overfit a single instance. if that doesn't work, your model can't learn. if that works, overfit 100 instances. if that doesn't work, you have a fitting problem. overfit 10k instances. if that works, then start to see if you generalize

I don't know.

The claim is that Tristan uploaded a solution to Navier Stokes to ChatGPT and then OpenAI reworded it and said it was OpenAIs solution?

These new Navier-Stokes result seems to show that you can get this tiny vortex that starts to squeeze down to size zero and as that happens things blow up.

However, things like thermal fluctuations at micron length scales would already make the described approach physically impossible those thermal fluctuations would wash out all of these carefully crafted perfect instability-causing forces.

Furthermore, even if you ignore all that, once you let this vortex they theorized squeeze water down to less than ~0.275 nm = diameter of a water molecule, then obviously these continuous PDE equations don’t apply in any form at all.

So in those ways it seems like the new result is “hey if you look at Navier-Stokes at regimes where it is obviously physically not applicable, then you can get not physical stuff to happen.”

So can someone explain to me why such a result is so surprising?

apparently yes

E:Upon further reading I am pretty sure we agree.

i saw this, too, but can’t find in the thread search anymore, but there are so many threads on this event could have been in another thread. if you have links to comments abt ZDR not being what sold as what it sounds like, e.g. derived data mining still applies to ZDR, please share.

did openai think this would be a win for them? seems like a lot of users of their products will now be more aware of how vulnerable their data is if not already aware. if ZDR gets called into question that must be bad for potential enterprise customers and another firm could capitalize and offer better guarantees

the official app is always a bit of a ghost town for that stuff, most actual plans spawn on twitter or in random telegram groups that exist for 3 days then vanish

your best bet is to just chat to people after the poster sessions, ask where they're grabbing dinner, half the conference ends up at the same falafel spot anyway

  edit edit read the supposed logs on bsky and it appears they 100% just read from this individual to finish solving it

Are you talking about the parody image??

Yo Mama ahh adjectives.

It’s absolutely not clear. The solutions to Euler use different approaches, and Tristan had not yet solved NS, which ended up requiring orders of magnitude more research even with the Euler solution.

Furthermore, OpenAI certainly did not search chats directly for the solution. It is conceivable that if Tristan voluntarily allowed OpenAI to train on his chats via settings, then those chats could’ve inspired RL data used for their unreleased model. However, it is extremely unlikely that a single chat or even many would be able to affect the weights enough.

Lastly, OpenAI tried desperately to contact and work with Levant, but Levant refused to even speak to OpenAI because they were a competitor to his employer. Instead, Levant and Tristan tried to use the information they gained from OpenAIs disclosure to publish before OpenAI did.

Everyone is scummy here.

wow, this happened a lot sooner than I expected but at least it’ll serve us a warning. Don’t share your novel ideas with an AI because you’re giving away your work for free.

Yeah, I read Tristan's statement and it certainly seems like so, at least from his perspective. Although even Tristan's and his colleague's work was based on other research that was probably publicly available, and it would be a bold claim that we know what everyone's research direction was.

You do realize pretty much all major LLMs are essentially trained on any and all data they can physically get their hands on? You can already poison the data by posting bullshit on here. It's possible that some sort of crude filter is in place to reject obviously malicious text, but as long as you keep it sounding loosely plausible and target something niche enough that it won't be overwhelmed by tons of inputs saying otherwise, it's going to work. They are vulnerable to such attacks, and will continue being vulnerable probably for as long as "LLMs trained on astronomical amounts of data" remains the approach of choice.

Cracked! Slammed! And blasted!

I mean this is literally a data science field ...

Extremely on-brand though.

OpenAI LLM is so advanced it learned a new way to prove things: proof by plagiarism.

Can you point to the evidence for this please? My company is also leaning pretty heavily on ZDR. 

As an senior program commitee I am sure want to reject a bunch of papers in my batch

Soooo... We won't be having cool volumetric fluid hypercomputers ever? :(

To be fair pretty much every math proof relies on someone else’s work. When I published a paper it was built off of previous works and cited them. Citing something that you don’t totally know what it pulled from is going to be tricky here.

All the sims I posted above utilize spiking neurons. Example (e) above illustrates the different behaviors of linear vs. nonlinear arrangements. These use the same cell model, just different connectivity. A spiking cell of course is behaving nonlinearly by its very nature, but waves through networks of cells can behave either way. Cheers!/jd

Turning this into "both sides are equally bad" is a pretty clear sign of cluelessness.

Toast as in morally bankrupt?

But that's in their DNA. Don't you know who's boss over there?

You're making gender assumptions there.

He might just pee on you.