MurphyA/hacker-news huggingface dataset:
by impossiblefork | 2025-05-31 08:05:32+00:00
While the CEO stuff is a problem, I don't think the other stuff matters.

Per chip area WSE-3 is only a little bit more expensive than H200. While you may need several WSE-3s to load the model, if you have enough demand that you are running the WSE-3 at full speed you will not be using more area in the WSE-3. In fact, the WSE-3 may be more efficient, since it won't be loading and unloading things from large memories.

The only effect is that the WSE-3s will have a minimum demand before they make sense, whereas an H200 will make sense even with little demand.
by saubeidl | 2025-05-31 08:05:50+00:00
Except Labor in Tech is unique in that it has zero class consciousness and often actively roots for their exploiters.

If we were to unionize, we could force this machine to a halt and shift the balance of power back in our favor.

But we don't, because many of us have been brainwashed to believe we're on the same side as the ones trying to squeeze us.
by Nuzzerino | 2025-05-31 08:05:58+00:00
Complain to it enough times, remain resilient and you’ll eventually figure it out (that’s a wild card though). Or find someone who has and take their word for it (except you can’t because they’re probably indistinguishable from the ‘bot’ now according to the contradictory narrative). Iterate. Spiral. No one should have to go through that though. Be merciful.
by notyouraibot | 2025-05-31 08:07:36+00:00
So funny story, I tried using o3 for a relatively complex task yesterday, installing XCode iOS Simulator on an external SSD, it was my first time owning and using a macOS so I was truly lost, I followed everything it told me and by the end of the hour.. things got so bad that my machine couldn't even run normal basic node projects. I had to a proper fresh boot to get things working again. So yeah lesson learned.
by mrtksn | 2025-05-31 08:07:42+00:00
Does anybody knows why Google and Microsoft constantly shuffle their communication apps? Both had the opportunity to be the king but instead they seems to choose to throw away their fortunes? I still remember the times when we used Gtalk as much as MSN messenger and both of those simply disappeared slowly when mobile started dominating and those simply sit tight and did nothing. Then there were numerous replacements and alternatives by both of Google and MS but for some reason they all felt neglected and later shut down. Microsoft bought Skype only to make it worse and shut it down. Considered to buy Discord at some point eventually to abandon the bid. Any insights?
by otabdeveloper4 | 2025-05-31 08:08:28+00:00
> This leads to output that we would classify as "very boring".

Not really. I set temperature to 0 for my local models, it works fine.

The reason why the cloud UIs don't allow a temperature of 0 is because then models sometimes start to do infinite loops of tokens, and that would break the suspension of disbelief if the public saw it.
by uxcolumbo | 2025-05-31 08:08:41+00:00
I'm in the exact same situation.

I can type around 60-70 wpm with non touch typing. Same as you, often have to correct things with Backspace.

I rarely use my pinky. But with touch typing I have to use it more and it feels very unnatural.

When I have to bang out emails or any other form of text for work, I can't see myself slowing down to force sticking on the home row to learn touch typing.

I can practice in the evening. But then you essentially keep using the 'bad' way of typing while also learning the good way. Seems confusing.
by chneu | 2025-05-31 08:09:50+00:00
Staffing changes. People have to justify their jobs. People get hired to create a product, then get shuffled around then nobody cares so the product dies.

Every time there's a leadership shuffle you'll notice products get left behind and eventually retired.

This was especially true in the early-ish days of Google. https://killedbygoogle.com/
by bionhoward | 2025-05-31 08:09:51+00:00
The best place to look is HuggingFace

Qwen is pretty good and in a variety of sizes. I’d suggest this one Qwen/Qwen3-14B-GGUF Q4_K_M for you given your vram and to run it using llama-server or lm studio (might be alternatives to lm studio but generally these are nice uis for llama server), it’ll use around 7-8GB for weights, leaving room for incidentals

Llama 3.3 could work for you

Devstral is too big but could run a quantized model

Gemma is good, tends to refuse a lot. Medgemma is a nice thing to have in case

“Uncensored” Dolphin models from Eric Hartford and “abliterated” models are what you want if you don’t want them refusing requests, it’s mostly not necessary for routine use, but sometimes you ask em to write a joke and they won’t do it, or if you wanted to do some business which involves defense contracting or security research, that kind of thing, could be handy.

Generally it’s bf16 dtype so you multiply the number of billions of parameters by two to get the model size unquantized

Then to get a model that fits on your rig, generally you want a quantized model, typically I go for “Q4_K_M” which means 4bits per param, so you divide the number of billions of params by two to calculate the vram for the weights.

Not sure the overhead for activations but might be a good idea to leave wiggle room and experiment with sizes well below 16GB

Llama server is a good way to run AI and has a gui on the index route and -hf to download models

LM Studio is a good gui and installs llama server for you and can help with managing models

Make sure you run some server that loads the model once. You definitely don’t want to load many gigabytes of weights into vram every question if you want fast realtime answers
by bjackman | 2025-05-31 08:10:25+00:00
I see your point but even if your VMM is a zillion lines of C++ with emulated devices there are opportunities to secure it that don't exist with a shared-monolithic-kernel container runtime.

You can create security boundaries around (and even within!) the VMM. You can make it so an escape into the VMM process has only minimal value, by sandboxing the VMM aggressively.

Plus you can absolutely escape the model of C++ emulating devices. Ideally I think VMMs should do almost nothing but manage VF passthroughs. Of course then we shift a lot of the problem onto the inevitably completely broken device firmware but again there are more ways to mitigate that than kernel bugs.
by mdp2021 | 2025-05-31 08:10:42+00:00
> LLMs as a replacement for search

Some people expect LLMs as part of a better "search".

LLMs should be integrated to search, as a natural application: search results can heavily depend on happy phrasing, search engines work through sparse keywords, and LLMs allow to use structured natural language (not "foo bar baz" but "Which foo did a bar baz?" - which should be resistant to terms variation and exclude different semantics related to those otherwise sparse terms).

But it has to be done properly - understand the question, find material, verify the material, produce a draft reply, verify the draft vis-a-vis the material, maybe iterate...
by nothrabannosir | 2025-05-31 08:11:47+00:00
Are you referring to people who got something completely for free as "victims" because they didn't keep getting more things for free?

It's an ironic take for a comment that uses words like "disingenuous" and "clutching pearls".

Pick a lane: either emotive arguments are in, or out. Don't accuse someone of speaking nonsense in the same comment where you claim that ceasing to provide free updates to a free product is "abuse". It's one or the other.
by A_D_E_P_T | 2025-05-31 08:12:59+00:00
Do "AI Startups" even make sense?

There appears to be a pattern. Unmet need is identified: "I want ChatGPT -- but able to read PDFs" or "I want ChatGPT -- but able to do research and produce lengthy reports." Startup gets funding for this and, if they're lucky, releases a rough beta that leans heavily on the OpenAI API. Two months later OpenAI launches a better, much more polished and seamless version, which is integrated into ChatGPT itself.

I had briefly considered forming a Legal AI startup (going so far as to download the fulltext of every legal ruling ever made in the US -- something like 400GB) but then o3/DeepResearch got so good that it became apparent that there'd be little point.

Steve Hsu claims to have solved hallucinations in a customer service context, which might be the only "startup-type" idea that has a head-start over the giants.
by imtringued | 2025-05-31 08:13:30+00:00
Google isn't doing the race thing. They just pay out to whoever submits a valid submission. The people doing the racing are the submitters who want to get ahead of their competition and are stockpiling their exploits. If they were altruists, they would just submit their exploits for no renumeration. Hence the race isn't something Google is doing.

The proof of work isn't there to add a "four second race". It's to prevent ddos like spam.
by jaynetics | 2025-05-31 08:13:53+00:00
I think some more white collar jobs might be affected, not just creative ones. There is a substantial amount of jobs where the end result needs to be of a certain quality, but all context can be inferred or provided up front, and checking and correcting a result is quicker than producing it manually. Think e.g. law or translations. Translators, proofreaders, and others are already feeling the squeeze.

In other cases, like software development, there is a split between tasks of a narrow scope and those of a wide scope. Creating one-shot pieces of software is kind of a solved issue now. Maintaining some relatively self-contained piece of software might soon turn into a task for single maintainers that review AI PRs. The more the bottleneck is context tracking, as opposed to producing code, the less useful the AI. I am uncertain, however, how the millions of devs in the world are distributed on this continuum.

I am also skeptical about legal protections or unionization, as many of these jobs are quite suited to international competition.
by karlperera | 2025-05-31 08:14:04+00:00
Some of the most exciting recent discoveries in astronomy—like new exoplanets, supernovae, and even comets—have come from amateur astronomers and citizen science projects. With affordable telescopes, open data, and platforms like Zooniverse, anyone can contribute to real research. Have you participated in a citizen science project or made an unexpected discovery? What tools or communities do you recommend for those looking to get involved? Let’s discuss how the line between amateur and professional astronomy is blurring, and what that means for the future of science.
by fhd2 | 2025-05-31 08:14:08+00:00
Considering how software is increasingly made out of seperate components and services, integration testing can become pretty damn difficult. So quite often, the public release is the first serious integration test.

From my experience, this stuff is rarely introduced to save developers from typing in the code for their logic. Actual reasons I observe:

1. SaaS sales/marketing pushing their offerings on decision makers - software being a pop culture, this works pretty well. It can be hard for internal staff to push back on What Everyone Is Using (TM). Even if it makes little to no sense.

2. Outsourcing liability, maintenance, and general "having to think about it". Can be entirely valid, but often it indeed comes from an "I don't want to think of it" kind of place.

I don't see this stuff slowing down GenAI or not, mainly because it has usually little to do with saving time or money.
by madaxe_again | 2025-05-31 08:14:12+00:00
When steam engines came along, an awful lot of people argued that being able to pump water from mines faster, while inarguably useful, would not have any broad economical impact. Only madmen saw the Newcomen engine and thought “ah, railways!”. Those madmen became extraordinarily wealthy. Vast categories of work were eliminated, others were created.

I think this situation is very similar in terms of the underestimation of scope of application, however differs in the availability of new job categories - but then that may be me underestimating new categories which are as yet as unforeseen as stokers and train conductors once were.
by blensor | 2025-05-31 08:15:37+00:00
Is this meant as a joke or a serious argument?

I personally find the original code just as if not more readable than the static lookup table and I don't need to count out the elements if I want to know how often it will retry.

But more importantly, changing the max retries is trivial in the original code and tedious in the static lookup table, especially for bigger changes.

Also, this is something you most likely want to make configurable to adapt to certain scenarios which is not possible with a static table

There are more reasons against it but those are the the main ones that jump at me right away
by whatnow37373 | 2025-05-31 08:15:50+00:00
No matter how you twist it at some point two consciousnesses differentiate on some contradictory issue maybe not name, but surely they differ on some issue otherwise they wouldn’t be .. different consciousnesses. Life as a human moves and is narrated as a single story, not the story of a thousand processes.

If that were true I can call my heart a process, my liver, etc. They are in a way part of me but they do not just ex nihilo cohere into a single narrative. That is an active process and whatever does that is the only really interesting one (IMO). So I think there might be a bunch of processes, sub personalities maybe, but there remains the problem of integration. Whatever integrates is the one that really fascinates me.

Anyway, thanks for indulging me. It is hard to go into any depth in this medium. I think you have really interesting ideas. Have a nice weekend.
by bjackman | 2025-05-31 08:16:57+00:00
> Android

Exactly. Android pulls this off by being extremely constrained. It's dramatically less flexible than an OCI runtime. If you wanna run a random unenlightened workload on it you're probably gonna have a hard time.

> Micro Kernels would do just as well.

Yea this goes in the right direction. In the end a lot of kernel work I look at is basically about trying to retrofit benefits of microkernels onto Linux.

Saying "we should just use an actual microkernel" is a bit like "Russia and Ukraine should just make peace" IMO though.
by keiferski | 2025-05-31 08:18:00+00:00
Levels. I think we are somewhere between 2 and 3?

1. YC startups target consumers. (B2C)

2. YC startups target businesses. (B2B)

3. YC network becomes large enough that startups can exist purely to serve other YC startups. (B2YC)

4. A new accelerator is launched which aims to fund YC companies that serve other YC companies. (YC4YC)

5. ?

Mostly joking, but I do sometimes look at the social media accounts of people in YC / Silicon Valley and wonder if they are living in an increasingly insular world. I think they would benefit from stepping outside of that into the greater world economy more deliberately.
by aloha2436 | 2025-05-31 08:18:33+00:00
> Why make source available at all if you are just going to release proprietary software?

Because there's years between one decision and the other, and in that time it turned out that because the software was open source they were structurally disadvantaged versus large cloud providers in being able to make money from it.

It seems disingenuous to suggest that the open sourcing was in bad faith given it happened years and paradigms apart from the closed sourcing, even though I don't agree with the decision either.
by tmtvl | 2025-05-31 08:18:38+00:00
Yes.

To be specific, it is data. It can also be code when placed in a context where code is expected (for example in the REPL).

If taken as code and evaluated it will probably raise some kind of exception (saying that '1' isn't a function). Saying that it isn't code because it raises an exception would be an interesting take, considering something like...

(sqrt "Hello, World!")

...would also raise an exception (something about wanting a number and getting a string) when evaluated, yet I doubt many people would argue that it isn't code.

Data can also be taken literally, as is the case when macros get involved. We do that every time we define a function, for example:

(defun square (x) (declare (type Number x)) (* x x))

In this case the argument x is passed through a list which doesn't get evaluated as code.

And of course you can have conditional evaluating of data as code, which still makes it code even though it doesn't necessarily get evaluated:

(define (may-error quote-the-thing) (if quote-the-thing (quote (1 2 3)) (1 2 3)))

...which will only evaluate the literal list (1 2 3) when the may-error function is passed a boolean false value.
by nevi-me | 2025-05-31 08:19:05+00:00
How about when you have to communicate with people? I had a terrible handwriting as a child at school, and I liked how the girls' handwriting was often very neat, so one year I decided to reteach myself how to write.

My handwriting became neater, but much slower. I never recovered the speed, so this bit me in university. I used to joke that I never finish exams, so I make sure that everything I write is correct. I'd always do better than people who finished the whole exam.

I was introduced to computers late in life, at 16 in the early 2000s. When I got to university, typing was a struggle. One day I saw someone typing fast. I decided to learn.

I think for me, the biggest benefit is mostly when writing long messages, more than typing. Having most conversations async at work means fewer pauses between reading and replying.

It also sometimes looks silly watching someone play hide and seek with their keyboard, because I've met people who punch in a few jets, then go hunting for others as if they've moved position.
by verisimi | 2025-05-31 08:19:13+00:00
> Language models are not designed to know things, they are designed to say things - that's why they are called language models and not knowledge models.

This is true. But you go to Google not to 'have a chat' but ostensibly to learn something based in knowledge.

Google seem to be making an error in swapping the provision of 'knowledge' for 'words' you'd think, but then again perhaps it makes no difference when it comes to advertising dollars which is their actual business.
by madaxe_again | 2025-05-31 08:19:15+00:00
> Because you can't offshore your clogged toilet or broken HVAC issue to someone abroad for cheap on a whim like you can with certain cases in tech.

Yet. You can’t yet. Humanoids and VR are approaching the point quite rapidly where a teleoperated or even autonomous robot will be a better and cheaper tradesman than Joe down the road. Joe can’t work 24 hours a day. Joe realises that, so he’ll rent a robot and outsource part of his business, and will normalise the idea as quickly as LLMs have become normal. Joe will do very well, until someone comes along with an economy of scale and eats his breakfast.
by anthk | 2025-05-31 08:19:26+00:00
On Forth, there's the philosophy of the fixed point:

https://www.forth.com/starting-forth/5-fixed-point-arithmeti...

With 32 and 64 bit numbers, you can just scale decimals up. So, Torvalds was right. On dangerous contexts (uper-precise medical doses, FP has good reasons to exist, and I am not completely sure).

Also, both Forth and Lisp internally suggest to use represented rationals before floating point numbers. Even toy lisps from https://t3x.org have rationals too. In Scheme, you have both exact->inexact and inexact->exact which convert rationals to FP and viceversa.

If you have a Linux/BSD distro, you may already have Guile installed as a dependency.

Hence, run it and then:

scheme@(guile-user)> (inexact->exact 2.5) $2 = 5/2 scheme@(guile-user)> (exact->inexact (/ 5 2)) $3 = 2.5

Thus, in Forth, I have a good set of q{+,-,*,/} operations for rational (custom coded, literal four lines) and they work great for a good 99% of the cases.

As for irrational numbers, NASA used up 16 decimals, and the old 113/355 can be precise enough for a 99,99 of the pieces built in Earth. Maybe not for astronomical distances, but hey...

In Scheme:

scheme@(guile-user)> (exact->inexact (/ 355 113)) $5 = 3.1415929203539825

In Forth, you would just use

: pi* 355 133 m*/ ;

with a great precision for most of the objects being measured against.
by izacus | 2025-05-31 08:20:24+00:00
I don't think they can hear you over record breaking profit and stock price.

Capitalism doesn't measure itself in "embarassement" or your opinion, it measures via cold hard cash. And Google has been making boatloads of it year after year after year.

Until that changes, a C-suite won't self reflect. They're "winning", aren't they?
by hsbauauvhabzb | 2025-05-31 08:21:48+00:00
For those that don’t know, Taylor Swift re-released her albums as ‘Taylor’s Version’, same music, just reproduced entirely from scratch due to (afaict) a licensing dispute with the original owner. Her fan base are pretty loyal and knowledgeable so presumably they would prefer the new version over the original. This would cause the originals to dump in value at which point she can pick them up for pennies.

My curiosity is why she even chose to buy them back, aside from maybe a defensive business move (to stop them licensing the tracks to movies at very cheap prices just to spite her, for instance).
by A_D_E_P_T | 2025-05-31 08:22:32+00:00
Thing is, OpenAI/Anthropic/etc. are demonstrably taking up those ideas. There actually were (are?) AI PDF reader startups and AI research assistant startups. (And AI coding startups, AI video startups, image analysis startups, etc.)

"AI startups," if they make sense, seem to have a very short shelf-life. They're either overtaken by the continuing improvement in LLM context windows, or, if there's a real and general unmet need for what they offer, the giants will tend to integrate it.
by simianwords | 2025-05-31 08:22:37+00:00
In such discourse I never see discussion on this:

There is no doubt that LLMs have gotten more accurate as newer models were released. At what point should we say "look this is accurate enough to be useful"?

We should acknowledge that nothing is ever 100% accurate. You won't go to a doctor expecting 100% accuracy. You know that the doctor's accuracy is high enough for the effort of making an appointment, listening to them to be worth it. Maybe they are 60% accurate?

My point is that LLM's are maybe at 20-30% accuracy where the benefit clearly exists even if we collectively acknowledge that 20-30% is not that high.

I find it amusing to think about an LLM that is 1% accurate (which could have been achieved way earlier in 2010's). What could have been possible with such an LLM with the right mindset?
by keiferski | 2025-05-31 08:24:23+00:00
Yes, they do, because ultimately software UI is what gets regular people to use things.

To a technical user there may be little/no difference to you between prompt engineering into a chat box vs. clicking a button with premade text slots.

But to the average non-programmer, a chat app like ChatGPT is somewhat pigeonholed into the chat format, and so use cases that don’t lend themselves to this interface will be outcompeted by specific apps that do.
by moralestapia | 2025-05-31 08:24:34+00:00
>Their CEO is a felon who plead guilty to accounting fraud [...]

Whoa, I didn't know that.

I know he's very close to another guy I know first hand to be a criminal. I won't write the name here for obvious reasons, also not my fight to fight.

I always thought it was a bit weird of them to hang around because I never got that vibe from Feldman, but ... now I came to know about this, 2nd strike I guess ...
by pera | 2025-05-31 08:24:40+00:00
You are being downvoted but I think you are correct: I'm not sure I could name a single company that came out from YC in the past 10 years, which makes think that YC was essentially pg, and I'm not a fan of him but he was obviously a very talented business person and had a really good eye for startups.

YC's leadership nowadays seem to lack of any kind of vision and just follows whatever shiny tech is currently in vogue, which is a huge red flag for accelerators.