skysight-inc/HackerNews huggingface dataset:
I've been playing around with data extraction using OpenAI's structured outputs feature last week. Perhaps this is due to me still being fairly new to this world, but man, has it been an exercise in frustration. My general takeaway so far is that LLMs are fantastic for creative writing, and are a much harder beast to tame when you're looking for exact, reproducible answers. Even when those answers should be the most obvious ones. My engineering brain does not appreciate all the prompt engineering hacks, the hopeful JSON schema tweaking, the "let's try this other random thing just to see if it works" approach to making progress. The worst has been getting to an OK point with one of the fields, only to find out later that giving directions for another field blew away the earlier progress. I'm sure I must be missing something since there are products that are doing this, but so far I have little to show for hours spent other than growing knowledge of LLM quirks and subtle behaviors.
Compensation gets attacked in a number of ways.

Your base salary won't tend to drop but at the same time you'll get an annual 1.5% increase when inflation is 9% and the company made $300 billion in profits last year.

Bonuses for normal employees (below VP) are essentially formulaic at most big tech companies, for the most part. So if you're a senior SWE with a 15% bonus target, well that's based on yoru base salary. It hasn't gone down in nominal terms but it has in real terms.

Also, depending on your company, there's a pool of discretionary funds on top of the formula. Your bonus can even be taken away and given to someone else on the team (yes, this happens). How big is that pool? Has it increased over time? Decreased? Or stayed the same? On a per-employee basis. You don't have visibility into that unless you're a manager.

Next is stock compensation. Your initial grant is obviously known. Annual refreshes if you get them tend to be formulaic too. But what about discretionary grants? That's where the big money is. How much is being thrown around in total? Is it going up or down over time? You have no visibility into that.

All of the above have, as input, your performance ratings. There are quotas for each performance level at a certain level (usually 150+ people or director level) so not everyone gets Greatly Exceeds Expectations. What are the quotas ("target percentages") for each bucket? Has that changed over time? Some compoanies now have targets for subpar ratings (ie ratings below "Meets Expectations"). It's the pipeline for getting rid of people and getting people to do more for the same money.

So technically you have to do more now to maintain a Meets Expectation rating than you did 5 or 10 years ago. Is that a pay cut?

And then we have promotions. The typical way this works is a company will divide promotion candidates into pools. A promotion committee will essentially rank the packets they have. At a certain level there is a quota for promotions to hand out. Those get distributed to those from the top down until there are no promotions left to give out.

Companies have allegedly reduced costs by simply reducing the promotion target percentages / quotas.

And then there are all the benefits that have a tendency to get worse over time. Health sinsurance, 401k matching and less tangible benefits like food, facilities and so on.
Next episode in this is Chinese companies produces HBM3 (they are already shipping HBM2), 7nm class GPU products competitive against A100 from multiple vendors, EUV. The US will realize what a monster they created.
> And it looks like they were forced to pivot because CCP limited salaries in finance while getting no money from VCs.

Pay bankers less for increased innovation. Talk about a win-win knock-on.
Came here to mention Zoho Mail. I use Zoho to provide IMAP and SMTP mail for a webapp that required a dedicated address. Would have been like $72/year to make a whole new user in Google Workspace.
I'm not sure i agree that paid content is cool in general.
> Facts themselves are not protected by copyright.

But don't LLMs encode language, not facts?

> If there's no unauthorized reproduction/copying then it's not a copyright issue.

I'm pretty sure copyright holders have gotten the models to regurgitate their copyright works verbatim, or nearly so.
Open models have only really become useful in the last year or so and still required significant investment to build. They have still lagged behind closed models in capability. though still not matching the best models, this shows that the gap has closed significantly and the cost to produce should be much lower.

Another thing to consider is society & the market is not currently rationale, lots of wild swings, over reactions, messaging & beliefs at the extremes
If you just want the key message without clicking the link:

"The researchers estimated an extra 8,000 people would die each year as a result of “suboptimal temperatures” even under the most optimistic scenario for cutting planet-heating pollution. The hottest plausible scenario they considered showed a net increase of 80,000 temperature-related deaths a year."

It's easy to feel glib about 'some number of people dying from changes to the climate' until it impacts you and your family. Even something like flu deaths always felt a bit distant to me, until I lost and nearly lost close family due to seasonal flu.
Yes, the relatively-low cost at which it was allegedly trained.
You can add that qualifier, but nothing will enforce that objects don't overlap. So you replaced slow correct code with fast incorrect code.
For reference, this is about ~$110k for a training run to beat Dall-E 3, assuming a (somewhat expensive) $1.30/hr for an A100 40GB.

The former CEO of Stability estimated the Dall-E 2 training run cost as about $1MM: https://x.com/EMostaque/status/1547183120629342214
A response to a feeling of ineffectiveness or lack of progress can be 'I need to catch up' which can result in weekend work. That IME can be a spiral. You don't get the rest you need. You feel less effective...
I never understood this reaction the market is having. It's like reading the tea leaves - effectively random and not helpful.

I think it makes more sense if someone thinks "Gen AI is just NVIDIA - and if china has Gen AI, then they must have their own NVIDIA" so they sell.

But it makes the most sense if someone thinks "Headlines link US lead in Gen AI and NVIDIA, bad headlines for Gen AI must mean bad news for NVIDIA".

And the theoretically ultimate market analysis guru probably thinks "Everyone is wrong about Gen AI and NVIDIA being intimately linked, but that will make them sell regarding this news, so I must also sell and buy back at bottom"
played around a bit with emcee and really impressed. giving claude access to APIs and having it just work is really satisfying.

what are next steps?
Well done; will test and possibly switch. But, for me more importantly, using Racket for this is more really nice. Thanks for that.
I don't quite understand the sentiment. Lowered cost of training and inference means more companies can join the game, and therefore more demand for the hardware. Basically Jevon's paradox in play. What will more likely fall instead in the long-term should be OAI's valuation, if they don't have other killer products.
I wouldn't pick 5¢ up off the ground but I would certainly pick up $2500.
Ask HN: How big is the impact of Deepseek in shifting AI landscape?
I am reading so much content but it is still hard to make out how much impact Deepseek will have. Is it a phase or a tangential shift ?
It's a VERY realistic take based on roughly 30 years in the trenches, that's what it is.
You get rid of them: https://quoteinvestigator.com/2014/02/28/clever-lazy/
I'm harvesting credit card numbers and passwords from your site. (2018)
Facebook flags Linux topics as 'cybersecurity threats' – posts and users blocked
This just doesn't match up with reality IME.

You don't have a right to drive your car anywhere - the state can revoke it. Many states have no laws at all about how to store firearms, and the ones that do in general are pretty hostile to the idea that you have a right to bear arms in the first place. You don't have a duty to work, someone isn't morally wrong because they live off family money. And you absolutely do not have a right to a job, because a job requires someone else to pay you money. Nobody has a right to have someone else pay them money.
But it still can be done on the npm side, right?
The Fountainhead has value in that it helps teach you that there are people who think like Ayn Rand. I wouldn't say it's particularly realistic, though: there are better books to learn about the world through. (But if you read more than two or three books, you'll quickly learn the problems with Ayn Rand's worldview.)

Books aren't mutable in the same way that arguments are: you can actually sit and dissect a book, in a way that you can't dissect a politician's rhetoric or a parent's scorn. So… kinda, yes: even The Fountainhead is worth reading, to some people (not that I'd recommend it).
I played a little bit with the image generation, and I'm not sure if there was something wrong with the site or was it was some weird setting, but it was Stable Diffusion 1.5 tier generation. Not that good :\
This is an excellent article. The only thing I am missing is a short paragraph about OIDC, which is the thing that enables authentication. To most people who just get in touch with the topic OAuth is more authentication than authorization.
I don't know the one that shipped from Microsoft, but I'm going to assume it's goal wasn't to teach people how to code but rather empower non-programmers to code. Starting from that, I don't see the two would be similar.
https://news.ycombinator.com/item?id=42835019

A strong argument that it's never more than one frame's worth of latency.
All NSF panels have been cancelled until further notice
It's clearly trained to be a censor and an extension of the CCPs social engineering apparatus. Ready to be plugged into RedNote and keep the masses docile and focused on harmless topics.
In some scenarios the equation flips, and the enterprise is looking for _more_ scale.

The more bandwidth that Cloudflare needs, the more leverage they have at the peering table. As GitHub's largest repo (the @types / DefinitelyTyped repo owned by Microsoft) gets larger, the more experience the owner of GitHub (also Microsoft) gets in hosting the world's largest git repos.

I would say this qualifies as one of those cases, as npmjs is hosted on Azure. The more resources that NPM needs, the more Microsoft can build towards parity with AWS's footprint.
We may be facing the same problem in the US soon.
Otherwise known as frequency swifting
So much for "but deepseek doesn't do multi-modal..." as a defence of the alleged moats of western AI companies.

How ever many modalities do end up being incorporated however, does not change the horizon of this technology which has progressed only by increasing data volume and variety -- widening the solution class (per problem), rather than the problem class itself.

There is still no mechanism in GenAI that enforces deductive constraints (and compositionality), ie., situations where when one output (, input) is obtained the search space for future outputs is necessarily constrained (and where such constraints compose). Yet all the sales pitches about the future of AI require not merely encoding reliable logical relationships of this kind, but causal and intentional ones: ones where hypothetical necessary relationships can be imposed and then suspended; ones where such hypotheticals are given a ordering based on preference/desires; ones where the actions available to the machine, in conjunction with the state of its environment, lead to such hypothetical evaluations.

An "AI Agent" replacing an employee requires intentional behaviour: the AI must act according to business goals, act reliably using causal knowledge of the environment, reason deductively over such knowledge, and formulate provisional beliefs probabilistically. However there has been no progress on these fronts.

I am still unclear on what the sales pitch is supposed to be for stochastic AI, as far as big business goes or the kinds of mass investment we see. I buy a 70s-style pitch for the word processor ("edit without scissors and glue"), but not a 60s-style pitch for the elimination of any particular job.

The spend on the field at the moment seems predicated on "better generated images" and "better generated text" somehow leading to "an agent which reasons from goals to actions, simulates hypothetical consequences, acts according to causal and environmental constraints.. " and so on. With relatively weak assumptions one can show the latter class of problem is not in the former, and no amount of data solving the former counts as a solution to the latter.

The vast majority of our work is already automated to the point where most non-manual workers are paid for the formulation of problems (with people), social alignment in their solutions, ownership of decision-making / risk, action under risk, and so on.
One of the questions about this is that of the US’s human capital, i.e. does the US (still) have enough capable tech people in order to make that happen?
That article misses that TikTok gets effective negative feedback: they know when you don't like a video. Contrast that to the interface that YouTube cribbed from [1]. When you show people a list of ten videos on the side you can't come to any conclusion of whether or not people liked the videos they didn't click on, in fact, I'm frequently frustrated because I also wanted to watch another video that was recommended and now it's lost. If Facebook had a "dislike" button that worked that would fix many of the things wrong with it. [2]

I read many papers on "negative sampling" which is used in western recommender algorithms to guess at what you didn't like because there's no dislike button: I always thought "I can't believe it works" and fact is, it doesn't or it doesn't work very well.

My RSS reader gets a thumbs up/thumbs down and gets AU-ROC of 0.79, TikTok gets 0.84 or so and has a lot more data and 1000x the budget.

I'd almost say "throw the western recommendation literature in the trash and treat it as a classification problem [3]" except that when you have less than <1000 data points for a user there is a cold start problem. You could throw AI and the computational power of a Dyson sphere at the problem and it won't do as much as a dislike button that speaks with authority.

[1] https://montevallotimetravel.wordpress.com/2012/05/03/idiocr...

[2] would be good for people who don't like hysterical posts about politics but it's an existential threat to the advertising economy, influencers, etc...

[3] calibrated, even
Computers Should Beep More
I wish I would not already be so leveraged.
Crafting a Better Shader for Pixel Upscaling [video]
It doesn't look like it allows editing, which I found surprising for this architecture, as the recent generation of flagship LLMs mostly have this capability (GPT-4o).
I'm not saying there should be no rules but saying "you can't lay off Employee A because he has kids, you have to lay off Employee B instead because they don't" with absolutely no consideration of work product is pretty asinine on its face.

Laying people off is a business decision - forcing a company to justify that from a business context is probably a Good Thing, but injecting weird social requirements on top of that is silly.
buying an individual stock is gambling. buying an broadly-diversified index is not.
I spent the last few months interviewing at various bay area startups for senior SE roles. About half of them wanted references. This was my experience so YMMV
Hot take but 99% of all profitable businesses have no moat, and there’s absolutely nothing wrong with that. You can still make lots of $$$.

Moats matter the most to investors and maybe the C suite. For everyone else, it’s just an intellectual exercise
Hey folks - I tried to make the most comprehensive guide to API rate limiting out there. There's definitely some less explored topics like the new rate limiting header RFCs so even if you're experience with rate limiting - you might learn something new
pnpm stores them in a central place and symlinks them. You’ll see the benefits when you have multiple projects with a lot of the same packages.
I don’t really agree, because I think there’s something of a chicken-and-egg effect here.

With complex projects like these that have to work well on such a wide array of hardware and configurations, lots of real world usage is required to achieve any level of refinement. Without widespread adoption, Wayland likely would have been stuck in experimental/toy status for much longer than it will as things are going currently.
Florida's citrus outlook remains bleak. But new science offers hope
> simultaneous with learning the English terms for computational constructs

Very often these are the terms for those things. Much like things named after their inventors, or discoverers; novel concepts often borrow the word of origin of its inception. What would you call "Currying" in another language?

So I guess you could rename keyboard, with <key>-<boards> with words for each coming from your native language, but you'd still be following the convention of 'form' - that the buttons are "keys" (which in other languages may not have the same meaning where a 'key' I believe is piano terminology derived from French "clé"), and its container is a "board".

Unless your language has a handy word that is a perfect fit for the concept of "keyboard", it seems like unnecessary work for the sake of it. Even English borrows 'loan'-words, and Japanese even has a separate alphabet for them.

> neither one of those facts is a good explanation for why teaching a few foreign-language words isn't just accidental complexity in the early stages

b/c you aren't really teaching a foreign word b/c the words still need further context in English, and that is a good reason IMHO, even if you disagree. You could teach ASM mnemonics ('mov', 'div', 'cdq'..) which are also derived from English terms, and I doubt it'd be much different given how abstract the relationship to the words is, and how unusual the terms (e.g. "execute" an action isn't that common in English, outside of CS, or perhaps the military).

> gradually add complexity in levels ... you're criticizing the entire pedagogical philosophy of Hedy and of most educational institutions.

> Educators in general prioritize breaking a concept down into manageable chunks ... if you don't like it then your beef is with the entire educational philosophy

It isn't clear to me that 'English" terms are a layer of complexity on top of local terms. I'd say you are teaching jargon either way, neither of which is clearly easier to learn - I could just as well argue that using native words could cloud the issue and create misunderstandings if they don't match the programmatic meaning well.
> Claims are, this is only in the web-version

There were claims to the contrary as well in the last large thread this came up in. Allegedly, on the initial question the model would cut its chain of thought short, and when the user insists it would ponder on how give them the runaround.
Never underestimate Google's ability to fall flat on their face when it comes to shipping products.
People complain about the things they care about.

Wayland made some huge design changes, and those changes all have pros and cons. How do we tend to communicate about pros and cons? By complaining.

It sucks that Xorg's accessibility features are so baked-in that you must be compatible with them; because that demand can become a wall of assumptions. It sucks that Wayland leaves 100% of accessibility to the compositor; because that creates a lot of redundant work, and the best implementations get siloed into plasma or gnome, creating multiple smaller instances of the tight integration that made UX less flexible to begin with.

Using Xorg, you can run an incredibly lightweight window manager that never even thought about managing keymaps, adjusting mouse acceleration, setting the display resolution, etc., because that's not it's job. I can get absolutely everything I want from i3wm on Xorg... except fractional scaling. So far, it looks like plasma is the only one that has really figured that one out, and I still get a tiny pointer sometimes.

The best thing about free software is that we can choose how it works. The more tightly integrated the pieces are, the fewer choices are available. Fewer choices results in more complaining. Wayland may be the most significant instance of this pattern in Linux history. The second most significant instance was already present: Desktop Environments.

The biggest source of complaints I have is that the best aspects of plasma are trapped inside KDE. If you want the best Wayland compositor out there, you have to have it wrapped in an entire full-featured Desktop Environment.

---

Complaining is the best thing about Linux, so long as it's able to drive real change. The more stubborn and inflexible a system (and whoever designs it) is, the more disconnected complaints become. That's the real problem that deserves our attention.
I believe that is University lab level of compute, right?

It is so nice to see that you don't need tech oligarch level of compute for stuff like this.
> Ah ok, so you’re just guessing. You wrote it as if it had already happened.

That's not a generous reading. I'm saying this is what has happened historically.

Edit: the use of the words "might" and "could" made this pretty clear.

> The economy as a whole is unaffected by AI at this point.

True in terms of no marked effect on GDP. But the stock market and the broader economy are very much linked. See 2008. And the stock market is high on AI.

> I’ve heard so many claims that the Chinese government doesn’t control research or businesses like TikTok.

Even western countries tell tech companies what to do. Do you think an authoritarian government is going to do that more or less? There's a reason they didn't want to sell TikTok.
I've never been laid off, but once was part of a company that went bankrupt and was one of the last people to leave the payroll (which is like being laid off, but where your employer is dead so at least you can console yourself with being the guy turning off the lights)... That said I did a lot of laying off for that company. Almost everyone ended up much better off after a few weeks or a month or so of searching. People would rightfully worry about if their actions caused it or why me instead of ___. The truth was that it was really about spreadsheets.

For me, I ended up getting a much better job that paid 2x what I made at the bankrupt company. But the feelings of having your livelihood rug-pulled are really difficult.
Ask HN: Do You Use Foreign Keys?
The answer should be obvious, but isn't.

I'm curious to hear real-world experiences that go beyond database design 101 textbooks.
Have you faced any tradeoffs, surprises, or regrets around this decision?
Are there ethical considerations here?

We'd consider it abhorrent to do brain surgery on a person or animal, to make them more compliant, or less likely to refuse instructions.
Not making the news in western media yet is PRC claims to have started mass producing their indigenous 28nm litho (70% of global wafer use) this month... the estimated cost is 1/30th of ASML machines. Extrapolate and they're on trend of produce 14nm machines at comparable fraction cost in next few years.
I updated my terminals to play a quiet sound when they finish long-running commands, and it's saved me many hours of wasted time.

I think modern software is missing a large opportunity to use unintrusive sound in "eyes-free" scenarios---to help us get back on track.
This isn't a contest.