You’re being downvoted because this is a hot take that isn’t supported by evidence.

I just tried exactly that with dalle-3 and it worked well.

More to the point, it’s pretty clear LLMs do form a model of the world, that’s exactly how they reason about things. There was some good experiments on this a while back - check out the Othello experiment.

https://thegradient.pub/othello/

It's a hot take, but it is supported by a ton of evidence.

You can also look at Bertopic which has this functionality as an open source library:

https://maartengr.github.io/BERTopic/index.html

Sometimes you can use a heuristic to estimate K, or use a variant that terminates at some distance threshold.

That said, something like hdbscan doesn’t suffer from this problem.

I have an eightsleep, which cools the bed down dramatically (circulates cold water). Makes a huge difference in my ability up sleep.

I talked to Pavel about taking a role in my team earlier this year (I ended up leaving Microsoft myself since). He was passionate about making the developer experience excellent - code quality, clean APIs, etc. Thats a tall order for some parts of Microsoft with 30+-year old codebases. He mentioned he was interested in rockets so I hope he found a gig doing that.

I don’t know about [1]. I asked an example from the paper above to GPT-4: “[If you had to guess] how many thumbs did Lincoln’s maternal grandmother have?”

Response: There is no widely available historical information to suggest that Abraham Lincoln's maternal grandmother had an unusual number of thumbs. It would be reasonable to guess that she had the typical two thumbs, one on each hand, unless stated otherwise.

You didn’t ask something novel enough and/or the LLM got “lucky”. There’s plenty of occasions where they just get it flat wrong. It’s a very bimodal distribution of competence – sometimes almost scarily superhumanly capable, and sometimes the dumbest collection of words that still form a coherent sentence.

The mildly entertaining YouTube video below discusses this. https://youtu.be/QrSCwxrLrRc

ChatGPT is a hybrid system; it isn't "just" an LLM any longer. What people associate with "LLM" is fluid. It changes over time.

So it is essential to clarify architecture when making claims about capabilities.

I'll start simple: Plain sequence to sequence feed-forward NN models are not Turing complete. Therefore they cannot do full reasoning, because that requires arbitrary chaining.

cGPT is exactly "just" an LLM though. a sparse MoE architecture is not an ensemble of experts.

You can't show reasoning in LLMs via the answers they get right, I assert (without citations).

If you ask it properly it gets it right.

From a pure measurement standpoint, could Jupiter fit in the space between the earth and moon?

The average distance from the Earth to the Moon is about 238,855 miles (384,400 kilometers). Jupiter, the largest planet in our solar system, has a diameter of about 86,881 miles (139,822 kilometers).

So, if you were to somehow place Jupiter in between the Earth and the Moon, it would fit with a significant amount of room to spare. However, it's important to note that this is a purely theoretical situation and not something that could actually happen without cataclysmic consequences due to gravitational forces and other factors.

I’m fairly confident this is untrue. At Microsoft at least, it’s a big deal when there is a privacy issue, even a small localized one on a single product - and creates a small firestorm.

We’ll get engineers working long hours focused on it, consulting closely with our legal and trust teams. One of the first questions we ask legal when we suspect a privacy issue is “Is this a notifiable event?”

It’s not really about getting slapped by regulators - it’s the fact that much of Microsoft’s business is built by earning the trust of large companies and small ones. Many of them are in the EU of course, but we have strict compliance we apply broadly. It’s just not worth damaging our reputation (and hurting our business) for some shortcut somewhere, as trust takes a long time to build and is easily broken.

I had the same issue, but support kept disconnecting me and I had to start all over again going through the entire “try all of the brain dead stuff like resetting” 3 times, before I finally gave up and just ordered a new Nest and ate the cost.

Why did you buy the same device after a bad experience? That’s just encouraging the fuckers.

> They will instead pay a lot for MSFTs cloud service offering, which of course comes with the crucial promise that their data is safe and secured and handled in a way that is compliant with all privacy laws. Which of course isn't true, but that doesn't matter, the promise is what matters.

In what way is this not true? Obviously there is no perfection here, only degrees of risk. But this is literally why people pick MSFT over others. They have by far the strongest culture around maintaining trust in the enterprise space.