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coherentpony

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1 points·by coherentpony·há 3 meses·0 comments

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coherentpony
·há 20 dias·discuss
My employer is counting token usage, so explaining my project between tokens isn’t necessarily a bad thing. I am clearly a more productive engineer because of it \end{sarcasm}
coherentpony
·há 24 dias·discuss
Uber’s situation was different, though. The reason Uber were bleeding money is because they purposefully made all their rides cheap to undercut the taxi businesses. People used Uber because it was cheaper than renting a taxi.

Now you can’t really find taxis anywhere, even at airports it’s a lot more difficult than it used to be.

Once the taxi business was disrupted enough, Uber’s pricing skyrocketed and customers had basically no other options for competition on pricing.

OpenAI basically created a new market. There is no AI chatbot incumbent to disrupt and swallow.
coherentpony
·há 28 dias·discuss
If your comment is intended to convey sympathy on these workers, I think you're going to have a difficult time finding folks that align with you.

If your comment is intended to remind folks that these workers can simply resign of their own free will to find meaningful and dignified work at a different employer, I think you're going to have an easy time finding folks that align with you.
coherentpony
·há 2 meses·discuss
> The task is to place four black queens and one black bishop on the chessboard so that there is no square not under their attack

> In other words, after arranging the five black pieces, it must be impossible to place the white king anywhere without it being in checkmate.

These two sentences mean very different things in the normal rules of chess. And if you replace the word “checkmate” with the word “check” in the second sentence it still doesn’t mean the same thing as the first sentence.

The first sentence implies that all the pieces must be defended.

Edit: Eh, I guess it depends on how you view the word “attack” since all the pieces are the same colour.
coherentpony
·há 2 meses·discuss
You can saturate the entire power budget on pretty much all GPUs just by moving data in and out of HBM. There is no compute needed at all to do this, and bandwidth bound workloads are extremely common in the scientific computing space.
coherentpony
·há 2 meses·discuss
Is it? Nobody else can really build on their work.
coherentpony
·há 4 meses·discuss
I am somewhat cynically waiting for the AI community to rediscover the last half a century of linear algebra and optimisation techniques.

At some point someone will realise that backpropagation and adjoint solves are the same thing.
coherentpony
·há 4 meses·discuss
It doesn’t work per-song. Songs have multiple chords, some even with alterations. If you tune an E so that it is perfectly a major third above C, then that E won’t be a perfect fifth above an A note. The Am chord has the notes A, C and E, so Am has notes that all belong to C major.

Additionally, some songs even change keys, which makes “per-song” not enough of a constraint.
coherentpony
·há 5 meses·discuss
I’m trying to make sense of this question.

GEMMs are dense O(N^3) work operations that have roughly the same access pattern and data reuse properties across all matrices. Of course, I’m simplifying things a lot here; tall-skinny and short-fat patterns are much harder to get performance out of but the spirit of the approach is the same as big square matrices.

Sparse LU solves have a different character. There is nowhere near O(N^3) work. You typically expect something closer to O(N^2) but getting performance out of these operations is notoriously difficult because it depends a lot on the sparsity pattern of the linear system. Making matters worse is that you may commonly have a sparse A that factorises to dense L and/or U matrices.
coherentpony
·há 6 meses·discuss
Ah yes I forgot about that. Thanks for the correction.
coherentpony
·há 6 meses·discuss
> Personally I have a bunch of machines dedicated to gaming in my house (https://lanparty.house)

Woah, that is extremely cool. Very nice work, sir.
coherentpony
·há 6 meses·discuss
The circumference of Earth at the equator is about 40,000 km and the speed of light is about 300,000 km/s. The appropriate division results in about 0.13 s.

That seems to track. The vast majority of requests won’t go half way around the Earth, so maybe halving that time at 0.06 seems like a reasonable target.
coherentpony
·há 7 meses·discuss
Ok that helps. Thank you.
coherentpony
·há 7 meses·discuss
I don’t understand what the visualisation screenshot in the README is trying to communicate to me.
coherentpony
·há 8 meses·discuss
It’s a natural observation, but it doesn’t address the floating point problem. I think the author should have said “fast or would accumulate floating point error” instead of “fast and would accumulate floating point error”.

You could compute in the reverse direction, starting from 1/n instead of starting from 1, this would produce a stable floating point sum but this method is slow.

Edit: Of course, for very large n, 1/n becomes unrepresentable in floating point.
coherentpony
·há 8 meses·discuss
What a wonderful comment. It was educational and friendly without holding my hand too much.

Thank you.
coherentpony
·há 9 meses·discuss
You originally called someone a redditor making a cringe joke for highlighting a serious historical problem. It wasn't clear to me that it was a joke at all, but my impression is that it seemed clear to you that it was a joke.

What if that person has also lived in Texas for 30 years? And what if they had a family member that died during that power grid failure in 2021? I personally would find it quite difficult to communicate to them the nuance of a local problem and a state-wide problem when the end result is the same: no power.

In the future, you might consider approaching an interaction online with more balanced judgement.

Edit: Actually, looking back at the original comment, it's not even clear they're talking about the Texas power outage in 2021. All they said was "Hope they have ample backup power." Seems like a reasonable thing to hope for what might be critical infrastructure.
coherentpony
·há 9 meses·discuss
> Texas loses power one time for a week and the redditors will never let it go. Wild how this is still a cringe joke so many years later.

Texas had the most number of power outages between 2019 and 2023 [1].

It wasn't one time. And it's not a joke. Infrastructure weatherization is a very real overlooked (and expensive) investment that still has not taken place.

[1]: https://www.congress.gov/118/meeting/house/116952/documents/...
coherentpony
·há 10 meses·discuss
Not totally orthogonal, and quite interesting: https://arxiv.org/abs/1410.6723
coherentpony
·há 10 meses·discuss
> For example, ChatGPT is even more aligned with Japan than with the US

I have no expertise in this field.

Is it actually even more aligned? Or is it simply aligned with the elements of Japanese culture and/or media that are exported to the West?