Surely this logic doesn't apply if we're to believe that "code is cheap" now :p
1,024 karma · joined May 29, 2013
The idea that agent harnesses should primarily have their functionality dictated by plaintext commands feels like a copout around programming in some actually useful, semi-opinionated functionality (not to mention that it makes capability-discoverability basically impossible). For example, Claude Code has three modes: plan, ask about edits, and auto-accept edits. I always start with a plan and then I end up with multiple tasks. I'd like to auto-accept edits for a step at a time and the only way to do that reliably is to ask CC to do that, but it's not reliable—sometimes it just continues to go into the next step. If this were programmed explicitly into CC rather than relying on agent obedience, we could ditch the nondeterminism and just have a hook on task completion that toggles auto-complete back to "off."
[0]: https://github.com/daturkel/pyto/blob/master/AYTO_S8.ipynb [1]: https://blogs.sas.com/content/operations/2018/08/14/are-you-...
The linked post is a very thorough treatment of AYTO and a great read. I really like the "guess who" bit on how to maximize the value of guesses. It's a shame the participants aren't allowed to have pen and paper—it makes optimization a lot trickier! I'm impressed they do as well as they do.
[0]: https://danturkel.com/2023/01/25/math-code-are-you-the-one.h...
Years of experience have proven that you can get quite far with pure collaborative filtering—no user features, no content features. It's a very hard baseline to beat. A similar principle applies to language modeling: from word2vec to transformers, language models never rely on any additional information about what a token "means," only how the tokens relate to each other.
One thing I'm wondering about is if it's possible (or necessary?) to use Keras in concert with Pytorch Lightning. In some ways, Lightning evolved to be "Keras for Pytorch," so what is the path forward in a world where both exist as options for Pytorch users—do they interoperate or are they competitors/alternatives to each other?
[1]: https://github.com/spotify/voyager [2]: https://engineering.atspotify.com/2023/10/introducing-voyage...
It's worse than just about any "real" image compression algorithm, but it works! (Plus you get lossless compression if your image is low-rank.)
https://danturkel.com/2022/12/27/advent-of-code-2022.html
(Maybe @dang can fix the submission link)
And the slightly less measurable: eat better and exercise more. I'm getting old enough that I should stop putting this off.
Also, pattern matching is coming to python in 3.10. You can read about it here: https://www.python.org/dev/peps/pep-0634/
I doubt that most offices would benefit from teaching their employees that instead of just hitting control-B to bold some text, they should now do \textbf{foo}, or that quotes should now be types ``like this''. If you need the huge array of features (which is typically only the case in the context of academic publishing), then it's worth making the investment to learn. But for 99% of corporate documents, Word likely can do what you need with much less pain.
I would argue that originalism doesn't really exist in practice in the context of the Supreme Court. Interpreting the constitution is always an active process where the interpreter injects some of themself into the the interpretation. The difference is that those who interpret the Constitution as a "living document" are up-front about this process, while originalists deny that it is happening.
And then I'd argue that this half-baked notion of Internet Originalism isn't really a sensible metaphor. The author argues that the way we use and build the internet should be in line within the framework that the web is a democratizing tool, and I agree with that (simply because I share those values, though I'd debate how much they're truly enshrined in the concept of the internet itself).
But the author seems to care more about not Internet Originalism but...Twitter Originalism. That a private company has to abide by a set of values that it (purportedly) supported at its inception.
> That is why a “living internet” interpretation is so dangerous. These companies are driven by profits and politics, not principle. [...] > The alternative is “internet originalism” — no censorship. If social media companies returned to their original roles, there would be no slippery slope of political bias or opportunism [...]
Yes—companies are driven my profits (and, to the extent that they're at risk of regulation, politics)! That's, like, their whole thing. Regardless of the potential greater good of these companies returning to their supposed "original roles," they're supposed to be forced to do so even when it means losing money and failing to self-regulate? It seems perfectly reasonable that a company which seeks to provide a mass communication platform might realize that the rules which worked at first need to be adjusted at scale. I don't see that as some massive betrayal.
No doubt there will be (and has been) some over-correction as Twitter navigates how to quell the use of its platform for spreading misinformation and hate speech. They've historically not been great at it, and they'll probably get to an ~ok~ solution eventually. And if they don't? A new private venture can show up to offer something better (as has happened several times).
Feel free to contribute. I'm open to suggestions on what to include as well as how to organize and present it. I hope it's a useful tool for people hoping to read up on the research behind various ML ideas.
Nonetheless, here are some I subscribe to:
Big, by Matt Stoller (about monopolies): https://mattstoller.substack.com/
Margins (about business and tech): https://themargins.substack.com/
Flow State (music): https://flowstate.substack.com/
Normcore tech (tech, data science): https://vicki.substack.com/
The Passion Economy (business): https://passion.substack.com/