MurphyA/hacker-news huggingface dataset:
by zahlman | 2025-05-05 03:30:33+00:00
> [Not a student’s real answer, but my handmade synthesis of the style and content of many answers]

> You only have to read one or two of these answers to know exactly what’s up: the students just copy-pasted the output from a large language model, most likely ChatGPT. They are invariably

This is validating. Your imitation completely fooled me (I thought it really was ChatGPT and expected to be told as much in an entirely unsurprising "reveal") and the subsequent description of the style is very much in agreement with how I'd characterize it.

In previous discussions here, people have tried to convince me that I can't actually notice these obvious signs, or that I'm not justified in detecting LLM output this way. Well, it may be the case that all these quirks derive from the definitely-human training data in some way, but that really doesn't make them Turing-test-passing. I can remember a few times that other people showed me LLM prose they thought was very impressive and I was... very much not impressed.

> When someone comments under a Reddit post with a computer-generated summary of the original text, I honestly believe that everyone in the world would be better off had they not done so. Either the article is so vapid that a summary provides all of its value, in which case, it does not merit the engagement of a comment, or it demands a real reading by a real human for comprehension, in which case the summary is pointless. In essence, writing such a comment wastes everyone’s time.

I think you've overlooked some meta-level value here. By supplying such a comment, one signals that the article is vapid to other readers who might otherwise have to waste time reading a considerable part of the article to come to that conclusion. But while it isn't as direct as saying "this article is utterly vapid", it's more socially acceptable, and also more credible than a bald assertion.
by spicyusername | 2025-05-05 03:30:36+00:00
Imagine there is a drought and the price of food rises, because food is scarce. A few people can no longer afford the whole sandwich.

To pander to those who can no longer buy the whole sandwich, and take advantage of the drought, those well off start buying even more food, more than they need, and reselling the sandwich, per-bite, with huge markup. This also drives the price even higher, due both to the markup and to the increased demand from the resellers. Now even less people can afford the full sandwich.

The resellers parasitic per-bite markup is the regressive tax, not the sale of the sandwich. The markup transfers wealth from those without the ability to buy the whole sandwich to those who can resell, when reselling is providing no value. Everyone was able to buy sandwiches just fine, before the drought. Those buying per-bite are also now going hungry, most meals, because they can only afford a few bites.

The solution is either to find ways to end the drought, ration the available full sandwiches, or sell smaller sandwiches, not to allow drought-profiteering that exacerbates the sandwich scarcity and makes more people go hungry.
by nine_k | 2025-05-05 03:32:22+00:00
In a medieval guild, to be admitted as a master, an apprentice had to create a chef d'oevre, or masterpiece, so called for this reason.

In the computer engineering industry, you increasingly have to demonstrate the same: either as a part of your prior work for hire, or a side project, or a contribution to something open-source.

A diploma is still a useful signal, but not sufficient, except maybe for very junior positions straight from college. These are exactly the positions most under pressure by the automation.
by Mbwagava | 2025-05-05 03:32:41+00:00
> If all we were interested in was moving the weights around, you’d be right to use a tool to help you.

Does the use of a quantifiable metric like a GPA not exacerbate this? In a world where people take a GPA seriously, you'd have to be irrational to not consider cheating a viable option.

You could say the same about credit score and dating apps. These institutions assist the most predatory and harm the most vulnerable.
by jhgaylor | 2025-05-05 03:32:42+00:00
The bulk of the server today is just context (and tools to get the context). I offer a contact tool when you use the hosted server because I can hide away my email credentials and expose a way for the LLM to send me an email.

Future tools I have in mind include taking a job description and returning a cover letter and sample interview.

Another benefit of using MCP is the LLM can request subsets of the context as it deems them valuable instead of preloading all of the context head of time.
by notphil | 2025-05-05 03:33:09+00:00
Cool idea. I can see this, if extended, being useful.

* A GitHub MCP exposing your code and issue contributions

* A site that exposes CV-data of candidates.

* An agent LLM iterating on all these, finding candidates that match roles.

Or vice versa, finding roles for a given candidate.

I might not be actively looking for roles, but I'd like to be aware of opportunities that might be a good fit. Recruiters historically have wasted my time.
by WatchDog | 2025-05-05 03:36:16+00:00
When using Claude Sonnet 3.7 for coding, I often find that constraints I add to the prompt, end up producing unintended side effects.

Some examples:

- "Don't include pointless comments." - The model doesn't keep track of what it's doing as well, I generally just do another pass after it writes the code to simplify things.

- "Keep things simple" - The model cuts corners(often unnecessarily) on things like type safety.

- "Allow exceptions to bubble up" - Claude deletes existing error handling logic. I found that Claude seems to prefer just swallowing errors and adding some logging, instead of fixing the underlying cause of the error, but adding this to the prompt just caused it to remove the error handling that I had added myself.
by bruce511 | 2025-05-05 03:36:53+00:00
That's entirely the point. If you see the degree only as a stepping stone to the company job, then that's all you see and that's all you get.

If you accept that the degree/job relationship is the start, not end, of the reason for being there, then you see other things too.

There are opportunities around the student which are for them, not for their degree, not for their job. There are things you can learn, and never be graded. There are toys to play with you'll never see again. There are whole departments of living experts happy to answer questions.

For example, (this is pre google) I wrote a program and so needed to understand international copyright. I could have gone to the library and read about it. Instead I went to the law faculty, knocked on the door, and found their professor who specialized in intellectual property.

Since the program I wrote was in the medical space, I went to the medical campus, to the medical research library, and found tomes that listed researchers who might benefit. I basically learned about marketing.

If all you care about is the company job, then all you'll see is the degree.
by vunderba | 2025-05-05 03:37:09+00:00
It's kind of the MCP version of this Show HN (Interactive AI Resume/LinkedIn) posted about a year ago.

https://news.ycombinator.com/item?id=38245665

Thanks for including the LLM rules (cursor) in the repo - MCP is new enough that I'll bet having that as a guidance was pretty helpful.
by bschwindHN | 2025-05-05 03:38:54+00:00
Give SolveSpace a try. It's fantastic for 2D sketches and then you can extrude/revolve/subtract these sketches into other solids to build up your part. It can export to STEP or STL and then it's an easy trip through the slicer and you're ready to print!

If you're more programming minded, try out RepliCAD. Or if you don't mind dealing with Python and its build ecosystem, there's CADQuery or Build123d
by dhosek | 2025-05-05 03:39:21+00:00
Maybe it’s because I’m just recovering from attending my 35-year college reunion, but I had a memory return of being in the college computer lab and telling someone to use the mouse to move the cursor, so they picked it up and waved it in the air.

That Star Trek IV scene was a reminder that a computer mouse isn’t as universally intuitive of a device as it might seem.

(And on a tangentially-related note—I’ve been driving a Ford Mustang convertible this weekend and the fact that some screens are touch screens and some are not has been a bit of a source for confusion to me. I think I don’t have the same issue with my Prius because there the steering-wheel cursor keys control a screen that’s on a different plane from the main dashboard. Also, I really miss my radar cruise control.)
by nntwozz | 2025-05-05 03:39:42+00:00
I think David Lynch nailed it in Lost Highway:

-

Ed: Do you own a video camera?

Renee Madison: No. Fred hates them.

Fred Madison: I like to remember things my own way.

Ed: What do you mean by that?

Fred Madison: How I remembered them. Not necessarily the way they happened.

-

I used to own a DSLR, it was great for planned shots when settings things up for something special (e.g. my dog in mid air jumping over a fallen tree in the woods).

It's a nice hobby but I lost interest and now I just shoot stuff randomly with my iPhone.

It's a nice thing to have, but I think there's a purpose in forgetting, keeping track of everything can become a burden.

We're too obsessed with this, people can't even take a jog any longer without tracking pulse, calories, route etc.

It's too much, and it's making many of us miserable.
Show HN: Promptor. Turn any codebase into a single, clean prompt – in seconds
by edrickdch | 2025-05-05 03:40:12+00:00
Promptor is a tiny macOS app that lets you drag-in a folder and drag-out a perfectly-formatted prompt ready for ChatGPT (or any LLM).

It's free, open-source and easy to use.

No server-side processing, no API keys, no rate limits – just a local SwiftUI app that gives you the full context of your project in one click.
by heavyset_go | 2025-05-05 03:40:45+00:00
> But let's be honest - most of these people, the ones the article is taking about, where they think they are some messiah, would have just latched onto some pre-internet cult regardless.

Honestly, I believe most people like this would just end up having a few odd beliefs that don't impact their ability to function or socialize, or at most, will get involved with some spiritual woo.

Such beliefs are compatible with American New Age spiritualism, for example. I've met a few spiritual people who have echoed the "I/we/you are god" sentiment, yet never lost their minds over it or joined cults.

I would not be surprised that if they were expertly manipulated by some of the most powerful AI models on this planet, they too, could be driven insane.
by EigenLord | 2025-05-05 03:40:54+00:00
I think the answer to the professor's dismay is quite simple. Many people are in university to survive a brutal social darwinist economic system, not to learn and cultivate their minds. Only a very small handful of them were ever there to study Euler angles earnestly. The rest view it as a hoop they have to jump through to hopefully get a job that might as well be automated away by AI anyway. Also viewed from a conditional reinforcement perspective, all the professor has to do is start docking grade points from students who are obviously cheating. Theory predicts they will either stop doing it, or get so good at it that it becomes undetectable-possibly an in-demand skill for the future.
by nine_k | 2025-05-05 03:41:11+00:00
700 AU is way past heliopause, firmly in the interstellar space. Same, 15 times farther than Pluto is definitely away from the Solar system "proper". It's about 100 light-hours away from Sun.

I wonder how could this object be counted as a "planet" belonging to the Solar system, even if it were the size of Jupiter. But it's an object "estimated to be 2 to 4 times the radius, and about ten times the mass of the Earth". This must be another class of celestial bodies, some jumbo-sized Oort cloud object.
by zahlman | 2025-05-05 03:41:29+00:00
Short version, although you already got an answer:

If everyone had to use it, and everyone were only allowed to use "static" dependencies determined ahead of time, yes. But:

* legacy projects that don't use pyproject.toml are still supported

* it's possible to publish an "sdist" source package that's built on the user's machine (for example, because it includes C code that's highly machine specific and needs to be custom built for some reason; or because the user wants to build it locally in order to link against large, locally available libraries instead of using a massive wheel that copies them)

* When something is built locally, it's permissible to determine the dependencies during that build process (and in some rare cases, that may be another reason why an sdist gets used - the user's environment needs to be inspected in order to figure out what dependencies to fetch)

* Even if it did work, `pyproject.toml` is really more like "source code" for the metadata (about dependencies and other things). The real metadata is a file called `PKG-INFO` when it appears in an sdist, or `METADATA` in a wheel. The format is based on email headers (yes, really).
by ehnto | 2025-05-05 03:41:57+00:00
And if it wasn't what you wanted, well maybe you are wrong. An AI that intelligent is always right after all.

Seriously though, at some point AI does actually need an input from the user, if we are imagining ourselves still as the users.

If instead we just let AI synthesise everything, including our demands and desires, then why bother being involved at all. Take the humans out of the loop. Their experience of the outputs of the AI is actually a huge bottleneck, if we skip showing the humans we can exist so much faster.
by edrickdch | 2025-05-05 03:43:59+00:00
I built Promptor after realizing I was paying US $0.30 per o3 request in Cursor.

Coding with o3 is amazing, but with ChatGPT Plus we already get 100 o3 requests every week…

so why not copy the entire repo into the chat?

clearly there's a cost arbitrage here in planning the feature or fix with o3 from the ChatGPT Web UI. Then, using gemini 2.5 or sonnet 3.7 to implement it.
by Jach | 2025-05-05 03:44:27+00:00
Huh, didn't realize that beach didn't like it so strongly. Still, hardly "much maligned"... My impression was that most people enjoyed it, even though it definitely has some weaknesses and could (especially now 15 years later) use a second edition, if for no other reason than to move off CLISP to SBCL. This seems supported by its high reviews on Amazon and GoodReads. (Of course overall I liked it too, and we got the best music video about lisp out of it.) FWIW my own criticisms were largely style-based: too much of it felt like Scheme code rather than Lisp code, even outside of emphasizing/educating about the more primitive features, with lots of things like inner functions, recursion where looping would have IMO been clearer, and so much use of raw car/cdr/caadr/caddr/whatdr instead of more clearly structured structs or classes or just helper functions called intuitive things like get-foo. (The book Calendrical Calculations: The Ultimate Edition uses lists for all its data structures but helpfully creates many functions to both construct and access their parts. e.g. generic dates are a (year month day) list, but the definition and exclusive use of standard-year, standard-month, and standard-day for getting at them would let one refactor it into a class. There are also functions like gregorian-date, julian-date, and egyptian-date that have exactly the same implementation (making a list of the 3 passed params) but serve as 'typed' list constructors, and indeed could be refactored into something that carried along type information without changing other code.)
by leoapagano | 2025-05-05 03:45:15+00:00
From my experience, I find most of the time the best part about hackathons is not what you create, but who you get to meet/network with. It may just be my uni/age cohort, but most projects I saw at the last hackathon I went to were less "MVP" type/semi-complete projects and more just "we have a concept of a plan."
by sho_hn | 2025-05-05 03:47:26+00:00
Unlike llms.txt (which I think none of the major vendors have announced to be using/supporting, too, for that matter), there's currently no standard for AI assistants running a web search and discovering these end points yet, though, is there?

That means someone would have to jump through manual hoops to consume this.

Perhaps a needed bit of integration is a vendor that allows you to park a chat box on your website that knows how to call out into your MCP, so I can talk to your resume directly on your website. I assume this exists already, if not it'd be weird (it's not that hard to cobble together manually against the agent-ish APIs, after all).
by marcus_holmes | 2025-05-05 03:48:15+00:00
I used to have a 100-lb bow (for re-enactment), and the comparison is apt, but slightly off:

Imagine picking up a 45-kg weight using only a string held by three fingers. The pressure on the fingers is intense. Getting the shoulders and chest into the pull is the trick, and it's not quite as hard as lifting a weight off the floor because of that. But the fingers are doing a lot of work. Mine had turned white after a few shots, even with a thick leather tab to protect them.

We did do volleys, because the public expected it and it was fun to do. But we could not hold for long - the bloke doing the shouting knew that he had only a couple of seconds between "draw" and "loose" or we'd be all over the place.
by dmazzoni | 2025-05-05 03:53:01+00:00
Consider that there is some in-between.

Some college students may be genuinely interested in one particular subject, but they're required to take a bunch of other courses, and consider those to just be hurdles.

I still think they're better off at least making an effort and trying to learn something, but I do think it's important to note that just because a student has no interest in one particular class, doesn't mean they have no interest in any class.
by magicalhippo | 2025-05-05 03:55:20+00:00
I have a vivid memory of playing Rise of the Triad[1] against my buddy over serial cable. As most PC games from back then, it used mode 13h[2], so 320x200 resolution with a 256 color palette.

I have the distinct memory of firing a rocket at him from far away because I thought that one pixel had the wrong color, and killing him to his great frustration. Good times.

You can play the shareware portion of the game here[3] to get an idea.

[1]: https://en.wikipedia.org/wiki/Rise_of_the_Triad

[2]: https://en.wikipedia.org/wiki/Mode_13h

[3]: https://www.dosgames.com/game/rise-of-the-triad/
by jhgaylor | 2025-05-05 03:57:02+00:00
If LLMs are going to get used to filter candidates out of jobs (they will, lets be real) then it is going to happen regardless of if a candidate makes a tool that explicitly provides their data in an LLM friendly format or not.

Resumes are already being run through a machine. We know what the next generation of machine looks like, so now as candidates we can put our best foot forward.
by marcus_holmes | 2025-05-05 03:57:13+00:00
Maximum range varies per archer. Each bow is different, and each archer is different. This isn't modern mass-produced armaments (though they did mass-produce bows, each one was still made from a different piece of wood with its own quirks), and maximum range also depends on the archer's draw length (how long their arms are) and strength.

One of the stories about Agincourt (that the author didn't mention and I don't know if it's true) is that the French underestimated the range of the English archers and drew up inside their maximum range, so were getting shot before they were ready for it.

So "everyone shoots when the enemy gets into range" would still not be a volley as each archer judges for themself when the enemy is in range.
by EigenLord | 2025-05-05 03:57:14+00:00
Years ago, in my writings I talked about the dangers of "oracularizing AI". From the perspective of those who don't know better, the breadth of what these models have memorized begins to approximate omniscience. They don't realize that LLMs don't actually truly know anything, there is no subject of knowledge that experiences knowing on their end. ChatGPT can speak however many languages, write however many programming languages, give lessons on virtually any topic that is part of humanity's general knowledge. If you attribute a deeper understanding to that memorization capability I can see how it would throw someone through a loop.

At the same time, there is quite a demand for a (somewhat) neutral, objective observer to look at our lives outside the morass of human stakes. AI's status as a nonparticipant, as a deathless, sleepless observer, makes it uniquely appealing and special from an epistemological standpoint. There are times when I genuinely do value AI's opinion. Issues with sycophancy and bias obviously warrant skepticism. But the desire for an observer outside of time and space persists. It reminds me of a quote attributed to Voltaire: "If God didn't exist it would be necessary to invent him."
by mettamage | 2025-05-05 03:57:20+00:00
This is how I currently am relearning upper high school math. It’s tremendously helpful as I am a why guy.

Why is the angle called m? Why is a combination nPr * (1/r)? What is 1/r doing there?

I use mathacademy.com as my source of practice. Usually that’s enough but I tend to fall over if small details aren’t explained and I can’t figure out why those details are there.

In high school this was punished. With state of the art LLMs, I have a good tutor.

Also it’s satisfying to just upload a page in my own handwriting and it understands what I did, and is able to correct me there.
by kmeisthax | 2025-05-05 03:58:52+00:00
We already do this. Neural networks can't work with tokens directly - they only take real-numbered vectors and they need differentiable input[0]. So you don't give it token 123, 456, etc; you have to turn each token into a "one-hot encoded" vector that's all zeroes except in the position indexed by the token ID, which gets set to one.

These one-hot encoded vectors are then fed through a linear layer that encodes the token vector down into the hidden state size of the model. e.g. you might have a token vocabulary of 10-100k but a hidden state size of 0.5-2k. Everything else in the model works in hidden state space[1], which has all sorts of higher-level concepts in it.

Now, if we were to remove tokenization, then the encoder needs to do more work in order to get to the same hidden state space we're used to. It might be able to find a more efficient encoding from unpaired bytes to the hidden space, but that seems unlikely, given that the tokenization most models use is already based on the statistical properties of the training set. If we don't automatically pair "anti" or "ism" into a single token before handing it off to the model, then the attention heads on the lower layers in the model have to do the same work.

Given that we used to train models on character sequences, and then moved to tokenization because it was more efficient, I suspect the trade-off is never going to be worth it.

[0] That is, you can't just give it a list of token IDs, because there's no mathematical meaning to token 123.25, nor any meaning to increasing or decreasing token IDs.

[1] This improves performance but makes interperability harder. Most notably, the hidden space's basis vectors are not directly correlated to words or concepts, instead all the concepts exist on a sort of N-dimensional ring.
by anonymousiam | 2025-05-05 03:59:14+00:00
Conceptually, your idea seems reasonable, but because the goal is to put the power from the solar micro-inverters onto the grid, they must lead the grid phase by a few degrees. If they lag instead of leading, they are draining power from the grid and not supplying power into the grid.

People with PV arrays want to make money by selling power into the grid. Perhaps if they were a little less greedy, they could back off the phase difference if they detect the grid phase drifting from too much "pushing." After all, they can't sell any power at all while the grid is down.