skysight-inc/HackerNews huggingface dataset:
> You've way overshot the mark here.

Nah, I'm just having fun.

>You cite fear but that's attempting to have it both ways.

Huh?

>In the context of the quote precision is called for.

Because we must make it explicit that AI is not conscious? But why?

Since you can only ever measure impacts on reality -- what difference does it make to you if there's a consciousness that's causing them or not?

>It's called "an aggregate."

An individual is conscious. Does it follow from this that the set of all individuals is itself conscious? I.e. do you say that it's appropriate to model humanity as sort of one giant human?
I believe that too is as the author wrote – like a disheartening number of things in the tech industry, there are no real standards around what on-call responsibilities look like. Each organization is free to set things up in whichever way suits their tastes, and the resulting practices vary widely as a result.
One man's "plausibility" is another person's "barely reasoned bullshit". I think you're being generous, because LLMs explicitly don't deal in facts, they deal in making stuff up that is vaguely reminiscent of fact. Only a few companies are even trying to make reasoning (as in axioms-cum-deductions, i.e., logic per se) a core part of the models, and they're really struggling to hand-engineer the topology and methodology necessary for that to work roughly as facsimile of technical reasoning.
Coffee enemas probably won't detox your system – more likely to cause damage
My setup is not as professional as yours, but I bought the "diva light" ring light and put my camera in the middle of it. I swear it makes me look 10 years younger and people say I look like a supermodel on calls which is really funny. The key is to put the camera and screen up high so you're looking upwards, which makes it a flattering angle for jawline.
This is true, but it doesn't mean that it decided those first 25 without "considering" whether those 25 can be afterwards continued meaningfully with further 25. It does have some internal "lookahead" and generates things that "lead" somewhere. The rhyming example from the article is a great choice to illustrate this.
LLMs are better at formally verifiable tasks like coding, also coding makes more money on a pure demand basis so development for it gets more resources. In descriptive science fields, it's not great because science fields don't generate a lot of text compared to other things, so the training data is dwarfed by the huge corpus of general internet text. The software industry created the internet and loves using it, so they have published a lot more text in comparison. It can be really bad in bio for example.
Funny how most of the counter comments here used the form "my experience is different/it's amazing!" and then listed activities that are completely different from what Sabine listed :)

We really should stop reinforcing our echo bubbles and learn from other people. And sometimes be cool in the face of criticism.
The fact that it is possible to cheat means the king has no clothes.
https://cloud.gov/docs/overview/what-is-cloudgov/ is the key page. Seems like they want to have a centralized place where they do the PaaS work across the govt. Let’s see if this ends up being more or less cost effective than what contractors deploy to GovCloud today.
Did you find anything interesting?
I have the Scarlett audio version. It works fine. However, I played around swapping my mics with the $1200 Sound Devices Pre2, and it just sounds amazing. I'm not sure what is going on inside that box. I haven't been able to justify that purchase.
And now spotlight defaults to the whole computer even when I start a search within a folder... for items in the folder... Turned to garbage sometime in the last ~18-24 months.

At least there's quicksilver
except that the chips in TI's calculators were low-power Z80 clones

So? That's like saying "there are no 8051s because Intel doesn't make them", even tho there are millions if not billions of clones made every year (since you'll undoubtedly say "well I haven't seen one", if your car tells you when your tire pressure is low, there's 4 8051s).
In a sane country this would be a crime. But here we are..
Popular in:

2023 (277 points, 44 comments) https://news.ycombinator.com/item?id=37842863

2023 (518 points, 88 comments) https://news.ycombinator.com/item?id=36025611

2021 (993 points, 166 comments) https://news.ycombinator.com/item?id=26100075

2017 (333 points, 46 comments) https://news.ycombinator.com/item?id=13983212

2015 (170 points, 31 comments) https://news.ycombinator.com/item?id=9445692

2013 (245 points, 49 comments) https://news.ycombinator.com/item?id=5241220
In TSV as commonly implemented (for example, the default output format of Postgres and MySQL), tab and newline are escaped, not quoted. This makes processing the data much easier. For example, you can skip to a certain record or field just by skipping literal newlines or tabs.
Leetcode style questions no longer work. If it's solvable with a few functions within 1 hour, AI will solve it in 5 minutes.

If the job is cutting trees, you can't measure them by how long they take to cut a tree, but whether they have stamina to cut through multiple trees.

Take home assignments work, and the good news is they can be shorter now. 1 day or 4 hours of work is enough of a benchmark. Something like a Wordle clone is about the right level of complexity.

Things we look for:

1. Do they use a library? Some people are a bit egoistic about doing things the easy way. GenAI will make a list of words, which is both wasteful and incomplete when they can find a dictionary of words. Do they cut down the dictionary to the right size? It should only be the words not definitions.

2. Architecture? What do they normally use? How do the parts link to one another? How do they handle errors?

3. Do they bring in something new? AI will usually use a 5 year old tech stack unless you give it a specific one, because that's around the average of code it's trained on. If they're experienced enough to tell AI to use the new tech, they're probably experienced enough.

4. Require a starting commit (probably gitignore) and ask them to add reasonable sized commits. Classic coding should look a bit like painting. Vibe coding looks like sculpting, where you chip bits off. This will also catch more critical cheating, like someone else doing the work on their behalf - the commits may be from the wrong emails or you'll see massive commits where nothing gets chipped off.

5. There are going to be people who think AI is a nuisance. Tests like this will help you benchmark the different factions. But don't give them so much toil that it puts the AI users at a large advantage and don't give overly complex "solved" questions that the AI can just pull out from training.
RachelByTheBay: Atop issue is just a bug
The Register: "In summary, there was a bug in atop that allowed unrelated programs to cause the atop command to fail, and to crash in more than one way. This sort of behavior should not occur and typically signals a deeper problem. This kind of unexpected behavior is the stuff of which security exploits are made. That doesn't necessarily mean this was an actual viable exploitable flaw - there's no evidence of one, so far - but it was a weird little bug, and that's a bad thing."
Really appreciate your team's enormous efforts in this direction, not only the cutting edge research (which I don't see OAI/DeepMind publishing any paper on) but aslo making the content more digestible for non-research audience. Please keep up the great work!
It might not be an LLM problem, but it’s an AI-as-product problem. I feel like every major player’s gamble is that they can cement distinct branding and model capabilities (as perceived by the public) faster than the gradual calcification of public AI perception catches up with model improvements - every time a consumer gets burned by AI output in even small ways, the “AI version of Siri/Alexa only being used for music and timers” problem looms a tiny, tiny bit larger.
For a good visual on how much lighting helps check out youtuber Hannah Poston's "Why do I look so young" where she shows herself with and without her lighting setup: https://youtu.be/S9TTLmTZnf4?si=gJoSCwWK8bg2rerL&t=41
You are talking about Google, but I wish at least Signal made the delivery receipts optional (or do away with them).

It's been proposed a number of times, but I don't think there has been any response from Signal.
At least they cared. I found an enumeration attack on an Australian referral service where phone numbers were keys and it returned way too much personal information. Responsibly disclosed numerous times, LinkedIn contacted employees. Not even acknowledged and at last check, still open vulnerability.
What issues would TSV have? As commonly implemented (for example, the default output format of Postgres and MySQL), in TSV, tab and newline are escaped, not quoted.
But you are just proving WeylandYutani’s point. You can make good money outside the US (ex. Switzerland, Singapore, etc) but because your preconceived notion you don’t even look at the evidence. I won’t be arguing on the definition of ‘perfect’ which is highly subjective.
Apple is annoyingly doing an AI sequoia.
More importantly it can be blamed on the fraudster, and acountability for who missed the fraud is no longer traceable.
happy user here. atuin coupled with z has made it so much easier to be productive across multiple projects (especially less frequently accessed ones). just "z project" and then Ctrl+r twice to see the most recently used commands in that directory.
I saw someone saying 80% of doctors believe that LLM's are trustworthy consultation partners.

Code created by LLM's doesnt compile, hallucinated API's.. invalid syntax and completely broken logic, why would you trust it with someones life !
Yes. Simply, and well put.
I personally think that it is reasonable to "want" an Apple notebook. They have great hardware, great battery life and an ecosystem where every device integrates. Only on macOS you can nicely develop software for iOS. Furthermore most vendors release software for macOS, while they don't for Linux (not only Adobe). BTW the apps I miss most on Linux is the Preview App and Apple Mail.

However I'm done with Apple. I think it's a decision - not "reasoning". That decision takes time and is painful. It's also a decision specifically against "the best" ecosystem available in favor of something "ok".

Not only they repeatedly disappointed my expectations - they just suck as a company (in my opinion). It's not about being less innovative for decreasing software quality, they have done so much for the market, that I think GNOME wouldn't even exist as it is without them... Its about sealing off every inch of their software and hardware they can. No repair without paying... Making RAM and SSD upgrades ridiculously expensive, you cannot even put default NVMe drives into a mac mini - everything is proprietary. Even their sensors have serial numbers to prevent hibernating if you change them out without "hacking" the firmware.

Hardware-wise I have high hopes for framework working with AMD - although they did not address the issues I'd suggest (speakers, lpcamm2), they're constantly improving without breaking their promises. This is hopefully not going to change when they get bigger.

OS-wise I'll stay on Linux. After a long journey going from Ubuntu to Debian to Fedora using GNOME, KDE and even NixOS with Hyprland for a short period, I gained enough knowledge required to really enjoy Linux. System76 is working on COSMIC, which could be pretty amazing, once it is released.

In case anyone would like to try my current Linux config, I'm constantly working on an "install everything" script (pretty early stage):

https://github.com/sandreas/zarch

HF ;)
Of course you'd be confused if your transform a list of basic fails people complain about into

> And people are like, "Wah, it can't write code like a Senior engineer with 20 years of experience!"

But LLMs should be good enough to resolve this confusion, ask them!
would you rather the LLM make up something that sounds right when it doesn't know, or would you like it to claim "i don't know" for tasks it actually can figure out? because presumably both happen at some rate, and if it hallucinates an answer i can at least check what that answer is or accept it with a grain of salt.

nobody freaks out when humans make mistakes, but we assume our nascent AIs, being machines, should always function correctly all the time
> The biggest thing I've found is that if you give any hint at all as to what you think the problem is, the LLM will immediately and enthusiastically agree, no matter how wildly incorrect your suggestion is.

I'm seeing this sentiment a lot in these comments, and frankly it shows that very few here have actually gone and tried the variety of models available. Which is totally fine, I'm sure they have better stuff to do, you don't have to keep up with this week's hottest release.

To be concrete - the symptom you're talking about is very typical of Claude (or earlier GPT models). o3-mini is much less likely to do this.

Secondly, prompting absolutely goes a huge way to avoiding that issue. Like you're saying - if you're not sure, don't give hints, keep it open-minded. Or validate the hint before starting, in a separate conversation.
Dupe (197 points, 1 day ago, 86 comments) https://news.ycombinator.com/item?id=43485980
The same reason people write C++ instead of better^TM alternatives.

Pick the tool you already know and focus on solving the problem.
Canada’s COL is an exception.

Wages are about half of the US yet in places like Toronto the COL is super high.

These profs likely negotiated a fat payday. It happens all the time - profs move from Harvard, Stanford, Yale to less prestigious schools because they’ll get something they otherwise can’t get - tenure, head of a school, more money, whatever.

Considering this move would have taken months to negotiate it likely has nothing to do with politics at all.
Huh, wonder if that’s a common thing. I had someone walk down the stairs in a huff, only to teleport back and smack someone in the face :)
i use the open source Glider frontend on Android and it shows related posts automatically. recommended.
I think this is the one where they train LLM without NVIDIA GPU's.
I don't buy it. Or rather, I am willing to believe that some team at Apple has convinced itself that this makes sense, but they're wrong.

In particular, the security boundaries are nonsensical. The whole model of "notarization" is that the developer of some software has convinced Apple that the software as a whole (not a specific running instance) is worthy of doing a specific thing to the system as a whole.

But this is almost useless. Should Facebook be allowed to do various things that can violate privacy and steal data? What if the app has a valid reason to sometimes do those things?

Or, more egregiously, consider something like VSCode. I run it, and the fancy Apple sandbox helpfully asks me if I want to grant access to "Documents." The answer is really "no! -- I want to grant access to the specific folders that I want this workspace to access", but MacOS isn't even close to being able to understand that. So instead, one needs to grant permission, at which point, the user is completely pwned, as VSCode is wildly insecure.

So no, I really don't believe that MacOS's security model makes its users meaningfully more secure. At best, the code signing scheme has some value for attribution after an attack occurs, but most attacks seem to involve stolen credentials, and I bet a bunch just hijack validly-notarized-but-insecure software a la the VSCode example.
> no professional ML engineer/team/org today that ships and ML product "at scale" gives a fuck about SVMs or graphical models or bayes nets or kernel methods.

There’s a reason why “AI is just statistics” became a meme: a lot of places do use textbook machine learning techniques and dress it up as AI. Yes deep learning will win with enough data but few companies have that luxury.
I understand how developers can come to this conclusion if they're only using local models that can run on consumer GPUs since there's a time cost to prompting and the output is fairly low quality with a higher probability of errors and hallucinations.

But I don't understand how you can come to this conclusion when using SOTA models like Claude Sonnet 3.7, it's response has always been useful and when it doesn't get it right first time you can keep prompting it with clarifications and error responses. On the rare occasion it's unable to get it right, I'm still left with a bulk of useful code that I can manually fix and refactor.

Either way my interactions with Sonnet is always beneficial. Maybe it's a prompt issue? I only ask it to perform small, specific deterministic tasks and provide the necessary context (with examples when possible) to achieve it.

I don't vibe code or unleash an LLM on an entire code base since the context is not large enough and I don't want it to refactor/break working code.
Too many don't knows, when they should they are stupid

Too little don't knows and end up being wrong, an idiot.
I don’t follow every rule in the world and don’t expect anyone else to either.

It’s a risk using AI in a job interview situation like you describe and if I thought the risk was worth the reward I might do it.

I mean maybe there’s some very small number of classified/protected data situations (not just “these are our sales numbers and are private”) where I think maybe the integrity component actually matters.

But if it’s just some random job that doesn’t like people using AI for some bogus reason, give me a break. They can make the rules as easily as people can break them.

The school thing isn’t that different except for the risk and the reward. The risk is higher the closer you are to graduation and the reward isn’t that great since colleges are so easy these days that you almost certainly don’t need to do anything against the rules to graduate.
For those that support Trump, where is the line? Is this not outright corruption you'd usually see in 3rd world countries?

I'm genuinely curious - I'm not from the US and don't keep up with your politics - how normal is this?
I found it interesting too, not sure why you're being downvoted.
He spouted every kind of hateful shit, and surrounded himself with even more vile shitstains. Every terrible thing imaginable was put on the table. Some Americans may not have liked the alternative but this election was never about “better” or more tolerable” or any thing else except shortsighted hate.

Reap what you so, this turd sand which does what it said on the tin.
>Because, you know, you already shipped with it ... must not be that bad.

This hits right in the feels of any engineer at any company.
> It is advertised as an autonomous software developer

By a few currently niche VC players, I guess. I don't see Anthropic, the overwhelming revenue leader in dollars spent on LLM-related tools for SWE, claiming that.
> As for coding, it took a friend of mine three days to go from a cold start with zero dev experience to creating a usable PDF editor with a basic GUI for a specific small set of features she needed for ebook design.

This is actually an interesting one - I’ve seen a case where some copy/pasted PDF saving code caused hundreds of thousands of subtly corrupted PDFs (invoices, reports, etc.) over the span of years. It was a mistake that would be very easy for an LLM to make, but I sure wouldn’t want to rely on chatgpt to fix all of those PDFs and the production code relying on them.
> Wah, it can't write code like a Senior engineer with 20 years of experience!

Thank goodness for that too. I want it to help me with my job, not replace me.
The Fledge: Lansing community center is helping break the cycle of poverty
Mostly because if you try and visit the page that the image was supposedly on, it won't actually be there.
What Is an AI Gateway: Differences from API Gateway
> The biggest issue I had migrating as a Photoshop user since 1996 was the key bindings

RIP GIMPshop https://en.wikipedia.org/wiki/GIMPshop
> This is moot with LLMs. There is no laziness or competing incentive for them.

The incentives for the LLM are dictated by the company, at the moment it only seems to be 'whatever ensures we continue to get sales'.
I hope they roasted the rest of the pig and had a goodbye feast.
They build arguably the best 3d printers out there. If you run a business that relies on 3d printing, they are the main game in town if you want reliability and consistency.

My X1C is completely cut off from the internet, it just talks over LAN to my computer and I send it jobs, I never setup any sort of account with Bambu - never really needed anything more than that.

I don’t myself have the same sort of xenophobia towards Chinese products that many other people have, but I do like to buy local when I can. There just aren’t really any American companies (or companies anywhere honestly) producing products at the level that they are for 3d printing. If something comes along, I’d be happy to try it out.
Just noticed that I was sharing my entire Safari, Spotlight and Siri search history in that menu. Why is that setting in Spotlight settings and not under Privacy/Analytics?
I have found this old comment:

* Battery life is a lie, especially since it drains almost as much battery closed as it does open.

...

Overall, I think I am probably going to switch back to a macbook after this, not being able to go a day without charging and your laptop always being on low battery is a bit anxiety inducing.

https://news.ycombinator.com/item?id=38206173
> It isn't ruminating over, say, a five word sequence and then outputting five words together at once when that is settled.

True, and it's a good intuition that some words are much more complicated to generate than others and obviously should require more computation than some other words. For example if the user asks a yes/no question, ideally the answer should start with "Yes" or with "No", followed by some justification. To compute this first token, it can only do a single forward pass and must decide the path to take.

But this is precisely why chain-of-thought was invented and later on "reasoning" models. These take it "step by step" and generate sort of stream of consciousness monologue where each word follows more smoothly from the previous ones, not as abruptly as immediately pinning down a Yes or a No.

But if you want explicit backtracking, people have also done that years ago (https://news.ycombinator.com/item?id=36425375).

LLMs are an extremely well researched space where armies of researchers, engineers, grad and undergrad students, enthusiasts and everyone in between has been coming up with all manners of ideas. It is highly unlikely that you can easily point to some obvious thing they missed.