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dwagnerkc

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The Self-Tuning Piano [video]

youtube.com
2 points·by dwagnerkc·geçen ay·6 comments

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dwagnerkc
·24 gün önce·discuss
Predicted Antwren is a new favorite. How interesting.
dwagnerkc
·geçen ay·discuss
Well, I don't think face palm emojis are support on HN, but certainly this would be the time for one, Ha!
dwagnerkc
·geçen ay·discuss
Same. I found this because I got my piano tuned yesterday and it bothers me it can't sound that wonderful every day - bothered me even more that it did not seem to exist as a commercial project or DIY solution. I'm in KC so might try to connect, maybe even get it for my Kawai!
dwagnerkc
·geçen ay·discuss
Supposed to be able to install on any piano, and remove without any sort of permanent damage or anything, can see on this page https://dgdevices.com/gallery
dwagnerkc
·3 ay önce·discuss
Well never needed an unlocked bootloader specifically, but have found Swappa to be solid place to buy used gear more generally - purchased 4 used iPhones and 1 Macbook Air so far.
dwagnerkc
·geçen yıl·discuss
they came for the speed but stayed for the API

This is exactly how I would describe my experience. When I talk to others about polars now I usually quickly mention its fast up front, but then mostly talk about the API, its composability, small surface area, etc. are really what make it great to work with. Having these same semantics backed by eager execution, query optimized lazy API, streaming engine, GPU engine, and now distributed auto-magical ephemeral boxes in the sky engine just make it that much better of a tool.
dwagnerkc
·geçen yıl·discuss
If you want to try it out. Can lazily load from HF and apply filtering this way.

  df = (
    pl.scan_parquet('hf://datasets/minimaxir/mtg-embeddings/mtg_embeddings.parquet')
    .filter(
        pl.col("type").str.contains("Sorcery"),
        pl.col("manaCost").str.contains("B"),
    )
    .collect()
)

Polars is awesome to use, would highly recommend. Single node it is excellent at saturating CPUs, if you need to distribute the work put it in a Ray Actor with some POLARS_MAX_THREADS applied depending on how much it saturates a single node.
dwagnerkc
·2 yıl önce·discuss
Them: We need this iOS app. The government of XYZ wants it.

Me (2 months later): Here it is.

Them:
dwagnerkc
·2 yıl önce·discuss
I have spent probably over 100 hours now fiddling with data using polars and it is just so enjoyable to use. The interface is the real magic here.

This was captured well in their company announcement blogpost [0]:

> A strict, consistent and composable API. Polars gives you the hangover up front and fails fast, making it very suitable for writing correct data pipelines.

[0] https://pola.rs/posts/company-announcement/
dwagnerkc
·2 yıl önce·discuss
That post also very helpfully links to another paper they published alongside the OLMo paper just on the dataset.

Dolma: an Open Corpus of Three Trillion Tokens for Language Model Pretraining Research

https://arxiv.org/abs/2402.00159
dwagnerkc
·3 yıl önce·discuss
404 on resume FYI
dwagnerkc
·4 yıl önce·discuss
I would add Prefix + z for temporarily maximizing/minimizing pane to the full windows is very useful.

Config doesn't have to be very complicated, I've used this for a while.

  set -g mouse on                # allow mouse
  set -g history-limit 999999999 # unlimited history
  set -sg escape-time 0          # vim esc response faster
dwagnerkc
·4 yıl önce·discuss
Try using mamba (https://github.com/mamba-org/mamba)

We ran into many unsolvable or 30m+ solvable envs with conda that mamba handled quickly.

The underlying solver can be used with conda directly as well, but I have not done that (https://www.anaconda.com/blog/a-faster-conda-for-a-growing-c...)