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Anthropic's Claude is said to improve on ChatGPT, but still has limitations

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Re: Anthropic's Claude is said to improve on ChatGPT, but still has limitations

#51

Post by coolspot »

turmeric_root wrote: post #40
wwwtyro wrote: post #3

Is there any reason to believe that the first open source chat GPT clone won't consume most mindshare, a la stable diffusion?

on top of the hardware requirements ($10s of thousands of GPUs are needed for something a language model as big as gpt-3) there's also a lot of work involved in RLHF models like chatgpt. you need to pay people to write and review thousands/tens of thousands of responses for training. see 'methods' here: https://openai.com/blog/chatgpt/

LAION’s Open Assistant trying to address that with gamified crowdsourcing.

https://github.com/LAION-AI/Open-Assistant

Re: Anthropic's Claude is said to improve on ChatGPT, but still has limitations

#52

Post by powersnail »

RangerScience wrote: post #44
powersnail wrote: post #23

Earlier quoted context omitted.

What the three laws of robotics didn't predict, is how much our current AI is pure heuristics, and so it doesn't quite have the ability to strictly follow rules, or even interpret rules in an unambiguous manner. Hard-coded behaviors cannot express the abstract ideas in those laws, while the ML part cannot be relied upon to accurately behave.

Um, actually! Asimov's theorized robots ("positronic brains") used potential-based computing (interestingly, AFAIK they predate digital computers; there's actually a few scenes in some stories where characters start using computers as New Shiny Thing) - so I'd actually argue that the original Three Laws are specifically for heuristic-based computing. The three laws aren't really "strict", nor are they what we'd commo…

I'm more thinking of the much more basic kind of bugs.

AI might fail to follow rule 1, simply by misidentifying a human as something else, or misidentifying what is harmful. Like how a Tesla can crash into an obstacle, because it failed to recognize that there is an obstacle.

This isn't a criticism of Asimov, of course. I think we simply haven't solved many basic problems that he probably regarded as "surely by the time robots need rules to follow, these aren't going to be issues".

> I'd probably stick one system on at the "front" to add/modify/create/interpret prompts in a way that adds the three laws, and then stick one at the end to measure (and then filter on) how well the output adheres to them.

I bet that we are going to get some sort of end-to-end simulated robot QA system. Imagine pushing your code to Github, and in a few minutes, Travis CI emails you, "28/1000 tests failed. 32 cases of bodily harm against human were reported." What a world to live in!

Re: Anthropic's Claude is said to improve on ChatGPT, but still has limitations

#53

Post by kurthr »

jibe wrote: post #17
troad wrote: post #13

Earlier quoted context omitted.

If it was a bona fide investment and you are without notice of any wrongdoing - no, I’d say you’re not. Presumably your nefarious investor holds some kind of ownership interest that can be sold by their trustees/liquidators to raise funds. If you are able to do so, it seems like a nice thing to try to help source money to help the people caught out, including by assisting in realising any ownership stake, but that’s…

I’d say you’re not If the investment was made with stolen funds they can be clawed back.

I guess the local grocery store better look out.

If he paid any taxes, can those be clawed back from the IRS too?

Re: Anthropic's Claude is said to improve on ChatGPT, but still has limitations

#54

Post by RangerScience »

powersnail wrote: post #52
RangerScience wrote: post #44

Earlier quoted context omitted.

Um, actually! Asimov's theorized robots ("positronic brains") used potential-based computing (interestingly, AFAIK they predate digital computers; there's actually a few scenes in some stories where characters start using computers as New Shiny Thing) - so I'd actually argue that the original Three Laws are specifically for heuristic-based computing. The three laws aren't really "strict", nor are they what we'd commo…

I'm more thinking of the much more basic kind of bugs. AI might fail to follow rule 1, simply by misidentifying a human as something else, or misidentifying what is harmful. Like how a Tesla can crash into an obstacle, because it failed to recognize that there is an obstacle. This isn't a criticism of Asimov, of course. I think we simply haven't solved many basic problems that he probably regarded as "surely by the t…

> CI

That'd be pretty cool, actually! A little... maybe ironic? How many stories are there about "they didn't stop to ask if they should, only if they could", and then... outsourcing that check to an AI system. Like I love it, but also, sus.

> bugs

Yep! I think positronic brains would notionally use a heuristics system ("human detector says 89%"), and AFAIK so do our AI systems. That said, your larger point still stands: what happens when such a system either fails, or is mis-calibrated, or is calibrated in a sus way?

(such as facial recognition, at first, not working on BIPOC faces... because the devs used themselves as the test subjects and weren't BIPOC)

I'm almost certain there's at least one story by Asimov on this issue; I know I've read other SciFi on this issue, although I think it's much more common to have the AIs act "better than the humans" rather than vice versa. Something like: "The rules you programmed in say Group X are humans even tho you don't treat them that way". Usually (I think?) when it's "Group X aren't humans by the programmed rules" it's apocalyptical because no-one / almost no-one fits.

I think you could probably write a cute short story about robots anthropomorphizing a lot of things in order to catch all the odd human edge-cases ("not all humans have a face").

Re: Anthropic's Claude is said to improve on ChatGPT, but still has limitations

#55

Post by troydavis »

mouse_ wrote: post #10
airstrike wrote: post #6

In a strange twist of events... their massive Series B round was led by SBF "The [$580M] Series B follows the company raising $124 million in a Series A round in 2021. The Series B round was led by Sam Bankman-Fried, CEO of FTX. The round also included participation from Caroline Ellison, Jim McClave, Nishad Singh, Jaan Tallinn, and the Center for Emerging Risk Research (CERR)." https://www.anthropic.com/news/announc…

When someone pays you with stolen funds, aren't you (morally, if not legally) obliged to pay it back to the victims?

Based on https://news.ycombinator.com/item?id=31209431#31210335, it's probably already been spent on compute to train this model. As the CEO commented in that thread, "It is in fact our intent to primarily spend the funds on compute."

Re: Anthropic's Claude is said to improve on ChatGPT, but still has limitations

#56

Post by dredmorbius »

troad wrote: post #13
mouse_ wrote: post #10

Earlier quoted context omitted.

When someone pays you with stolen funds, aren't you (morally, if not legally) obliged to pay it back to the victims?

If it was a bona fide investment and you are without notice of any wrongdoing - no, I’d say you’re not. Presumably your nefarious investor holds some kind of ownership interest that can be sold by their trustees/liquidators to raise funds. If you are able to do so, it seems like a nice thing to try to help source money to help the people caught out, including by assisting in realising any ownership stake, but that’s…

NB/OT: Late response on an earlier thread:

https://news.ycombinator.com/item?id=34182022>

Re: Anthropic's Claude is said to improve on ChatGPT, but still has limitations

#57

Post by Roark66 »

antimatter15 wrote: post #32
wwwtyro wrote: post #3

Is there any reason to believe that the first open source chat GPT clone won't consume most mindshare, a la stable diffusion?

There are already open source LLMs with comparable parameter counts (Facebook's OPT-175B, BLOOM), but you'll need ~10x A100 GPUs to run them (which would cost ~$100K+). I suspect a big part of why stable diffusion managed to consume so much mindshare is that it can run on ordinary consumer hardware. On that point, I would be excited about an open-source RETRO ( https://arxiv.org/pdf/2112.04426.pdf ) model with compar…

One can in theory run even 175B bloom with just a modern multicore CPU, 32gb of RAM and 2TB of nvme storage. There is a library called accelerate witch with some slight modifications allows one to run in cpu/storage only mode models that don't fit in memory. Of course it takes a looong time to do inference, but one can at least have a taste.

The biggest bloom I personally have run on cpu only in this fashion is 7B. It requires 4x7B of RAM plus some. On my hardware it tends to use all 32GB RAM and about ~4GB of storage during inference. At the moment I believe there is still a limitation of the smallest layer fitting in memory at once. This is why I haven't tried bigger bloom, but I believe there are ways to overcome it. Once this problem is resolved one should be able to use the same tech to use GPUs with less vram (like my 2070 with 8GB) for parts of larger models.

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