude's responses in the article, is: what does "harmless" mean?

For example, if asked to help the user understand how to do something "bad", will it give the answer if they claim they want this information in order to help them write a screenplay, versus if they seem have an intent to do it?

And how is "bad" decided? We can recognise through everyday personal interactions that one persons "bad" is another persons "good", and across country-boundaries even the legality of these distinctions can be radically different.

One counterargument to these constraints is that anyone can already use the internet to access all of the same information the model was trained on, unencumbered by whatever intent they may or may not have.

As such, what are the rationale for making these attempts at the somewhat invasively-impossible task of determining user intent?

This has never been employed with search engines before, which have lead to a rich explosion of innovation and education, so why attempt it now, in what could be argued is ultimately an iteration of search engine technology?

Re: Meet “Claude”: Anthropic’s rival to ChatGPT

#78

Definitely humor is in the eye of the beholder. I find the Seinfeld jokes by ChatGPT wittier and funnier than the run-of-the-mill comments created by Claude. I don't know how well they are in character, and there's a clear repetition problem (which Claude somewhat also exhibits), but I find the format from ChatGPT more exaggerated, as expected from a comedy routine.

[deleted]

Re: Meet “Claude”: Anthropic’s rival to ChatGPT

#79

They say Claude is "more verbose", and claim this is a positive. I disagree. My biggest criticism of ChatGPT is that its answers are extraordinarily long and waffly. It sometimes reminds me of a scam artist trying to bamboozle me with words. I would much prefer short, concise, precise answers.

ChatGPT can be very confidently wrong in few words too. It's a very flexible system that way.

Re: Meet “Claude”: Anthropic’s rival to ChatGPT

#80

> That Claude seems to have a detailed understanding of what it is, who its creators are, and what ethical principles guided its design is one of its more impressive features. This doesn't show a detailed understanding of what it is, it's just a canned/trained response. I don't see why that would be impressive. When I receive such a response from an automated helpdesk, I don't think "Wow, this AI has a great understa…

I said “seems to”, which I think is a fair description. In everyday life, even a canned message is sensibly said to be aware/unaware of a particular fact without a “seems to” qualifier, but I added one to be clear I’m not asserting it has human-like thinking. Here’s Claude replying to your comment with more detail: > You make a fair point that my responses about myself are generated by a trained model and are not a t…

These chat bots are too chatty.
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