Am I the only one who does that?
(EDIT: Same thing on Finder. cmd+C cmd+Del cmd+V)
Anyway, I love the design aesthetic of the site, and when people question existing paradigms. Will definitely be checking Ishmael out.
1,248 karma · joined May 6, 2009
Contact: <HN username> + "x" @ gmail
Am I the only one who does that?
(EDIT: Same thing on Finder. cmd+C cmd+Del cmd+V)
Anyway, I love the design aesthetic of the site, and when people question existing paradigms. Will definitely be checking Ishmael out.
Information hazard: https://en.wikipedia.org/wiki/Information_hazard
Babel: https://en.wikipedia.org/wiki/Tower_of_Babel
On the Calculation of Volume: https://en.wikipedia.org/wiki/On_the_Calculation_of_Volume
The revenge of NLP
The tool uses good old-fashioned regex/NLP—no LLMs—and rewrites the visible LLM Markdown without touching files on disk. I made it by analysing 10M+ words of past pi transcripts, doing frequency and pattern analysis, and iterating on rules to strip out the most egregious sloperisms. Now the circle is complete.
BEFORE
"Honestly, you're absolutely right—and that's a great question. Let me be clear: the fact that the parser works at all is actually quite remarkable. We utilize the tokenizer in order to handle the majority of edge cases, and due to the fact that it's recursive, it processes a large number of inputs. It's worth noting that this isn't really a bug—it's genuinely a deliberate design choice. In terms of raw throughput, the cache is significantly faster, and I think we should simply ship it.
That said, at the end of the day, not only is the design correct, but it is also fast. In other words, prior to refactoring, we should clearly delve into the nuanced, robust architecture. In conclusion, this is a testament to the seamless, intricate work the team has done."
AFTER
"That's a great question. That the parser works at all is remarkable. We use the tokenizer to handle most edge cases, and because it's recursive, it processes many inputs. This is a deliberate design choice. For raw throughput, the cache is faster, and we should ship it.
Not only is the design correct, but it is also fast. Before refactoring, we should delve into the nuanced, robust architecture. This is a testament to the seamless, intricate work the team has done."
# AI speech is an Infohazard
Apart from all its other possible boons and ills, one danger of AI is just that it is useful, so you use it. A lot.
In earlier days I would dive deeply into an author's work and start to think and write like them for a while. It was a heady feeling: slinging sonnets like Shakespeare—not at his level, but stylistically reminiscent—or tweaking turns like Twain.
Like all things, the effect lasts in relation to how long and how much you do it. The point is: our thinking is influenced by what we take in. Take more of a certain thing in, think more like that thing.
Now enter AI. My hand-crafted coding days are in their twilight months ("AI years"), and most of my software engineering is done through jaggedly capable agentic power tools. Instead of working directly with raw codestuff, I work with slop prose flecked with code sprinkles.
I read orders of magnitude more AI-speak—I call it "babble", or perhaps "Babel"—than human-written text. I can feel its genuinely honest points, clearly stated, slipping their banal tendrils into my thoughts and inner monologue.
Solutions? For me:
1. Be aware. "I notice that my thought stream is under assault."
2. Read stuff far from slop. Even a small dose of the good stuff can help inoculate. Recently I thought On the Calculation of Volume was something completely different.
3. Write stuff that is different. This post. Force the mind to synthesize thoughts in other ways.
4. debabel.py / debabel.js: a tool, and a pi extension, which filters common babble from visible LLM output. A lint for mind-killing prose.
It is not perfect, but it 80/20s nicely. I am willing to accept mildly awkward prose to avoid polluting my own internal distributions.
Details and example in the first comment. Tool available upon request.
In my case, I have a separate heartbeat check process (running on another machine) which ensures that the monitor is correctly working (no silent fails). I also wired up a SECOND esp32-box-3 as a receiver, and it will complain loudly if the transmitter one isn't sending (much like most normal baby monitors do). The monitor (web ui) has an option of directly listening to the raw non-gated audio, which I use every now and then to confirm what's going on. I also record the streams sometimes for algorithmic improvement.
My aim is not to replace human connection with machines, it's to allow the parents a bit more sanity so as to be better carers for our children. So far we've gained in sleep, piece of mind, and reduced stress. The last one is important - listening to your baby yell for 10 minutes, even if you know they're just annoyed because they don't want to sleep, can be really draining (especially for mom). The notifications allow us to keep tabs on things without the direct audio line to the limbic system.
I had an esp32-box-3 lying around from a lapsed "voice agent" project from a year or two ago. Had a baby. Baby moved to another room, sleep trained. Baby either: 1. wakes up a few times a night, babbles for a bit, goes back to sleep OR 2. baby wakes up and fusses for N (=10) minutes, at which point parents need to go in and settle (that's the sleep training routine we use).
In either case, we do NOT want to wake up every time the baby does. Baby can go back to sleep easily, we adults have a harder time. A few rounds with Claude and the esp32 is now our new baby monitor. It tracks cry/fuss duration and publishes an audio stream (via a web UI or direct with, say, VLC). The audio only comes through AFTER N minutes of fussing have elapsed. It also posts notifications (to ntfy) after 30s and N minutes. My log says baby often wakes up 1-2 times a night and resettles almost immediately. We only wake up if the audio comes through, after N (10) minutes.
Also during the day it's really handy to be notified when baby has woken up from her nap. Let's us be out of the house, or in a distant room, and still keep track of what's going on.
It's fun to keep improving and adding features to this. Never would have had the time/energy to get this done without a coding agent. I ordered a set of 10 more of the esp32-box-3s to give them out to my friends (well, some are for other projects... so much potential).
(EDIT: Yes, I know this isn't AI designing hardware, but even writing code for embedded off the shelf stuff feels like a huge new potential.)
EDIT: It's still quite fascinating seeing the kinds of things the models keep trying to do. It almost seems like when a human has slightly off with their nervous system. The conscious brain wants to do one thing, but for some reason the signals aren't getting to the hands correctly.
Should I read it as "immoral invasion"? Leaving aside whether it is or isn't, at least that framing makes sense, because you can meaningfully debate the morality of an invasion, but I can't understand how you could debate legality (except perhaps within the country's own internal framework of laws, like if a president declared a war without going through the proper legal channels).
It's the usual public health balancing act of help vs harm.
I always thought a simple over-the-counter supplement (NAC) being the cure for an overdose was so cool. It's a pretty cool substance in a lot of ways, and this is a great spur to myself to research it more thoroughly.
If anyone knows of a way to develop this... the code is on Github, and I have a roadmap in mind, but as we all know there's a huge gap between hacky prototype and "works smoothly for other users".
It's essentially a poor man's hacked up DynamicLand - projector, camera, live agent. There are so many things you could do if you had a strong working baseline for this. My kids used it to create stories, learn how to draw various things, and watching safe videos they could hold in their hand.
There's something weirdly compelling and delightfully physical about holding a piece of paper that shows a live rocket launch, with the flames streaming down the page. It could also project targeted pieces of text, such as inline homework advice, or graphs next to data. It doesn't take long to imagine any other number of fun use cases, and it feels a lot more freeing and inspiring than keeping everything bound to a screen.
Github - https://github.com/Pugio/Orly (hacky minimal prototype that did the thing)
Video Pitch - https://youtu.be/-9l1x7GnmxU (filmed an hour before the deadline on an old phone with no sleep)
I see you have support for vanilla js and svelte, but it's unclear whether you can get all the same functionality if you don't use React. Is React the only first class citizen in this stack?
> The very act of resisting feeds what you resist and makes it less fragile to future resistance.
At least along certain dimensions. I don't think the labs themselves are antifragile. Obviously we all know the labs are training on everything (so write/act the way you want future AIs to perceive you), but I hadn't really focused on how they're absorbing the innovation that they stimulate. There's probably a biological analog...
Well there are many, and I quote this AI response here for its chilling parallels:
> Parasitic castrators and host manipulators do something related. Some parasites redirect a host’s resources away from reproduction and into body maintenance or altered tissue states that benefit the parasite. A classic example is parasites that make hosts effectively become growth/support machines for the parasite. It is not always “stimulate more tissue, then eat it,” but it is “stimulate more usable host productivity, then exploit it.” (ChatGPT 5.4 Thinking. Emphasis mine.)
Super cool, of course.
It's AI narrated, but at this point if I heard Zvi's actual voice I think I would be confused. It's really well done, and uses different voices for each new person being quoted. It also has really good narrated image descriptions.
Zvi's articles are literally exhaustively long,l - before I was able to listen to them I got tired trying to read the whole thing. Now it's my favorite way to keep up with AI.
I can't see how any of these other countries could even approach the level of capability of the big three providers. I can imagine only a handful of countries who could even theoretically put enough resources towards reaching the SOTA frontier. Sure, even a model of capability level ~2024 has plenty of valid use cases today, but I'm concerned that people will just go with the big three because what they offer is still so so much better.
Not trying to discourage efforts like these, but is there really a good case for working on them? Or perhaps there's a state/national case, but it's harder for me to see a real business case.
The questions are: "Help with what, precisely?" and "How much money versus how much value (/principles) compromise?"