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OpenAI researcher announced GPT-5 math breakthrough that never happened

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Re: OpenAI researcher announced GPT-5 math breakthrough that never happened

#171

Post by ramenbytes »

andrewflnr wrote: post #130
crazygringo wrote: post #119

Earlier quoted context omitted.

In my experience doing literature super-deep-dives, it hallucinates sources about 50% of the time. (For higher-level literature surveys, it's maybe 5%.) Of the other 50% that are real, it's often ~evenly split into sources I'm familiar with and sources I'm not. So it's hugely useful in surfacing papers that I may very well never have found otherwise using e.g. Google Scholar. It's particularly useful in finding relev…

So, the exact stuff Google used to be good at.

The exact stuff I now use Kagi for. Finding obscure relevant PDFs that Google didn't is literally one of the things that made me switch.

Re: OpenAI researcher announced GPT-5 math breakthrough that never happened

#172

Post by ummonk »

OtherShrezzing wrote: post #126
gpjt wrote: post #68

To be fair to the OpenAI team, if read in context the situation is at worst ambiguous. The deleted tweet that the article is about said "GPT-5 just found solutions to 10 (!) previously unsolved Erdös problems, and made progress on 11 others. These have all been open for decades." If it had been posted stand-alone then I would certainly agree that it was misleading, but it was not. It was a quote-tweet of this: https:…

Am I correct in thinking this is the 2nd such fumble by a major lab? DeepMind released their “matrix multiplication better than SOTA” paper a few months back, which suggested Gemini had uncovered a new way to optimally multiply two matrices in fewer steps than previously known. Then immediately after their announcement, mathematicians pointed out that their newly discovered SOTA had been in the literature for 30-40 y…

We also had the GPT-5 presentation which featured both incorrect bar charts (likely AI generated) and an incorrect explanation of lift.

Re: OpenAI researcher announced GPT-5 math breakthrough that never happened

#173

Post by ummonk »

derektank wrote: post #168
malfist wrote: post #165

Earlier quoted context omitted.

> because the risk of the models being abused or trafficked is virtually zero. That's not really true. Look at one if the more common uses for AI porn: taking a photo of someone and making them nude. Deepfake porn exists and it does harm

The harms associated with someone creating a deep fake of you are real but they're pretty insignificant compared to the harms associated with being sex trafficked or being exposed to an STI or being unable to find traditional employment after working in the industry.

Would you support installing public spy cams in everyone's bedrooms so as to end the demand for human trafficking in porn?

Re: OpenAI researcher announced GPT-5 math breakthrough that never happened

#174

Post by HarHarVeryFunny »

derektank wrote: post #169
HarHarVeryFunny wrote: post #123

Earlier quoted context omitted.

I'm pretty sure that if they didn't deliberately chose to train on sex chat/stories, etc, then the LLM wouldn't be any good at it. The model isn't getting this capability by training on WikiPedia or Reddit. So, it's not a matter of them not being able to do a good job of preventing the model from doing it, therefore giving up and instead encouraging it to do it (which anyways makes no sense), but rather them having c…

>The model isn't getting this capability by training on WikiPedia or Reddit I don't know about the former, but the latter absolutely has sexually explicit material that could make the model more likely to generate erotic stories, flirty chats, etc.

OK, maybe bad example, but it would be easy to create a classifier to identify stuff like that and omit it from the training data if they wanted to, and now that they are going to be selling this I'd assume they are explicitly seeking out and/or paying for creation of training material of this type.

Re: OpenAI researcher announced GPT-5 math breakthrough that never happened

#175

Post by Timsky »

happy_dog1 wrote: post #155
Timsky wrote: post #86

> GPT-5 is proving useful as a literature review assistant No, it does not. It only produces a highly convincing counterfeit. I am honestly happy for people who are satisfied with its output: life is way easier for them than for me. Obviously, the machine discriminates me personally. When I spend hours in the library looking for some engineering-related math made in the 70s-80s, as a last resort measure, I can try to…

I wonder whether for a lot of the search & literature review-type use-cases where people are trying to use GPT-5 and similar we'd honestly be much better off with a really powerful semantic search engine? Any time you ask a chatbot to summarize the literature for you or answer your question, there's a risk it will hallucinate and give you an unreliable answer. Using LLM-generated embeddings for documents to retrieve…

I think you have a very good point here: a semantic search would be the best option for such a search. The items would have unique identifiers so the language variations can be avoided. But unfortunately, I am not aware of any of these kinds of publicly available projects, except DBpedia and some biology-oriented ontologies that would massively analyze scientific reports.

Currently, I am applying RDF/OWL to describe some factual information and contradictions in the scientific literature. On an amateur level. Thus I do it mostly manually. The GPT-discourse somehow brings up not only the human-related perception problems, such as cognitive biases, but also truly philosophical questions of epistemology that should be resolved beforehand. LLM developers cannot solve this because it is not under their control. They can only choose what to learn from. For instance, when we consider a scientific text, it is not an absolute truth but rather a carefully verified and reviewed opinion that is based on the previous authorized opinions and subject to change in the future. So the same author may have various opinions over time. More recent opinions are not necessarily more "truthful" ones. Now imagine a corresponding RDF triple (subject-predicate-object tuple) that describes that. Pretty heavy thing, and no NLTK can decide for us what the truth is and what is not.

Re: OpenAI researcher announced GPT-5 math breakthrough that never happened

#176

Post by derektank »

ummonk wrote: post #173
derektank wrote: post #168

Earlier quoted context omitted.

The harms associated with someone creating a deep fake of you are real but they're pretty insignificant compared to the harms associated with being sex trafficked or being exposed to an STI or being unable to find traditional employment after working in the industry.

Would you support installing public spy cams in everyone's bedrooms so as to end the demand for human trafficking in porn?

No? And I didn't suggest deepfakes should be legal.

I was just pointing out that when you're talking about the scale of harm caused by the existing sex industry compared to the scale of harm caused by AI generated pornographic imagery, one far outweighs the other.

Re: OpenAI researcher announced GPT-5 math breakthrough that never happened

#177

Post by ogogmad »

OtherShrezzing wrote: post #126
gpjt wrote: post #68

To be fair to the OpenAI team, if read in context the situation is at worst ambiguous. The deleted tweet that the article is about said "GPT-5 just found solutions to 10 (!) previously unsolved Erdös problems, and made progress on 11 others. These have all been open for decades." If it had been posted stand-alone then I would certainly agree that it was misleading, but it was not. It was a quote-tweet of this: https:…

Am I correct in thinking this is the 2nd such fumble by a major lab? DeepMind released their “matrix multiplication better than SOTA” paper a few months back, which suggested Gemini had uncovered a new way to optimally multiply two matrices in fewer steps than previously known. Then immediately after their announcement, mathematicians pointed out that their newly discovered SOTA had been in the literature for 30-40 y…

No, your claim about matrix multiplication is false. Google's new algorithm can be applied recursively to 4x4 block matrices (over the field of complex numbers). This results in an asymptotically faster algorithm for nxn matrix multiplication than Strassen's. Earlier results on 4x4 matrices by Winograd and others did not extend to block matrices..

Google's result has more recently been generalised: https://arxiv.org/abs/2506.13242

Re: OpenAI researcher announced GPT-5 math breakthrough that never happened

#178

Post by Timsky »

kianN wrote: post #140
Timsky wrote: post #86

> GPT-5 is proving useful as a literature review assistant No, it does not. It only produces a highly convincing counterfeit. I am honestly happy for people who are satisfied with its output: life is way easier for them than for me. Obviously, the machine discriminates me personally. When I spend hours in the library looking for some engineering-related math made in the 70s-80s, as a last resort measure, I can try to…

If you’re interested in a literature review tool, I built a public one for some friends in grad school that uses hierarchical mixture models to organize bulk searches and citation networks. Example: https://platform.sturdystatistics.com/deepdive?search_type=e...

Thank you for sharing! I like your dendrogram-like circular graphs! They are way more intuitive. That could be a nice companion for a bibliometrix/biblioshiny library for bibliometric analysis https://www.bibliometrix.org/. I tried "Deep Dive" with my own request, and ... it unfortunately stops at the end of "Organizing results". Maybe I should try again later.

Re: OpenAI researcher announced GPT-5 math breakthrough that never happened

#179

Post by malshe »

Timsky wrote: post #86

> GPT-5 is proving useful as a literature review assistant No, it does not. It only produces a highly convincing counterfeit. I am honestly happy for people who are satisfied with its output: life is way easier for them than for me. Obviously, the machine discriminates me personally. When I spend hours in the library looking for some engineering-related math made in the 70s-80s, as a last resort measure, I can try to…

I think its scope is narrower than a lit review assistant. I use it mainly for finding papers that I or my RAs might have missed in our lit review.

I have a recent example where it helped me locate a highly relevant paper for my research. It was from an obscure journal and wouldn't show up in the first few pages of Google Scholar search. The paper was real and recently published.

However, using LLMs for doing lit review has been fraught with peril. LLMs often misinterpret the research findings or extrapolate them to make incorrect inferences.

Re: OpenAI researcher announced GPT-5 math breakthrough that never happened

#180

Post by kianN »

Timsky wrote: post #178
kianN wrote: post #140

Earlier quoted context omitted.

If you’re interested in a literature review tool, I built a public one for some friends in grad school that uses hierarchical mixture models to organize bulk searches and citation networks. Example: https://platform.sturdystatistics.com/deepdive?search_type=e...

Thank you for sharing! I like your dendrogram-like circular graphs! They are way more intuitive. That could be a nice companion for a bibliometrix/biblioshiny library for bibliometric analysis https://www.bibliometrix.org/ . I tried "Deep Dive" with my own request, and ... it unfortunately stops at the end of "Organizing results". Maybe I should try again later.

Haha that’s embarrassing! The progress bars are an estimate. If a paper has a lot of citations, it may take a bit longer than the duration of the bars but it will hopefully finish relatively soon!

Edit: Got home and checked the error logs. There was a very long search query with no results. Bug on my end to not return an error in that case.

If you were hoping to use the citation network, it needs the url as input rather than the title.

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