codechicago277
codechicago277 on Hacker News
Well probably better to look to Picard than a literal Nazi…
“Square of the lines of code”
Sounds exponential
This isn’t one of those times.
They should really consider going electric
I used the digits of pi, transposing and changing the order, and got 14% on the original game. Professional poker players will use external sources of randomness to make sure they’re perfectly balancing their positions and not exploitable.
Posted by
codechicago277 on Wednesday October 07, 2026 @11:02AM
from the niallferguson.substack.com dept.
Solving people problems efficiently and effectively.
I’ve been buying dvds and surfacing a lot of the content to Jellyfin and Tailscale, it’s a lot easier than it used to be and they even have smart TV apps on some of the platforms. Don’t even have to pirate to get use out of it.
Posted by
codechicago277 on Saturday September 19, 2026 @10:38AM
from the wsj.com dept.
It’s difficult if not impossible to know where to look for edge cases or performance problems without understanding the code.
100% AI on Pangram.
Would be great if we could automatically tag posts that contain a certain level of AI content. If the author couldn’t be bothered to write it in their own words, I can’t be bothered to read it, and at best will have an AI summarize it instead.
Pangram flags this post as 100% AI
Posted by
codechicago277 on Friday September 11, 2026 @09:25AM
from the wsj.com dept.
Getting 11% AI on Pangram, which isn’t bad tbh.
They were already heavily limited and essentially useless by then, definitely not enough access to sync your profile to another network.
Few details but glad to see the project will continue. Given how much crucial information is posted exclusively to X, having an alternative frontend is important.
Interesting that they were inspired by Invidious (alternative YouTube frontend). That’s another project that could use some love. Hopefully AI coding tools can do some good and make it easier for these projects to find ways into the walled gardens and work around the counter measures.
Waiting for the day all the social networks allow api access and become usable again. Maybe we can call it “agent first” to help move things along.
Posted by
codechicago277 on Thursday September 03, 2026 @03:17PM
from the nolanlawson.com dept.
I need to take a step back.
Posted by
codechicago277 on Monday August 31, 2026 @12:11PM
from the wsj.com dept.
Posted by
codechicago277 on Thursday August 27, 2026 @10:35AM
from the nolanlawson.com dept.
You already guessed a word that had a “T” in it, and the game confirmed that “T” is not in the word. So you can’t guess another word with a “T”.
I’m not a logician either but believe this is what Tarski’s definition of truth solves for. In order to make a statement about the statement itself, you have to introduce a new meta language. Then a statement in the meta language is only true if the underlying statement is true.
Much more rigorous explanation:
https://plato.stanford.edu/entries/tarski-truth/
It’s sad to see people in the thread conflate capitalist greed with the “Protestant work ethic.” Despite the popularity of prosperity gospel teaching in the US, Jesus’ actual teachings clearly condemn greed and oppression of those who have less. A work ethic is still valuable, because goods have to be produced, but the reason we can’t solve worldwide poverty by just writing a check is that oppressive leaders at some point in the chain will use that money to enrich themselves, or they will take it from those who can’t defend themselves.
This isn’t to say that the purpose of Christianity is to fix these social problems, but it’s easy to forget how central generosity and compassion are to the Christian message. “Money Cult” by Chris Lehmann is a good exploration of how American Christianity corrupts these truths.
Yeah, this response is pure propaganda, say one thing in the headline and the opposite in the body.
Anthropic does not support a ban on open models, except for any models that aren’t closed.
Even with an LLM you still have to kick it off, which is mental effort.
In this framing, clean coding abstractions gain a purpose beyond helping humans understand the code and actually help enforce that the end result is reasonably bug free. Building code out of understandable pieces can ensure that the whole thing is reasonably understandable.
While the article is focused on “low level” bugs, the key insight is that human understanding has limits, and bugs show up when the human is overconfident in their understanding, and unwilling to verify the code by running it on a sample of test cases. This does seem to help explain why “high level” bugs occur, where the reality somehow doesn’t match the assumption. Maybe a dependency is on the wrong version, a global variable isn’t initialized in certain cases, etc.
In a world of LLMs producing code that isn’t always understandable to humans, it does raise the question of how to enforce that AI code is bug free, and maybe forcing coding agents to stick to human abstractions is the missing piece.
Becomes a problem when the next version of Mac OS changes the api, and you have to dig up the code, install dependencies, recompile and fix it. Meanwhile potentially breaking something else.