MurphyA/hacker-news huggingface dataset:
by mynameisash | 2025-05-28 02:09:26+00:00
Lots of responses to your first two points, and I immediately jumped to your last one:

> Third, I was surprised the author felt bad. A sign that there is unfortunately some stigma in re-using things.

Ever since my wife and I got married 20+ years ago, we've had a clothesline, and we are constantly line-drying our clothes, weather permitting. I've had plenty of weird looks and probably even a few comments. I definitely have had the impression that people look down on me for doing so, but weird stigma be damned.
by taneq | 2025-05-28 02:09:40+00:00
> I never understood why Reddit, which always tried to give off the "for the little guy" vibes was so rabidly against anyone promoting their own work.

Reddit hasn't been 'for the little guy' for a decade, that's why they have to try so hard to give off those vibes.

> Reddit would aggressively remove self promotion in most subs while clearly running major PR campaigns under the guise of organic content.

Yep, this is why they do this. They're removing competition (in the form of ads they weren't paid for) to boost their product (ads they were paid for).
by bigyabai | 2025-05-28 02:10:01+00:00
High risk high reward doesn't always pay off. Sometimes you gotta swallow a Cybertruck, or a $44 bln Twitter acquisition, or a high-margin Nvidia-fuelled AI datacenter, or a political lobbying shitstorm. All of which fall squarely in the lap of Mr. Musk as the adamant leader pulling the strings.

If you're correct and Elon is to be credited with these administrative successes, then turnabout is fair play in assessing his entirely unnecessary business strategies. Let's not fool ourselves into thinking Tesla would be undervalued if Elon hadn't bought Twitter. I heard the "underrated genius" shtick when Jobs died, and then every subsequent biography echoed his personal struggles and failures he hid to prop up his cult of personality.
by mmmBacon | 2025-05-28 02:11:38+00:00
It’s not correct to say that lasers are unreliable. Last year more than 20M transceivers shipped. Your statement is not at all supported by real field failure data.

The reliability of micro LEDs. and specifically GaN based micro LEDs is however an open question.

In the absence of any dislocation failure mechanisms it will depend on the current density and thermal dissipation. And just like any other material, it will have to survive in a non-hermetic environment and in the presence of corrosive gasses (an issue in data centers).

To get the 10G, it’s probably kind of like a VCSEL without the grating and so current density is probably high. How well you’re able to heat sink it is going to determine how reliable it will be.

Overall I like the idea. It looks like the beachfront could work. I’d spend more time talking about and how the electrical connection works and what kind of interface to a chip would be needed.

I’d also be careful before throwing shade on laser reliability because it could backfire on you (for all reasons above).
by raihansaputra | 2025-05-28 02:12:41+00:00
i think a way to see it is MotherDuck is a service to just throw your data at at they will sort it (using duckdb underneath) and you can use DuckDB to iterface with your data. But if you want to be more "lakehouse" or maybe down the line there are more integrations with DuckLake ir you want data to be stored in a blob storage, you can use DuckLake with MotherDuck as the metadata store.
by kristopolous | 2025-05-28 02:14:32+00:00
Also I forgot to one other built on llm.

This one is a ZSH plugin that uses zle to translate your English to shell commands with a keystroke.

https://github.com/day50-dev/Zummoner

It's been life changing for me. Here's one I wrote today:

$ git find out if abcdefg is a descendent of hijklmnop

In fact I used it in one of these comments

$ for i in $(seq 1 6); do printf "%${i}sh${i}\n\n-----\n" | tr " " "#"; done | pv -bqL 30

Was originally

$ for i in $(seq 1 6); do printf "(# $i times)\n\n-----\n" done | pv (30 bps and quietly)

I did my trusty ctrl-x x and the buffer got sent off through openrouter and got swapped out with the proper syntax in under a second.
by darkteflon | 2025-05-28 02:14:49+00:00
I see what you mean, but I guess it depends on your definition of vapourware. I don’t think whether it’s publicly available is determinative. That fact that it’s called “full self-driving”, combined with the claims made about (let alone the money taken for it), and the length of time taken, render it vapourware for me. Duke Nukem Forever was the platonic vapourware, until it released as a complete product, at which point it ceased being vapourware. I don’t think anyone believes that FSD is the finished article, and those last few percent are critical where human lives are at risk. But I can see that reasonable minds may differ. It’s not a precise term.
by tantalor | 2025-05-28 02:18:37+00:00
You're missing the point. Most tools are deployed by humans. If they do something bad, we can blame the human for using the tool badly. And we can predict when a bad choice by the human operator will lead to a bad outcome.

Letting the LLM run the tool unsupervised is another thing entirely. We do not understand the choices the machines are making. They are unpredictable and you can't root-cause their decisions.

LLM tool use is a new thing we haven't had before, which means tool misuse is a whole new class of FUBAR waiting to happen.
by anonzzzies | 2025-05-28 02:21:14+00:00
Perspective right, the definition:

> software or hardware that has been advertised but is not yet available to buy,

for me, if I would've bought a Tesla, it would be vapourware for sure: Elon advertised it every chance he got and gets (this summer we will have it!), people bought it because of that and it's not there: that's vapourware.
by yallpendantools | 2025-05-28 02:22:02+00:00
What really bothers me with the article---something I think I share with top-level commenter dpkga---is throwing away perfectly fine articles of clothing (i.e., "tennis shoes"). Not to mention, expensive. These, presumably wouldn't cost a fortune to transport even overseas. I get it that maybe the student had to make a choice between, say, bulky books/notebooks/school work which may come in handy for the future but that's where the "expensive" part comes in; why even buy something expensive if there was any chance you'd discard it before its service life is up? (Other commenters have provided answers elsewhere that I consider plausible.)

The furniture (i.e., "bean bag chair") I can totally understand why they'd discard it. The only thing that bothers me then is, will they buy a similar item for next year? Because if they will, then this stuff doesn't "doesn't matter" and therefore the problem actually exists, if only because it feeds into the mindless consumer attitude which leads to over production of goods that end up in landfills if not in someone else's hoard pile.
by kcorbitt | 2025-05-28 02:22:27+00:00
It seems like the speedups here are most useful for small models, since on larger models a smaller fraction of the total time would be spent swapping between kernels? Would be interesting to see at least theoretical results for LLMs in the 14-70B parameter range, which is what most folks deploy in practice.

And of course the effect on throughput at larger batch sizes, which they allude to at the end.

Overall a very interesting result!
by analog31 | 2025-05-28 02:22:59+00:00
I live in Madison WI. Move-out weekend is called Hippie Christmas. Townspeople furnish their own apartments with stuff thrown out by the students.

I visited a friend's apartment, and he described the decor as "a mixture of TarJay and Hippie Christmas."

We also regularly leave stuff by the curb and it gets taken. Conveniently, you leave it out a day or two before trash day, and if it's not taken, then you can throw it in the trash.
by jmyeet | 2025-05-28 02:23:25+00:00
Let's look at Elon's accomplishments:

- Ousted from Paypal for pure incompetence. Made money anyway from vested stock riding the dot-com bubble;

- Bought his way into Tesla then engaged in historical revisionism to paint himself a "founder". Tesla is a weird company because it defies any fundamentals. It seems to be valued between $500k and $1M per car sold in a year, which is just ludicrous. Tesla, as a company, has only survived by government largesse, be they carbon tax credits or the DOE loan in the late 2000s that saved Tesla from bankruptcy.

The only thing propping up Tesla now is import bans on Chinese EVs. Tesla isn't a car copmpany or an energy company. It's a proxy for investing in Elon directly. When Elon's relationship with the administration inevitably sours, Tesla's fortunes will sink as well. European Tesla sales have already dropped ~50% due to brand damage. The admin has cancelled an EV credit program that Tesla relied upon.

- SpaceX. This is a success. I still contend SpaceX succeeded in spite of Elon, not because of him;

- SolarCity. Failure. This became a recurring trend as SolarCity ended up owing a lot of money to SpaceX so the Tesla buyout was basically Elon using one of his companies to rescue another of his companies that owed a ton of money to yet another of his companies;

- Twitter. This one is hilarious because he completely overpaid for it. It seems like he was goaded into buying it by Peter Thiel and tried to get out of the deal until the Delaware Chancery Court forced him to complete the sale. By all accounts its lost 70-85% of its $44B purchase price. Elon ended up raising a bunch of money for xAI and basically used that to buy out his bad investment in TWitter, which for anyone else would be corporate fraud on a massive scale.

And what does Elon do all day anyway? Because it seems all he does is pretend to be a gamer and tweets nonstops. When does he actually manage any of these companies? In fact, his tweeting actually hurts his companies, Tesla in particular.

I'm honestly surprised there's still anyone who clings to the myth of Elon given all the evidence we have to the contrary.
by dang | 2025-05-28 02:25:59+00:00
Could you please stop posting shallow dismissals and putdowns of other people and their work? It's against the site guidelines, and your account has unfortunately been doing a lot of it:

https://news.ycombinator.com/item?id=44073456

https://news.ycombinator.com/item?id=44073413

https://news.ycombinator.com/item?id=44070923

https://news.ycombinator.com/item?id=44070514

https://news.ycombinator.com/item?id=44010921

https://news.ycombinator.com/item?id=43970274

If you wouldn't mind reviewing https://news.ycombinator.com/newsguidelines.html and taking the intended spirit of the site more to heart, we'd be grateful.
by the_af | 2025-05-28 02:26:28+00:00
But there was a conceivable way (maybe not in Python) to make a `slow_add` function very generic, yet only be defined over structures where any conceivable `+` operation is defined.

You just have to say the type implements Semigroup.

Yes, this would work if the arguments are lists, or integers, or strings. And it won't pass the typecheck for arguments that are not Semigroups.

It may not work with Python, but only because it's designers weren't initially interested in typechecking.
by __MatrixMan__ | 2025-05-28 02:26:31+00:00
I enjoyed this video of [what turns out to be an unrelated] explosion: https://www.youtube.com/watch?v=Ep8XJanoFgw

At about 0:39 a pressurized tank of something does a whimsical loop-de-loop into the plume of fire and it's hard not to feel like the little guy is just having so much fun.
AskHN: Rebuild a Project with Copilot GitHub Interfaces
by solarized | 2025-05-28 02:27:42+00:00
Anyone has trying to "rebuild" a repo with copilot github interfaces? What's your experience so far ?

Long story short i can't find any satisfying pgsql web based client. So this morning i click phpmyadmin repo - "the best" web based client for mysql. I click copilot icon on the top bar.

Do chit-chat with copilot(gpt4). I prompt her to find most optimal ways to clone it into "phpPgAdmin". collaborate each steps.

I still skeptical and worried about hallucination things. But Response and technical steps are so promising.
by marcus_holmes | 2025-05-28 02:29:38+00:00
Is there even such a thing as the "science of business"? One can form a hypothesis, and then conduct an experiment, but the experimental landscape is so messy that eliminating all other considerations is impossibly hard.

For example, there's a popular theory that the single major factor in startup success is timing - that the market is "ready" for ideas at specific times, and getting that timing right is the key factor in success. But it's impossible to predict when the market timing is right, you only find out in retrospect. How would you ever test this theory? There are so many other factors, half of which are outside the control of the experimenter, that you would have to conduct the experiment hundreds of time (effectively starting and failing at hundreds of startups) to exclude the confounding factors.
by ecb_penguin | 2025-05-28 02:29:39+00:00
> I think there's a meaningful distinction between high-pressure situations at work and exams in school

Sure, in school there is no real consequence. That's why it's important. School exams are orders of magnitude easier than the real world.

> "thrives under pressure" is not a universal quality everyone is expected to have or use

School isn't intended to imbue everyone with universal qualities. Some people will excel and some wont. The ones that excel will go on to work in situations where you must thrive under pressure.

> It's a useful skill, and it's more useful to have than to not have, but the same can be said of a thousand skills

This is a different discussions then.
by landl0rd | 2025-05-28 02:30:13+00:00
Right I am not actually interested in whether it was legal under british law. My point is british law is unjust and fundamentally illiberal in this respect. Anything that wouldn't pass the Brandenburg v. Ohio test of "imminent lawless action" is unconscionably bad.

All that aside, can you explain the other 29 arrests that day so well? https://www.economist.com/britain/2025/05/15/britains-police...

This is from The Economist of all places not some right-wing rag. Please do not stick your head in the sand on this to "own the rightoids" or whatever. If you're a lefty oppose it on grounds of how it's used against the pro-palestinians.

P.S. I don't see why you're bringing up the trump admin's actions like one bad thing existing means another can't. Both things can be bad. We can oppose both things. It's not that hard.
by curiousObject | 2025-05-28 02:30:26+00:00
Agree.

The only permission the extension needed was “downloads, which normally only allows an extension to download and search for user files, not read or write to them”

That’s not an unusual permission for an attractive but safe sounding extension, for example an extension to download all images from a page

$100k at least?

The value of this to bad guys could be up to millions
by pvg | 2025-05-28 02:31:08+00:00
I guess I'm having trouble following this, what is the non-productive quagmire? It's someone's Show HN and you started grumping at them out of nowhere - that's what it looks like externally. There is no right way to do that on HN just like there isn't in most typical social contexts. You can just offer your critique without the overwrought bombast, it's what most other people do. I imagine you don't begin work emails in the style of your flagged comment.
Ask HN: Why No Crypto / Web3 links?
by kentf | 2025-05-28 02:32:31+00:00
Is there a rule against posting crypto / web3 links or is the HN community allergic to it?

I’ve been building in web3 / crypto for years now and think the depth of social and technical problems are super interesting.

Lots of other places to post but curious why no / very few crypto links here.
by 90s_dev | 2025-05-28 02:34:11+00:00
There's such a strong nostalgia among so many of us for 90s software, that I can't help but wonder if I should repurpose 90s.dev to be something much bigger than it is, something like a community that wants to recreate and share the wonder and beauty and joy of using computers in the 90s. I already planned on doing some of that with the mini os that I'm developing, with bringing back program skinning for one thing, but I think it needs to become much more official and big-picture, a community.
by rexer | 2025-05-28 02:34:20+00:00
I think this downplays the security issue. It's true that scoping the token correctly would prevent this exploit, but it's not a reasonable solution under the assumptions that are taken by the designers of MCP. LLM+MCP is intended to be ultra flexible, and requiring a new (differently scoped) token for each input is not flexible.

Perhaps you could have an allow/deny popup whenever the LLM wanted to interact with a service. But I think the end state there is presenting the user a bunch of metadata about the operation, which the user then needs to reason about. I don't know that's much better; those OAuth prompts are generally click throughs for users.
by bloppe | 2025-05-28 02:34:30+00:00
Well you're not giving the access token to Claude directly. The token is private to the MCP server and Claude uses the server's API, so the server could (should) take measures to prevent things like this from happening. It could notify the user whenever the model tries to write to a public repo and ask for confirmation, for instance.

Probably the only bulletproof measure is to have a completely separate model for each private repo that can only write to its designated private repo, but there are a lot of layers of security one could apply with various tradeoffs
by timschmidt | 2025-05-28 02:37:13+00:00
> However the program has been in development for quite a while

No longer than other rocket programs. The speed of development is frankly mind blowing considering it's scale. Regulatory hurdles seem to be the biggest delaying factor. Which goes a long way toward explaining Musk's political activities AFAICT.

> and seems to have a lot of internal issues. Be that poor management, scope creep, or whatever the process looks flawed.

It seems like you're making the mistake of equating SpaceX's hardware-rich development philosophy (i.e. just fly it and see what happens) to NASA's check-it-ten-times-before-flight risk-averse methodology. Different approaches. Russia followed the former, much like SpaceX, and Soyuz is second only to Falcon 9 in number of launches. Arguably, more can be learned, more quickly, and for lower cost following the hardware-rich approach. You just have to deal with the optics and armchair rocket engineers declaring every launch a failure until they aren't.
by suraci | 2025-05-28 02:37:59+00:00
I'm a big fan of Cold War-era thriller films

there're also some good spy films at that time, but these are not as cool as thrillers such as The Thing and Invasion of the Body Snatchers

unfortunately or fortunately, there hasn't been such brilliant films since the end of the Cold War(I like The Facult, but it is not that good)

fortunately or unfortunately, I believe that such brilliant films are about to make a comeback
by ptrj_ | 2025-05-28 02:38:16+00:00
This could also give a nice speedup for MoE models w/ total 7B-70B parameters but O(10x) fewer active params, e.g. https://huggingface.co/Qwen/Qwen3-30B-A3B, assuming the expert router can be effectively scheduled within the monolithic mega-kernel.
Show HN: AutoThink – Boosts local LLM performance with adaptive reasoning
by codelion | 2025-05-28 02:39:11+00:00
I built AutoThink, a technique that makes local LLMs reason more efficiently by adaptively allocating computational resources based on query complexity.

The core idea: instead of giving every query the same "thinking time," classify queries as HIGH or LOW complexity and allocate thinking tokens accordingly. Complex reasoning gets 70-90% of tokens, simple queries get 20-40%.

I also implemented steering vectors derived from Pivotal Token Search (originally from Microsoft's Phi-4 paper) that guide the model's reasoning patterns during generation. These vectors encourage behaviors like numerical accuracy, self-correction, and thorough exploration.

Results on DeepSeek-R1-Distill-Qwen-1.5B:

- GPQA-Diamond: 31.06% vs 21.72% baseline (+43% relative improvement)

- MMLU-Pro: 26.38% vs 25.58% baseline

- Uses fewer tokens than baseline approaches

Works with any local reasoning model - DeepSeek, Qwen, custom fine-tuned models. No API dependencies.

The technique builds on two things I developed: an adaptive classification framework that can learn new complexity categories without retraining, and an open source implementation of Pivotal Token Search.

Technical paper: https://papers.ssrn.com/sol3/papers.cfm?abstract_id=5253327

Code and examples: https://github.com/codelion/optillm/tree/main/optillm/autoth...

PTS implementation: https://github.com/codelion/pts

I'm curious about your thoughts on adaptive resource allocation for AI reasoning. Have you tried similar approaches with your local models?
by prettyblocks | 2025-05-28 02:39:38+00:00
I've been trying to maintain a (mostly vibe-coded) zsh/omz plugin for tab completions on your LLM cli and the rate at which you release new features makes it tough to keep up!

Fortunately this gets me 90% of the way there:

llm -f README.md -f llm.plugin.zsh -f completions/_llm -f https://simonwillison.net/2025/May/27/llm-tools/ "implement tab completions for the new tool plugins feature"

My repo is here:

https://github.com/eliyastein/llm-zsh-plugin

And again, it's a bit of a mess, because I'm trying to get as many options and their flags as I can. I wouldn't mind if anyone has any feedback for me.
by timschmidt | 2025-05-28 02:39:49+00:00
I notice I mis-typed and should have said you can't overstate the importance of Starlink on the development program. And I agree with you about pushing the envelope. It was really interesting to hear that they were planning on testing an engine-out scenario with this booster by lighting one of the middle 10 engines and two centers. If they can pull that off, they'll have a measurable increase in fault tolerance over Falcon 9.
by codelion | 2025-05-28 02:40:55+00:00
The motivation for AutoThink came from watching how current reasoning models waste computation - they spend the same amount of "thinking time" on "what's 2+2?" as they do on complex mathematical proofs. This seemed obviously inefficient.

The breakthrough was combining two techniques I'd been working on separately: adaptive classification (which can learn new categories without retraining) and an open source implementation of Pivotal Token Search from Microsoft's Phi-4 paper. When I put them together with dynamic token budgeting, the performance gains were much better than expected.

What surprised me most was that the technique actually uses fewer tokens on average while improving performance. The adaptive allocation means simple queries finish faster, offsetting the extra computation on complex ones.

A few technical notes:

- The steering vectors are small (typically <1MB per pattern) and add minimal memory overhead

- Classification adds about 10ms latency, which is negligible

- Target layer selection matters - I found middle layers (15-20) work best for most models

I'd love feedback on:

- Have you tried similar adaptive approaches with your models?

- What other reasoning patterns would be useful to steer toward?

- Ideas for automatically detecting the optimal target layer?

Thanks for checking it out! Happy to answer any questions about the implementation or results.
by CapricornNoble | 2025-05-28 02:41:37+00:00
It's been years since I've been to Vietnam, and I can't say I ever encountered this sub-culture. Closest was going on a few dates with a trophy-winning bachata dancer / dance instructor. But I'm not that surprised it has spread, knowing that it's "A Thing" here in Japan for ages as well.

Encountered a few other American/Caribbean sub-cultures though, like a twerk contest in a hip-hop club, and a reggae dive bar. These were 2015-2019 in Hanoi.