MurphyA/hacker-news huggingface dataset:
by gh02t | 2025-07-14 17:46:13+00:00
I did try tuning the watchdog thresholds/gain too but never had much luck. I read a few places that there might have been problems with some of the early AS3935 chips (but could never find too much info) and I know there were problems with some of the breakout boards on Aliexpress having the wrong capacitors on the board (which was another thing I tested/fixed). The one thing I never tried was all my boards are fairly old so they might have whatever the original hardware flaw is and maybe newer ones work as intended.

I've been mighty tempted to try again with a newer one as I really want to build a compact portable lightning sensor linked to Meshtastic but I dread going through the whole ordeal again.
by mrinterweb | 2025-07-14 17:46:33+00:00
One of the reasons microservice architecture originally became popular was to break apart monolithic applications. In many cases, I bet a big driver was a lack of separation of concerns, and a more modular design was desired. There are many ways to put up walls in software to help make software more modular and self-contained. Rails engines are a good way to make more a rails app more modular. The number of times I've seen microservices created for the purpose of modularity (not scaling concerns), and the complexity that has brought has really soured me on microservices.
by khelavastr | 2025-07-14 17:46:37+00:00
The study clearly shows increased incidence of withdrawal symptoms. But, in a semantic game, the symptoms aren't defined as "antidepressant discontinuation".

Freddie got tricked.

The abstract explains, "Individuals who discontinued antidepressants experienced more symptoms compared to those discontinuing placebo or continuing an antidepressant, but the mean number of symptoms was below the cutoff for clinically important discontinuation syndrome."
by jerf | 2025-07-14 17:47:08+00:00
"I'm guessing yours doesn't support IPv6 because most fiber providers don't."

Yeah, what's up with that? I just got switched on to fiber and the CGNAT for IPv4 doesn't shock me much, but what's with the no IPv6 in 2025?

I know enough to deal with it, but what's the deal? Is there something systematic here?
by woodruffw | 2025-07-14 17:47:27+00:00
I don’t know anything about the original author, but I do know what function coloring is. It’s a way to describe effects. An effect is a function color.

> That's all fine and good in theory, but in practice it makes no difference, at the user level, or at the compiler level

Every example given so far shows Io’s virality, so I don’t know how you can assert how it doesn’t make a difference. The entire point of the design appears (reasonably) to be to introduce a token object that conveys an effect, rather than requiring a runtime to intermediate that effect.

Again, none of this is bad. Effect typing is cool. But it is, by definition, a way to color a function.

(Maybe the confusion here stems from the fact that languages like Go appear to have it “both ways” without coloring. Go is able to do that because it has an intrusive runtime that intermediates asynchronous events. Zig can’t do the same thing without making the same compromises as Go vis a vis FFI performance and ABI compatibility.)
by burntsushi | 2025-07-14 17:47:53+00:00
It's not clear to me that you're accounting for the difference in size that results from static vs dynamic linking. For example, if I build `ugrep` with `./build.sh --enable-static --without-brotli --without-lzma --without-zstd --without-lz4 --without-bzlib`, then I get a `ugrep` binary that is 4.5MB. (I added all of those `--without-*` flags because I couldn't get the build to work otherwise.) If I add `--without-pcre2`, I get a 3.9MB binary.

ripgrep is only a little bigger here when you do an apples to apples comparison. To get a static build without PCRE2, run `cargo build --profile release-lto --target x86_64-unknown-linux-musl`. That gets me a 4.6MB `rg` binary. Running `PCRE2_SYS_STATIC=1 cargo build --profile release-lto --target x86_64-unknown-linux-musl --features pcre2` gets a fully static binary with PCRE2 at a 5.4MB `rg` binary.

Popping up a level, a fair criticism is that it is difficult to get ripgrep to dynamically link most of its dependencies. You can make it dynamically link libc and PCRE2 (that's just `cargo build --profile release-lto --features pcre2`) and get a 4.1MB binary, but getting it to dynamically link all of its Rust crate dependencies is an unsupported build configuration for ripgrep. But I don't know how much tools like ugrep or GNU grep rely on that level of granular dynamic linking anyway. GNU grep doesn't seem to do so on my system (only dynamically linking with libc and PCRE2).

Additionally, the difference in binary size may be at least partially attributable to a difference in Unicode support:

$ echo ♥ | rg '\p{Emoji}' ♥ $ echo ♥ | ugrep-7.5.0 '\p{Emoji}' ugrep: error: error at position 6 (?m)\p{Emoji} \___invalid character class
by bilbo0s | 2025-07-14 17:48:12+00:00
Sure.

My point is that so is the percentage of males in any sortition cohort.

Therefore, a consistent female census of 10% or less in all sortition cohorts, would be as unlikely as a consistent male census of 10% or less in all sortition cohorts.

In other words, having one sortition cohort result in 10% males would not be suspicious. Having every sortition cohort result in 10% males would be suspicious in the extreme. So much so that we should start looking for whoever is "putting their finger on the scale" so to speak.
by vkou | 2025-07-14 17:48:22+00:00
That's due to politics being a team sport, and everyone, including the voters, understanding that it's a team sport.

Getting your team control of a branch of government is way more important than having a 'good' rep in your district, because if you don't, they won't have any ability to do anything for it anyways.

If you couldn't get someone you wanted in the primaries, you just have to hold your nose, close your eyes, lie back, and vote for whomever made it through.

Whether this results in long term problems is a bit of an academic question, given that every election in the past decade is one where you either get to vote for the status quo, or an insane cult of personality.
by 542354234235 | 2025-07-14 17:48:54+00:00
Thats not how the balance of power between the State and Federal level work. The anti-commandeering doctrine prevents the federal government from directly compelling states to implement or enforce federal law. It has been ruled on time and time again, from 1842 when Justice Joseph Story affirmed it [1] to Justice Samuel Alito in 2018 [2]. Having to get voluntary buy-in from States for Federally passed laws is a key check on Federal power.

[1] “The clause relating to fugitive slaves is found in the national Constitution, and not in that of any State. It might well be deemed an unconstitutional exercise of the power of interpretation to insist that the States are bound to provide means to carry into effect the duties of the National Government nowhere delegated or entrusted to them by the Constitution.” Prigg v. Pennsylvania https://supreme.justia.com/cases/federal/us/41/539/

[2] “Congress may not simply ‘commandeer the legislative process of the States by directly compelling them to enact and enforce a federal regulatory program.” Murphy v. National Collegiate Athletic Association https://www.oyez.org/cases/2017/16-476
Try My AI Pitch Tool and Share Your Feedback (PM Side Project)
by herald67 | 2025-07-14 17:49:11+00:00
I’m working on a product management side project called Pitch Craft.

An AI web app that turns your spoken startup idea into a clear one-liner and a structured pitch deck outline (using Guy Kawasaki’s 10-slide framework).

Project link: https://talk-to-pitch.lovable.app/

After you try it, comment below with your answers to these four questions:

1. What is your role? (e.g., founder, PM, early employee) 2. Was it easy to record your audio pitch? (Yes/No) 3. How would you rate the clarity of the AI-generated one-liner? (1 = Not clear at all, 5 = Extremely clear) 4. What’s one thing you’d improve or add? (Short answer)

Thank you for your feedback.

Your input will help me improve the tool.
by smath | 2025-07-14 17:49:27+00:00
I have wondered this too. Some stumbling blocks might be (1) lots of people are not well informed enough or care enough to participate -- which if true, would suggest there is a deeper problem (2) how to prevent lots of coersion.

But imo definitely worth thinking more abt. It might solve a lot more problems than it creates by giving power back to the people.
by NathanKP | 2025-07-14 17:49:32+00:00
Stay tuned! I think there is definitely room for a CLI version as well. That said, IDE's have a significant advantage over CLI because of the features available to them. For example, the reason why IDE's feel "slow" is often because they just come with more features: automatic linters and code formatters, type checkers, LSP servers.

An agent running in the IDE can make use of all this context to provide better results. So, for example, you will see Kiro automatically notice and attempt to resolve problems from the "Problems" tab in the IDE. Kiro will look at what files you have open and attempt to use that info to jump to the right context faster.

The way I describe it is that the ceiling for an IDE agent is a lot higher than a CLI agent, just because the IDE agent has more context info to work with. CLI agents are great too, but I think the IDE can go a lot further because it has more tools available, and more info about what you are doing, where you are working, etc
by psanchez | 2025-07-14 17:50:23+00:00
The jump table is interesting, although I guess the performance of switch will be similar if properly optimized with the compiler, but would not be able to tell without trying. Also different compilers might take different approaches.

A few months ago I built a toy boolean expression parser as a weekend project. The main goal was simple: evaluate an expression and return true or false. It supported basic types like int, float, string, arrays, variables, and even custom operators.

The syntax and grammar were intentionally kept simple. I wanted the whole implementation to be self-contained and compact, something that could live in just a .h and .cc file. Single pass for lexing, parsing, and evaluation.

After having the first version working, I kind of challenged myself to make it faster and tried many things.

Once the first version was functional, I challenged myself to optimize it for speed. Here are some of the performance-related tricks I remember using:

- No string allocations: used the input *str directly, relying on pointer manipulation instead of allocating memory for substrings. - Stateful parsing: maintained a parsing state structure passed by reference to avoid unnecessary copies or allocations. - Minimized allocations: tried to avoid heap allocations wherever possible. Some were unavoidable during evaluation, but I kept them to a minimum. - Branch prediction-friendly design: used lookup tables to assist with token identification (mapping the first character to token type and validating identifier characters). - Inline literal parsing: converted integer and float literals to their native values directly during lexing instead of deferring conversion to a later phase.

I think all the tricks are mentioned in the article already.

For what is worth, here is the project:

https://github.com/pausan/tinyrulechecker

I used this expression to assess the performance on an Intel(R) Core(TM) i7-8565U CPU @ 1.80GHz (launched Q3 2018):

myfloat.eq(1.9999999) || myint.eq(32)

I know it is a simple expression and likely a larger expression would perform worse due to variables lookups, ... I could get a speed of 287MB/s or 142ns per evaluation (7M evaluations per second). I was gladly surprised to reach those speeds given that 1 evaluation is a full cycle of lexing, parsing and evaluating the expression itself.

The next step I thought was also to use SIMD for tokenizing, but not sure it would have helped a lot on the overall expression evaluation times, I seem to recall most of the time was spent on the parser or evaluation phases anyway, not the lexer.

It was a fun project.
by airza | 2025-07-14 17:50:41+00:00
I think the hard counterpoint is - some ways that American government function are patently insane compared to other industrialized countries. Having moved from US to Nl just having one single source of truth about where I live and who I am for all sources of government is much less of a headache in day-to-day life. Mail forwarding, authentication for municipal governments, health insurance, etc, just takes 0% of my life (compared to the pain of authenticating myself separately to every part of the government, sometimes by answering questions about my life trawled from _private_ data aggregation companies - the lack of a central civil register does not seem to be particularly effective right now in stopping the Us government from terrorizing its citizens. Gathering this data for everyone is certainly more tedious but i think avoiding the dragnet completely for the average member of society is functionally impossible.
by munificent | 2025-07-14 17:50:55+00:00
> The inability of developers to tell if a tool sped them up or slowed them down is fascinating in itself, probably applies to many other forms of human endeavour, and explains things as varied as why so many people think that AI has made them 10 times more productive, why I continue to use Vim, why people drive in London etc.

In boating, there's a notion of a "set and drift" which describes how wind and current pushes a boat off course. If a mariner isn't careful, they'll end up far from their destination because of it.

This is because when you're sitting in a boat, your perception of motion is relative and local. You feel the breeze on your face, and you see how the boat cuts through the surrounding water. You interpret that as motion towards your destination, but it can equally consist of wind and current where the medium itself is moving.

I think a similar effect explains all of these. Our perception of "making progress" is mostly a sense of motion and "stuff happening" in our immediate vicinity. It's not based on a perception of the goal getting closer, which is much harder to measure and develop an intuition for.

So people tend to choose strategies that make them feel like they're making progress even if it's not the most effective strategy. I think this is why people often take "shortcuts" when driving that are actually longer. All of the twists and turns keep them busy and make them feel like they're making more progress than zoning out on a boring interstate does.
by BwackNinja | 2025-07-14 17:51:15+00:00
Zawinski's Law, when taken literally, argues that programs all eventually need to be communicated with by people and other programs using a generic protocol and without using program-specific or domain-specific libraries to do so.

Unix shells (local), I'll add in HTTP (remote), and Email (remote and asynchronous) are the only forms that are ubiquitous, precisely because they enforce no structure for the payload. The structured alternatives are only popular in specific domains because they create their own ecosystem. As long as input can clearly be parsed, which goes hand in hand with being human-readable as long as you're not trying to be too efficient, you get schema implicitly transmitted out of band (by having output that you can visually inspect) and interoperability for anything that can read and write text.

I'd be interested in other directions this might go, but I remain skeptical of anything that will introduce and enforce a new paradigm that requires adding complexity to programs to accommodate it.
by placardloop | 2025-07-14 17:51:42+00:00
AWS really shot themselves in the foot with naming everything “Amazon Q <insert suffix here>”. The Q that’s in the console is completely and entirely different from the “Q Developer” and other AI products that AWS is launching.

The Q Developer CLI, Q Developer IDE plugins, and now Kiro are pretty much just wrappers around Claude Sonnet 3.7/4, and work just as well as them.
by charlysl | 2025-07-14 17:51:57+00:00
Thank you, I will certainly check this out because this is something I've been sort of doing, manually, but I am still struggling to get the right workflow.

This recent OpenAI presentation might resonate too then:

Prompt Engineering is dead (everything is a spec)

In an era where AI transforms software development, the most valuable skill isn't writing code - it's communicating intent with precision. This talk reveals how specifications, not prompts or code, are becoming the fundamental unit of programming, and why spec-writing is the new superpower.

Drawing from production experience, we demonstrate how rigorous, versioned specifications serve as the source of truth that compiles to documentation, evaluations, model behaviors, and maybe even code.

Just as the US Constitution acts as a versioned spec with judicial review as its grader, AI systems need executable specifications that align both human teams and machine intelligence. We'll look at OpenAI's Model Spec as a real-world example.

https://youtu.be/8rABwKRsec4?si=waiZj9CnqsX9TXrM
by seanwilson | 2025-07-14 17:52:25+00:00
If this makes sense, how is the study able to give a reasonable measure of how long an issue/task should have taken, vs how long it took with AI to determine that using AI was slower?

Or it's comparing how long the dev thought it should take with AI vs how long it actually took, which now includes the dev's guess of how AI impacts their productivity?

When it's hard to estimate how difficult an issue should be to complete, how does the study account for this? What percent speed up or slow down would be noise due to estimates being difficult?

I do appreciate that this stuff is very hard to measure.
by foruhar | 2025-07-14 17:52:29+00:00
This interested me as a simple-ish approach to a tough-ish promblem. From the example Trip Planner file:

"""Command line interface to process a trip request.

We use Gemini flash-lite to formalize freeform trip request into the dates and destination. Then we use a second model to compose the trip itinerary.

* This simple example shows how we can reduce perceived latency by running a fast model to validate and acknowledge user request while the good but slow model is handling it.

The approach from this example also can be used as a defense mechanism against prompt injections. The first model without tool access formalizes the request into the TripRequest dataclass. The attack surface is significantly reduced by the narrowness of the output format and lack of tools. Then a second model is run on this cleanup up input. *

Before running this script, ensure the `GOOGLE_API_KEY` environment variable is set to the api-key you obtained from Google AI Studio.

Usage: python3 trip_request_cli.py """
by hombre_fatal | 2025-07-14 17:52:34+00:00
What about a particularly exciting book in audiobook form?

To get back into running I listened to some page turners, but I’d only listen to them when running. Sometimes I’d do an extra lap just to hear more. And I’d look forward to the next run.

Once the habit takes, I don’t need as much stimulation.

Another idea is political commentary slop or news. Don’t consume any during the day like you normally do (Reddit, twitter, news sites).

Instead consume it only through Youtube on your run. It’s usually stimulating enough to compel the run.
by burningChrome | 2025-07-14 17:52:48+00:00
Not true.

The majority of the bills are written by lobbyists. Most of the bills introduced are so called "copycat" bills.

USA TODAY and the Republic found at least 10,000 bills almost entirely copied from model legislation were introduced nationwide in the past eight years, and more than 2,100 of those bills were signed into law.

Special interests sometimes work to create the illusion of expert endorsements, public consensus or grassroots support. One man testified as an expert in 13 states to support a bill that makes it more difficult to sue for asbestos exposure. In several states, lawmakers weren’t told that he was a member of the organization that wrote the model legislation on behalf of the asbestos industry, the American Legislative Exchange Council.

https://publicintegrity.org/politics/state-politics/copy-pas...
by namlem | 2025-07-14 17:52:55+00:00
Voters thought Donald Trump and Joe Biden had merit. Clearly the voters are not a trustworthy source of discernment.

That is not because voters are stupid. It is because they are rationally ignorant. Why spend hours researching the issues and candidates for a 1 in 10 million chance of having an impact? It makes no sense. However, if we instead convened "elector juries" of a couple hundred randomly selected citizens and gave them the resources to carefully research and vet the candidates before deliberating on who is best, I think they would do a pretty good job.
by norskeld | 2025-07-14 17:53:00+00:00
Is lexing ever a bottleneck though? Even if you push for lexing and parsing 10M lines/second [1], I'd argue that semantic analysis and codegen (for AOT-compiled languages) will dominate the timings.

That said, there's no reason not to squeeze every bit of performance out of it!

[1]: In this talk about the Carbon language, Chandler Carruth shows and explains some goals/challenges regarding performance: https://youtu.be/ZI198eFghJk?t=1462
by packetlost | 2025-07-14 17:54:04+00:00
Yes, but it also removes a lot of footguns. Access to resources (ie. paths mostly) is controlled almost entirely by the parent process, which makes access controls highly pluggable and flexible.

The real problem is Plan9 never really had a lot of attention put on the things that make having a sane security policy good. Factotum seems, at best, to be bolted on after the fact.
by gopher_space | 2025-07-14 17:54:06+00:00
> If I had billions to throw around, instead of siphoning large amounts of it to a relatively small number of people, I would instead attempt to incubate new ideas across a very large base of generally smart people across interdisciplinary backgrounds.

I had an interesting conversation with an investor around the power vs knowledge dynamic in the VC world and after a few hours we'd basically reinvented higher education with reverse tuition. Defining a general interest or loose problem space and then throwing money over a wall to individuals excited about exploring the area seems wasteful until you look at the scale of failed projects.
by ceejayoz | 2025-07-14 17:54:18+00:00
https://www.npr.org/2025/06/04/nx-s1-5417980/private-prisons...

> Nearly 90% of people in ICE custody are held in facilities run by for-profit, private companies. Two of the largest, Geo Group and CoreCivic, are working to increase their ability to meet the administration's demand.

CoreCivic used to be called the "Corrections Corporation of America". GEO Group used to be "Wackenhut Corrections Corporation".

It should be unsurprising that the folks who make money building and running large, secure facilities to detain people would be interested in doing the same for ICE.
by em-bee | 2025-07-14 17:54:25+00:00
the problem with meritocracy in the military is that it is defined top-down. iaw, there is an in-group that decided who gets to join them.

a better approach would be what i have seen in the boy scouts of america a few decades ago with regards to joining the order of the arrow. there the whole troop would select those who would be invited. most troop members were not members of the OA themselves. thus the ones who were already selected had little influence in who got to join them.