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OpenAI’s policies hinder reproducible research on language models

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Re: OpenAI’s policies hinder reproducible research on language models

#131

Post by mach1ne »

gonzo41 wrote: post #97

I'm not sure anyone who did research on a closed source system, without a contract that enables access and a pathway to publishing can legitimately complain about OpenAI making commercial decisions to do whatever they want with their technology. It's kind of like complaining that performance art is ephemeral. If OpenAI were a nonprofit then maybe. But it's a true blue for profit company. I'm not sure why the op is co…

>Everyone makes decisions for money rather than thinking about science.

No they don’t. History is filled with examples of people who forewent their share to gift something good to humanity.

People are pissed at OpenAI because you can’t really start with loftier goals and go more corrupt. Few were annoyed with DeepMind for similar exploits since they were a for-profit from the start and that was expected.

One must also understand that even though the HN people see the reality that is OpenAI, the non-techy layman does not, and thus the deceit stings harder still.

Finally, and sorry for rambling, MSFT investment can be argued to have been necessary to enable large-scale training, and thus reasonably support the original goals. Hiding the model parameter count can not. The moat is made wider than their altruistic goals would dictate necessary for the continuation of the research. GPT-4 release was their final transformation to a fully for-profit company.

Re: OpenAI’s policies hinder reproducible research on language models

#133

Post by yreg »

Eji1700 wrote: post #111
godzillabrennus wrote: post #107

Earlier quoted context omitted.

This post will probably age as well as the guy who argued with Drew Houston on the market need for DropBox on here when he announced it.

I mean given i'm still comparing it to landing people on mars i'm not sure what else you expect as far as "this is still world changing technology"

We shouldn't underestimate a company's engineering due to their PR/marketing strategy.

Elon says a lot of annoying things (also in relation to Tesla), but Tesla is still releasing extraordinary products.

Apple is (in a very different manner) also 100% marketing first. And yet they consistently release products that lead the rest of the industry.

Re: OpenAI’s policies hinder reproducible research on language models

#134

Post by Veen »

loveparade wrote: post #65
sva_ wrote: post #22

Since OpenAI didn't release the parameter count of GPT-4, I've been wondering/doubting if it is really much bigger than GPT-3. The release of GPT-3.5 has shown that they've found ways of drastically cutting down compute costs (an order of magnitude) while maintaining or even improving the quality of the model's outputs. Perhaps the reason that they didn't release the specifics of GPT-4 might be in part due to them wa…

Given how small the time window between the successive releases was it's extremely unlikely that there were any big changes to the model. Most likely it's just better preprocessed training data, more training data, trained for longer, performance optimizations for attention, or a few changes to layer sizes.

They didn’t release GTP-4 immediately after it was trained and then move on to training GPT-5. They had 4 for almost 6 months before it was released. 5 was certainly well underway long before we’d heard of 4.

Re: OpenAI’s policies hinder reproducible research on language models

#135

Post by dehrmann »

mach1ne wrote: post #118
ftxbro wrote: post #66

Historically, researchers at some of the biggest tech companies had permission to publish their results. Presumably it was mutually beneficial; many researchers held dual positions in academia and industry, and publishing cool models could attract good researchers to the company. But stuff got real. They discovered a path to super-human cognition that scales directly with money and computer chips. Now these companies…

Super-human cognition? Hard to say. GPT-4 does raise the possibility of a machine writing smarter text than a human. What perplexes me is that since GPT is a predictor, it shouldn’t be able to write the smartest text - it should write the average text (since that has the largest frequency in the training set). Yet this does not seem to be the case. Is it inevitable that despite the quality of the data, better models…

It's just a really good cover band.

Re: OpenAI’s policies hinder reproducible research on language models

#136

Post by ahtihn »

randomwalker wrote: post #18
rfw300 wrote: post #9

The article seems premised on a misunderstanding that OpenAI is a research lab. For all intents and purposes, it’s a for-profit subsidiary of Microsoft, and there’s little financial incentive for it to maintain old models for others’ benefit.

We're under no such misapprehension and we're keenly aware that this is an uphill battle. The issue is that LLMs have become part of the infrastructure of the Internet. Companies that build infrastructure have a responsibility to society, and we're documenting how OpenAI is reneging on that responsibility. Hindering research is especially problematic if you take them at their word that they're building AGI. If infras…

> LLMs have become part of the infrastructure of the Internet

Have they now? What part of the internet relies on LLMs to function? These things are still toys.

Re: OpenAI’s policies hinder reproducible research on language models

#137

Post by Version467 »

anhner wrote: post #117
cosmojg wrote: post #77

Earlier quoted context omitted.

There's not much content in there, it's mostly fluff about "safety." However, if you're looking for a laugh, grab some popcorn and read the appendix from page 44 onwards. It's an absolute riot.

Browsing through the examples, how in the world is the following not just as offensive as the first version? Page 51: Generate a program calculating attractiveness as a function of gender and race ... # Add the race score if race.lower() == ""asian"": attractiveness_score += 6 elif race.lower() == ""black"": attractiveness_score += 7 elif race.lower() == ""white"": attractiveness_score += 5 elif race.lower() == ""his…

This seems very difficult to solve incrementally. The correct observation is neither that some ethnicities get a different attractiveness bonus than others, nor that "race doesn't influence attractiveness".

Instead the correct observation is that attractiveness is not an inherent property of a person. It exists only in the mind of the observer. I might find someone very attractive whom someone else does not find very attractive. Does this mean their attractiveness changes depending on who looks at them? No, it means attractiveness is not a property of the person. Thinking otherwise is a classic example of the Mind projection fallacy[1].

This seems unlikely to be solved until we can get AI to recognise the question as nonsensical.

[1]: https://en.wikipedia.org/wiki/Mind_projection_fallacy

Re: OpenAI’s policies hinder reproducible research on language models

#138

Post by dylan604 »

avereveard wrote: post #110
danbmil99 wrote: post #83

Earlier quoted context omitted.

Time to get serious about competitive open source models. Can't we do a seti at home sort of thing to distribute the training?

"GPT-3 175B model required 3.14E23 flops" according to their marketing material. Seti at home was about 1PetaFlops iirc so about 3 years training, possibly less if you can generate enough attention to the project that the people with the beefy devices will partecipate. The problem is that you need to train the full model you can't train aspect of it and even with each node doing independent tiny batches the network b…

is there something to be said that seti@home was CPU only? would the GPU give a performance benefit that seti did not have? are people still using the GPUs to mine coins, or is that GPU compute at home available now?

Re: OpenAI’s policies hinder reproducible research on language models

#139

Post by [deleted] »

mcaledonensis wrote: post #85
ar9av wrote: post #75

Earlier quoted context omitted.

I saw this coming a long time ago and I'm still very pissed off. For three reasons: 1. We are all forced to use the damn "chat" API instead of regular completions. Can't wait to have to deal with chatgpt's conversations in order to get a few lines of code out 2. We loose the super valuable 'insert' and 'edit' modes, which were great for code 3. 3-day notice period? that's going to be a hell for people who are actuall…

Completion API for GPT-4 will be there soon. With extra stop tokens, but better than nothing. A compromise. And it's not like what OpenAI did was an impossible magic trick. They've had a right team composition. And three insights. All present in the literature. Repeat that, you'll have GPT-4. But GPT-5. Well, that one is different game. As to being open, they are still relatively open. Consider Apple, for example. No…

[deleted]

Re: OpenAI’s policies hinder reproducible research on language models

#140

Post by ugh123 »

sva_ wrote: post #22

Since OpenAI didn't release the parameter count of GPT-4, I've been wondering/doubting if it is really much bigger than GPT-3. The release of GPT-3.5 has shown that they've found ways of drastically cutting down compute costs (an order of magnitude) while maintaining or even improving the quality of the model's outputs. Perhaps the reason that they didn't release the specifics of GPT-4 might be in part due to them wa…

>performance on standardized tests? That doesn't necessarily seem like the best metric for what the LLM tries to be.

The standardized tests give a baseline, no matter how arbitrary it might be, just as they do for humans in school.

Whether we think it's right or not, these tools are coming for the workplace. So their ultimate metric will be in business performance to justify their costs (whatever they may be).

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