kherud (u/kherud) - Readit News

kherud commented on What does Palantir actually do? wired.com/story/palantir-... · Posted by u/mudil

This one?

https://news.ycombinator.com/item?id=44785708

kherud · 11 days ago

It's probably "Reflections on Palantir" https://news.ycombinator.com/item?id=41855006

kherud commented on Preventing Flash of Incomplete Markdown when streaming AI responses engineering.streak.com/p/... · Posted by u/biot

kherud · 3 months ago

Is there a general solution to this problem? I assume you can only start buffering tokens once you see a construct, for which there are continuations, that once completed, would lead to the previous text being rendered differently. Of course you don't want to keep buffering for too long, since this would defeat the purpose of streaming. And you never know if the potential construct will actually be generated. Also, the solution probably has to be more context sensitive. For example, within code blocks, you'll never want to render links for []() constructs.

EDIT: One library I found is https://github.com/thetarnav/streaming-markdown which seems to combine incremental parsing with optimistic rendering, which works good enough in practice, I guess.

kherud commented on The Legend of Holy Sword: An Immersive Experience for Concentration Enhancement arxiv.org/abs/2408.16782... · Posted by u/PaulHoule

bigcat12345678 · a year ago

bene gesserit vibe hit hard

Now there is a path forward to be able to focus on a single cell in my body. LoL

kherud · a year ago

That was my association as well! Dune even uses similar vocabulary. For example someone mentioned "pranayama" in this thread, which sounds a lot like Dune's "Prana-bindu". Really makes me wonder about Frank Herbert's experiences about all of this.

kherud commented on Learning to Reason with LLMs openai.com/index/learning... · Posted by u/fofoz

kherud · a year ago

Aren't LLMs much more limited on the amount of output tokens than input tokens? For example, GPT-4o seems to support only up to 16 K output tokens. I'm not completely sure what the reason is, but I wonder how that interacts with Chain-of-Thought reasoning.

kherud commented on Features I'd like to see in future IDEs mordenstar.com/blog/how-t... · Posted by u/vunderba

crooked-v · a year ago

What I'd really like is an IDE that functions on objects of code and not text files, and diffs and merges thar similarly operate on the syntax tree of the code and not on whether there's an extra newline or not.

Like, code formatting, that's just an implementation detail. Why can't there be a thing to let two people edit the same repo with different formatting preferences without it causing merge conflicts?

kherud · a year ago

Maybe you're already aware of it, but there is difftastic [0], which is a syntax aware diff tool that can also be used with git. Its understanding of syntax is based on treesitter, so it works for most languages. Although I haven't tried, I think most IDEs should also be able to use it.

[0] https://difftastic.wilfred.me.uk/

kherud commented on A new type of neural network is more interpretable spectrum.ieee.org/kan-neu... · Posted by u/pseudolus

thomasahle · a year ago

KANs can be modeled as just another activation architecture in normal MLPs, which is of course not surprising, since they are very flexible. I made a chart of different types of architectures here: https://x.com/thomasahle/status/1796902311765434694

Curiously KANs are not very efficient when implemented with normal matrix multiplications in Pytorch, say. But with a custom cuda kernel, or using torch.compile they can be very fast: https://x.com/thomasahle/status/1798408687981297844

kherud · a year ago

Interesting, thanks for sharing! Do you have an explanation or idea why compilation slows some architectures down?

kherud commented on Can reading make you happier? (2015) newyorker.com/culture/cul... · Posted by u/kawera

verisimi · a year ago

Surely the answer is the level of emotional engagement you have? Eg dissatisfaction, excitement, engagement with authority, etc.

kherud · a year ago

I think it's more about invested work vs. reward.

Mindless browsing is one of the lowest work activities, but the influx of information is highly rewarding for the brain. That's why it's so addicting. Programming and OS installation are more work, but there is direct progress. Filing taxes is just work, but at again it's a very direct way to feel productive. All of these activities are immediately rewarding.

Reading on the other hand requires a lot of concentration, without much immediate reward. And I think the ratio here is highly subjective for most people.

kherud commented on Data Fetching for Single-Page Apps martinfowler.com/articles... · Posted by u/fagnerbrack

branko_d · a year ago

The original promise of React was:

UI = f(state)

The problems come when you modify state in response to rendering the UI. This seems deceptively natural (and in fact seems encouraged by on-line tutorials), but leads to "spaghetti fetching" when composing components together - it creates a "feedback loop" that modifies state just because some component happens to mount, which can then modify state further, then cause further mounting/fetching etc...

A better approach is to treat fetching as an explicit state change. If user clicks on a button, you do the fetch and modify the state. If that causes some components to be mounted - so be it, but does not cascade any further.

kherud · a year ago

Let's say you want to show a modal, which fetches some data and modifies the state. Based on this, new children are rendered which again fetch state. The problem of "spaghetti fetching" becomes worse the more levels of recursive fetching there are. If I understand you correctly, you argue for fetching all data upfront, and then rendering the modal and all its children all at once. This way you ensure "UI = f(state)" by removing side effects from "f".

On the other hand, I can also see some drawbacks:

  1. This goes against the idea of fetching data close to where it's used, basically promoting modularization.
  2. From the POV of the children, you have to backtrack where their data are coming from.
  3. If components always use the same data, you have to duplicate fetching their data everywhere you want to use them.
  4. You can't partially show children, but have to wait for everyone to have their data before rendering them.

I feel like there are trade-offs to be made here.

kherud commented on How Does GPT-4o Encode Images? oranlooney.com/post/gpt-c... · Posted by u/olooney

rvnx · a year ago

Author claims that the most likely is that there is Tesseract running behind ChatGPT-4v/o.

There is no way that this is Tesseract.

-> Tesseract accuracy is very low, it can barely do OCR on printed documents.

kherud · a year ago

Shouldn't this theory be testable? The response time for an image of the same size should remain constant (assuming a generated response of constant size). You could then try to put an increasing amount of text inside of the image. If this text is fed to the LLM using OCR, the total amount of tokens grows. You should then be able to observe an increase in response time.