skysight-inc/HackerNews huggingface dataset:
I have had a lot of opportunity to estimate a lot of projects, but one thing I still can't figure out is estimate education.

If a client wants to know "why is this going to take so long?" I can list the unknowns and third-party touch points, which are always things that make tasks take longer, but then they'll wonder why those are going to make it take longer. From there it's a challenge to communicate how unknowns are part of every project, how they are a good indicator of the risk of a task, and how there are some things you just won't know until you start work on a task in earnest.

Doesn't seem to matter how much detail I go into, it always comes back to "but I thought this would be easy."

The best I can come up with is to educate clients on what bad estimation looks like (Did they come right back with a fixed estimate for your type of project? Are they even asking questions?), hope they come back after getting different estimates with the exact red flags I warned them about, and then maintaining client trust by any means necessary so that when I say something is going to take a certain amount of time they know I'm not exaggerating.
Paying contractors to support your free GitHub project is wild.

Open source is beautiful and broken at the same time.
YouTube's network effect creating a winner-take-most was recognized, pitched, and valued from the very start.

The capabilities of LLMs are impressive, but none of them have published an idea I consider to have the same potential for a trillion $ monopoly that the current hype looks like.

There are far more similarities with the dot-com hype.

No critical first mover advantage in sight. All parts are replaceable for the cheapest variant with little to no down side to users.
I hope I'll live to see the day we have a laptop, tablet and smartphone all in one.

You plug it into a desktop setup and it's a high end computer with which you can game and work, then you detach it and fold it into a tablet, and fold again into a smartphone.
> I was talking about language acquisition specifically.

Yeah, humans don't acquire language separately from other experience.

> Most of the data that you reference is visual input and other body sensations that aren't directly related to that.

Visual input and other body sensations are not unrelated to language acquisition.

> OTOH humans don't take all that much text to learn to read and write.

That generally occurs well after they have acquired both language and recognizing and using symbolic visual communication, and they usually have considerable other input in learning how to read and write besides text they are presented with (e.g., someone else reading words out loud to them.)
It's just status anxiety. Mid engineers go on and on claiming theres literally no value from LLMs even possible in principle while top tier people are using them as force multipliers.
I'm not judging harshly: adrenaline dumps are a real thing. And even though it looks under control, a few passenger interviews have indicated that many folks didn't have time to think.

But the whole point of all those procedures about turning stuff off and putting things is away is situations like this: you may or may not have time to think, and you may or may not have to deal with smoke or flames. And just because there weren't smoke/flames right at that moment, you can't tell if they would arrive "soon": planes have been completely engulfed in fire with-in 90 seconds in the past.

The idea behind suggesting a fanny pack, and perhaps having all your cards and papers (and medicine) on your person, is so that if such a thing should happen you do not have to think to make sure you have what you need. So that in a panic you already have it with you if you get out just by the fact you got out and it was physically attached to you.
why not go down vscode extension path?
To be able to print it and fill in by hand or by typing on a PC? To be able to save the filled-in form in a portable file?
No DeepSeek model is open source; they're freely redistributable, but without source.
They appear to be fantastic for those with limited vision.

Same thing with voice assistants like Alexa, for the average person having a live speaker listening 24 7 is kinda silly, but for someone who's legally blind it's a life changer.

Say at 90 you can't see well, you can say, "Hey Alexa, play some John Coltrane". It would be better for this all to run locally, but let's not let perfect be the enemy of good.
Thanks, I’ve read the constitution too. Ever heard of congress, full of elected officials? Or the senate? Your claim that there are so few elected officials is patently absurd.
Yukjin Korean
An idea I’m working on is allowing the integration of APIs by writing a prompt. I’d have a large number of APIs of different types and I’d discover the best endpoint and execute it and return the results. First time your code runs would “compile” the prompt, so subsequent execution would run O1.
This could be used by a human or an AI agent.
let temp = Get(“current temperature in NYC in F”)
Simple scenarios like these are easy, but looking at more sophisticated stuff as well.
I agree (mostly), but

> If the cloud disappeared, I wouldn't be able to build apps anymore.

Seems rather hyperbolic. Colos and shared hosting were a thing long before the cloud craze, and still continue to be a thing. I figure if nothing else a lot of people would go back to the still relatively low touch environment of uploading PHP or CGI scripts, which honestly seems like a pleasant change these days.
Estimating the quality of academic books from their descriptions with ChatGPT
I don't know how to tell you this, but the government isn't a business and has completely different objectives and operating conditions
That might work if you're slashing headcount at a social media company (though I would argue that it doesn't), but the stakes are a bit higher when you're responsible for things like feeding hungry people, curing disease, or keeping planes in the sky.
And people with short term memory loss nevertheless have theory of mind just fine. Nothing about LLM's dropping context over big enough windows implies they don't have theory of mind, it just shows they have limitations - just like humans even with "normal" memory will lose track over a huge context window.

Like there are plenty of shortcomings of LLMs but it feels like people are comparing them to some platonic ideal human when writing them off
Broken heart syndrome (Takotsubo cardiomyopathy)
...unless you're in competition with them.
That's the thing I've learned about drills...you unfortunately need 2. One is the probably battery powered for doing random light drilling conveniently for relatively short periods of time around the house. Two is a probably corded, high power drill for everything else.
Do you hear yourself?

Name a specific thing you would like to know about DOGE that is not publicly disclosed.
And you could theoretically just have Postgres be the app server -- you can even write pg stored procedures in friendly languages like Python.

(Tangent: In fact, I sort of used to develop that way with SQL Server back in the early 2000s. VBScript and PHP sucked, and databases in my apps were sometimes shared between different apps, so I liked to put a lot of the data-level logic in stored procedures. You need a migration strategy of course but that was honestly a perfectly fine way to develop. I was productive and remember those days fondly. I didn't expose SQL Server to the net directly, but it was sort of the app server, and stored procedures can be extremely performant since there's no round-trip)

But I mean...

Still. You need private application code somewhere. At a minimum you need it to ensure that users aren't doing and seeing things they're not supposed to do and see. And also to connect to auxillary services e.g. payment processors -- you need to store the credentials somewhere private.
It’s true that LLMs have only limited short-term memory, and no long-term memory, but that is completely orthogonal to having a theory of mind.
> Every single piece of my tools is Snap-On or something really comparable.

A Snap-On drill, battery and charger costs $980 [1]

The article is about a homeowner who needs to make one 60mm hole through wood

For such a simple task, the $45 drill I linked will do just as well as the $980 one

[1] https://sep.snapon.com/product/CDR9050K2
yet with claude still the most useful, lmsys is broken for coding
> Why were you so desperate to flee Windows 7?

Well, let's look at your statements:

> Windows 7 was objectively the best Windows, and Ubuntu is considered by many to be one of the worst distros.

You have two statements: one about the distribution of "goodness" as a function of Windows versions, and another about the distribution of "goodness" as a function of Linux distros.

So, logically, the question to answer if we want to get at your question is: how does the distribution of "goodness" compare across Linux and Windows?

Perhaps their answer might differ from yours. :)
My thoughts exactly. :(
And didn’t Apple move iPhone production to India already?
Tariffs result in higher prices, resulting in less demand, resulting in less consumption, resulting in less production, resulting in fewer greenhouse gases produced resulting in saving the planet? Trump is saving the planet? /s
You mean Dell, HP and Lenovo?

Heck, I could drive to the Lenovo plant on my lunch break...
True.

Those other brands will see price hikes that are slightly lower than 10% then.
What do we do with this?
Everyone thinks they are the main character of the story. I should get to keep my bag because I am the protagonist, but everyone else is supposed to leave theirs, so that we can escape faster! The rules don't apply to me specifically because I am the only person in my life that matters.
Show HN: 3D Data World Explorer
Hello!

I'm working on a new personal project 3D Data World this project aims to be a fun place where you can explore data about the world. I decided to start this project to put my data analyst skills into practice, such as: data collection, data cleaning and data visualization. For now, I just have one single category that is Population. In the near future, I plan to add more categories and explore different ways to visualize the data.

What kind of data would you like to see? If you have any feedback or ideas, feel free to share them.
But as I explain in another thread, that doesn’t apply because E and N are in 1-to-1 correspondence which is not the case with Q and R
Survive sure. But one of the people in critical condition is a small infant that got thrown out of their lap belt so they will probably have life-altering injuries from this.
Putting aside the obviously dystopian qualities of this product... I find it strange that I know zero people who own this device which has sold supposedly over a million units.
What about third world programmers? They can’t necessarily afford a $5000 GPU. If it weren’t for the “generosity” of tech companies like GitHub granting free LLM usage, they might be locked out entirely. This would put them at a disadvantage, we can argue to what degree but it’s still a disadvantage.

Depending on the curve we’re on, LLMs may grow more resource hungry while becoming closer to human performance in software engineering tasks. It’s not unimaginable this would concentrate productivity in the upper class of software engineers that can afford the hardware and/or licenses.
Actually, I used to like Elon and was almost about to buy a Tesla, before the overwhelming burden of evidence required me to change my mind about him.

What motivates your point of view? I'm genuinely very curious.
Yeah that's true. But I'm not sure how the costs for that will work out at scale considering software is a high attrition industry with career advancements done mostly through lateral movement.
Yup, it was written from scratch. Yeah, having a flexible virtualized table certainly makes it easier to build more complex things on top (a lesson I initially learned from NSTableView/UITableView).

Currently, it's not user extendable. While it does support some IPython features (eg: Python classes that implement IPython's rich outputs also work in Scripton), ipywidgets are currently not supported.
I’m always reminded of the quote at my mechanic’s “the reason it only took half an hour is that I spent 10 years learning to do it that fast” [paraphrase]

If you’re actually an expert in something you will be able to assess (ask the right questions) the scope to 95% probability (yes there are always edge cases)

I suspect if a professional installer had surveyed the situation he would have immediately looked for hose length, holes, have the tools etc.

It seems like this is more a case of dunning-Kruger than anything else (and trust me I’ve been there “I mean how hard can it be to X”)
What can I say. I grew up in a town of ~500 people.
I'm more of a R7RS kinda guy but I appreciate this, especially the types. Scheme allows for extremely non-linear memory access which means you necessarily need dynamic memory management and garbage collection. IMO once you're to that spot, there's little reason to stick with Rust, though it being the implementation language is interesting in itself. That being said, there are battle tested Scheme implementations out there that have fantastic FFI APIs that would probably work just as well if you don't mind a small bit of C to glue things together.
Show HN: I built the simplest waitlist builder so you can market your product
So, no source then. You cannot include everyone with “hope” or everyone with capitalist leanings as adherents of a relatively fringe belief system. Hoping for personal profit is again not an ideology.
Weather data.
Why does it need to work beyond text-based output?
"How could you possibly leave Windows for Linux?!" also smacks of zealotry.
There it is... the consequences of our actions.
"fee technicians — the people who collect money at park entrances and campgrounds — who were two months into the hiring process"

What? It takes two months+ to hire a ticket seller? Ridiculous.
This is hilarious if you know the movie, Dog Day Afternoon, which is the true story of a bank robber who was trying to help his trans lover pay for surgery. I wonder what part of that got censored?
I'm fully straddling both. I loved successfully recapping a Macintosh SE and restoring a Lathe from 1964. I was mentally counting the execution threads in the processors in the house, got up into the upper 50's and chuckled going from 54 to 55 when including the 68000 in the Mac.
All people on board survived that crash as well.
I think the above poster was comparing search engines to LLMs and just using Google as a generic example.

LLMs very obviously aren't a replacement for live human written information which is findable with a search engine.
Signal used to be a pretty good SMS app, even disregarding the cryptography aspect. That how I treated it, and that's how it became successful among "normies". It was a good SMS app with encryption as a bonus. So much that as Signal discontinued SMS access, I was tempted to take an older version of Signal, strip out all the crypto, making it play well with the Android SMS system, and republish it as a simple SMS app.

But it seems that Signal failed grasp the importance of SMS, instead of fixing the ongoing issues, they let it rot before discontinuing it completely. Yes, SMS is bad for privacy, but they are not in a position to change that, they don't have the critical mass that Whatsapp has.

They thought they could take advantage of the boost they got with the Whatsapp/Facebook controversy and Elon Musk "use Signal" tweet to make people change their ways, probably not realizing that privacy is not that strong an argument for people outside of their bubble and that they have to offer "something else", and good SMS integration is "something else". And yes, having users that have "nothing to hide" is important for a privacy-focused app, because otherwise, the simple fact that someone is using that app can make him a target (see: EncroChat).
A fair amount of anecdotal data though, it has helped me and others that I know. While the effect is pretty mild it is positive. Having a lifelong chronic condition I’m very sensitive to changes and have no discernible placebo effect. I’ve tried so many things that my prior belief when trying something new is that it wont work, so it’s a nice unexpected surprise when it does.
Heritability is genetic determinism. It's not like you get a different set of genes as you age. Are you indirectly saying that the genes responsible for physical characteristics follow different rules than the genes responsible for intelligence? Like could your environmental factors change your height? I would say maybe it is something in the middle like the genes determine your maximum potential in physical and mental expression.
This thread is about large language models and generative AI. AFAIK LLMs perform pretty badly at time series prediction.

Maybe some specially trained weather prediction neural network could perform well, but that isn’t really what we’re talking about here.
Yeah so like, this is a cool result, and it uses a transformer architecture. I actually do think that it's fair to say that transformers have proven widely useful, especially in tasks that look like sequence modeling. It's a step change akin to the now-pervasive use of convolutional neural networks that started in the 2010s, and is deeply significant of course. This is also really different from "this is an LLM"

The reason I want to specifically harp on this is because a lot of people are selling this narrative where "AI is becoming superintelligent" or whatever by making an amorphous blob out of a bunch of separate advances that use machine learning techniques. This has been happening for a while, is a great thing for science, and it's clear that machine learning methods are here to stay in science. I'm a machine learning researcher. I've understood, celebrated, and tried to help with this as best I can manage over the last 9 years of my life. And it's been going on for a lot longer than the general public has been in this AI hype wave. The entire modern field of bioinformatics is arguably built on the backbone of machine learning, and has been since before I went to grad school.

This is really different from "We fed everything into a language model and now it's superintelligent and is making scientific advances all by itself" or even "scientists just ask chatGPT shit and it figures it out for them". The breathless tech press really makes it sound like anything that happens in AI research, which increasingly includes the entire usage of ML toolkits in the sciences (Which is pervasive, and expectedly so! ML is an extension of statistics and statistics has been the basis of science for like a century) is just some amorphous force called "AI" that's suddenly gained this aggregate body of competency. Imagine if we anthropomorphized statistics that way. Or Math for that matter. This kind of narrative gives me the overall impression that this is not being talked about honestly, and it's clear that this is profitable to do. I don't have to use charged words like "con" or "fraud" to think this deceptive framing is not a great thing
+1 for Jodorowsky's Dune. It's a fascinating study of "the greatest sci fi movie never made". You can see its DNA in Star Wars, Bladerunner, Alien and more.

I hope some day Moebius and Jodorowsky's storyboards are published in the public domain
It's the same with touch typing too.

IME, without good muscle memory (touch or hybrid typing) of keys, consciously searching for each key is going to seriously disrupt the flow and thought process behind the code being written.

It may not make you a rockstar programmer, but it will definitely make coding more enjoyable.

I think there was a recent HN discussion on this topic.
I have been building it, in fact.

https://qbix.com/ecosystem

Do I have your attention now?

Ten years and $1 million dollars later, it’s free to use, but we haven’t started promoting it yet, still testing with paying clients:

https://github.com/Qbix

Here are some ideas:

https://qbix.com/community.pdf

https://qbix.com/alumni.pdf
Honestly I think the hardest part was focusing on the areas that drive the biggest impact and finding out what actually mattered with early beta users. I started way too complex with the briefing/summary feature and built a way to manage how frequently each email category comes up in the briefings. So for example, you could say summarize my newsletters once a week, but give me receipts every three days. That was such overkill and a waste of time.

One thing that sticks out to me after using this for a few months is that I'm actually okay with getting notified more frequently than I thought I was, but the key is that each notification needs to be highly relevant and only the most important information. I've tuned it to fit my needs precisely.

I also love the thought of building a knowledge base for myself, and one of the next things I want to explore is to suck in information from Obsidian, Notes, texts, etc. and embed it all so I have an assistant with complete personal context about me. For that one, having it be a self-hosted open source project with a private open source LLM feels like the only real way to go.
How simple are we talking?
And the desktop Mac Pros are built in Texas.
Yep. Of course, one needs to adapt the speech to the audience :-)
yes, and you can even use infrared spectroscopy to infer brain activity via the bold signal: https://en.wikipedia.org/wiki/Functional_near-infrared_spect...
Not an expert, but IIUC current quantum computers probably could "factor" numbers in the ~10k range (but doing so wouldn't be that interesting since they could only do so without the error correction that will be incredibly necessary to making Shor's algorithm work in practice)
I had a DIY project last night that took double the time I estimated. I wanted to replace the charging port on my smartphone. I've replaced parts in previous smartphones, but that was the era of quick replaceable batteries and limited water resistance. I had the charging ribbon assembly replacement part, I had tools, and I had watched some videos. But something I didn't take into account from some of the videos is how they glossed over removing and replacing the glued on, glass back of the phone.

I spent at least an hour just trying to get the back off without cracking it.

Then on to the battery, which was glued in. Some videos manhandled the battery to the point I could see some bending, which I definitely wanted to avoid(I planned to reuse the same battery). Some used heat to loosen up the glue, but once the phone was open I noticed the temperature warning on the battery, 104F, which was probably pretty close to what it would take to get the glue under the battery to soften. One video dripped IPA around the sides of the battery. I realized I didn't have an eye dropper for precise placement, and I didn't want to just douse my whole phone in alcohol, so I ended up using a plastic chopstick to get droplets in.

At least 30 minutes went towards that and finally feeling safe enough to pry out the battery.

Then removing boards and ribbon cables, and trying not to break any connectors took about 30 minutes. Putting them back in took another 30 minute because keeping the connectors from folding under things and getting crimped was really annoying. The bend of the ribbon cable was off, so aligning things was extra funky too.

After finally getting things back in place and screwed in, I tested the phone before gluing the back on. What I didn't do is test the fit of the back before applying the glue. Turns out one little plastic piece wasn't clipped in underneath a metal frame in the middle of the phone, so the back couldn't fit flush. Another 30 minutes spent just cleaning out the glue so I could start over. And then I finally got the back glued on and sat with it wrapped in rubber bands for another 30 minutes.
B.C. couple referenced non-existent, AI-generated court rulings in condo dispute