skysight-inc/HackerNews huggingface dataset:
Does anyone know what hardware inference can run on or memory requirements?
Agreed. It seems like a completely garbage analysis.
What Is Programming?: Your Journey from Idea to Reality
Especially since I'll probably spew as soon as I taste the Aspartame!
So even though there has been small incremental progress at most in the last 30 years and your mentor's predictions were wildly wrong about how much easier anything would become, you still think "AI" will give you the power of 50 programmers?
I suspect this is related to a lot of people using IF to gorge on unhealthy foods. They openly brag about it on forums and social media.

Having high glucose, saturated fats, and insulin for 8hs can't be good for your body. People love magic solutions.

I suspect a similar effect will happen with Gen Z junk food vegans.

https://www.mayoclinic.org/diseases-conditions/heart-disease...
Ah, that makes sense, thanks. A legend or even sentence explaining that somewhere in the article would've been great.
They're used rarely these days, but in some places they're busy enough that they will make have someone making the drinks and marking them.

Which is why they don't have to indicate "sprite" or "orange" because you can see the color through the lids.

Where drinks are self-serve they're not needed, but usually still exist.
They have quite a few in Houston, only the 4th largest metro area in the US.
People like to believe in medical "certainty". This kind of headline is just a symptom of that. All this headline really means is that it has failed to find where the abnormalities are, but we translate not finding brain abnormalities, to there being none. This is why you need to be your own advocate when it comes to your health, you can't allow yourself to be talked down because some arbitrary test tells you you're not experiencing what you are. Unfortunately, most people only find this out the hard way.
On my machine, the complier constant-folds the multiplication, producing a single-precision add for `mul_as_float` and a convert-t-to-double, double-precision-add, convert-sum-to-single for `mul_as_double`. I missed the `+=` in your original comment, but adding a float to a double does implicitly promote it like that, so you'd actually need:

t += (float)((double)0.02f * (float)17);

to achieve the "and then converting the result [of the multiplication] to float" (rather than keeping it a double for the addition) from your original comment. (With the above line in mul_as_double, your test code no longer finds a counterexample, at least when I ran it.)

If you ask for higher-precision intermediates, even implicitly, floating-point compliers will typically give them to you, hoped-for efficiency of single-precision be damned.
MIR comes from the Rubyverse and isn't related to LLVM MLIR.

https://github.com/vnmakarov/mir?tab=readme-ov-file#mir
Discussing the Disappearance of Trust
Is zero trust the path to zero truth?
> "Reality is that which, when you stop believing in it, doesn't go away" —PKD
Looks like a wrapper on top of a couple of popular Huggingface libraries. All the heavy-lifting is done with TRL, Transformers and PEFT.
Reminds me of studies showing the early retirement results in earlier death, without accounting for people who had to retire early because of poor health.
Why even do a study if you're going to do that? I've seen a few studies that just fail to account for really basic stuff.

Why?
Thank you EU!
Really great project, just wish nested tasks or sub-tasks was easier to interact with.
> You'll see notices everywhere because increasingly AI will be used in all parts of the content creation pipeline.

Which would be OK with me, personally. Right now, those cookie banners do serve a valuable function for me -- when I see them, I know to treat the site with caution and skepticism. If AI warnings end up similar, they too will serve a similar purpose. It's all better than nothing.
> You, not a boss, will own the code.

Developers can already deploy code on massive infrastructure today, and what do we see? Huge centralization. Why? Because software is free-to-copy winner-takes-most game, where massive economies of scale mean a few players who can afford to spend big money on marginal improvements win the whole market. I don't think AI will change this. Someone will own the physical infrastructure for economies-of-scale style services, and they will capture the market.
> American Heart Association which i thought was pretty reputable

The same association that says soybean oil and cheerios are good for you
>almost all animals in wild live longer

I seriously have to ask if you're an LLM trained to spout BS?

I would like you to drop the source of your 'wild vs zoo' statistics? If need be, expand that into wild vs general captivity. Here, let me do it for you...

https://www.nature.com/articles/srep36361

>We found that mammals from zoo populations generally lived longer than their wild counterparts (84% of species). The effect was most notable in species with a faster pace of life (i.e. a short life span, high reproductive rate and high mortality in the wild) because zoos evidently offer protection against a number of relevant conditions like predation, intraspecific competition and diseases.

I generally don't go out of my way to call out peoples BS, except in this case you're spouting things that are potentially dangerous to others. Don't go drinking out of puddles your dog does. I've seen dogs eat out of hot trash cans and be fine. Also I've seen dogs eat small chocolate bars and die. Trying to guess the quality of your water on the longevity of your dog is a great way to end up with brain cysts.
> The question is not about what AI can do today but what we assume AI will be able to do tomorrow.

And I think many assumptions on this front are products of magical thinking that are discarding limitations of LLMs in favor of waiting for the intelligence to emerge from the machine, which isn't going to happen. ChatGPT and associated tech is cool, but it is, at the end of the day, pattern recognition and reproduction. That's it. It cannot invent something not before seen, or in our case here, it cannot write code that's never been written.

Now that doesn't make it useless, there's tons of code that's being written all the time that's been written thousands of times before. But it does mean depending what you're trying to build, you will run into it's limitations pretty quickly and have to start writing it yourself. And that being the case... why not just do that in the first place?

> We never had technology which can write code like this. I prompted ChatGPT to write a very basic java tool which renders an image from an url and makes it bigger on a click. It just did it.

Which it did, because as the other comment said, tons of people already have.

> Its not clear at all how fast we will progress but i'm pretty sure, we will hit a time were every junior is worse than AI which will force people of rethinking what they are going to do. Do i hire an junior and train him/her? Or do i prefer to invest more into AI? The gap will widen and widen, a generation or a certain amount of people will stay longer and might be able to stay in development but a lot of others might just not.

I mean, this sounds like an absolute crisis in the making for software dev as a profession, when the entire industry is reliant on a small community of actual programmers overseeing tons of robot junior devs turning out mediocre code. But to each their own I suppose.
Yeah, we actually ran into opposite problem a lot, namely that the changing tables were only in the mens restroom. In one organization who I won't name, they were actually very proud of that. I also learned very quickly that this is not something you're allowed to complain about in our current society.
>> Yeah. But the whole discussion here was about the dilemma the optimizer faces if it only has the two indexes on (created_at) and (organization_id), and why the assumption of independence/uniformity does not work for the skewed case.
>
> Was it? The whole discussion started when zac23or said at the top of the thread that their biggest problem with PostgreSQL is its optimizer, that this is their worst example, that it needs an index on (organization_id, created_id) for it to be solved, and that SQLite and MS SQL Server do not need that index on (organization_id, created_at). ...

I don't know, but that's how I understood the discussion - I tried to explain why the Postgres optimizer makes this choice, and why planning this type of queries (LIMIT + WHERE) is a hard problem in principle.

>> Of course, adding a composite or partial index may help, but people are confused why the optimizer is not smart enough to just switch to the other index, which on my machine does this:
>
> I'm curious how you forced the optimizer to switch to that query plan if it's not smart enough to do it on its own.

I simply dropped the index on created_at, forcing the planner to use the other index.

> I think a third question, which is implicit in your comments is, "Well then why doesn't the optimizer use one plan for organization_id=10 and the other plan for the other values of organization_id?" That's a good question. Is this possible? Does any other database do this? I don't know. I'll try to find out but if somebody already has the answer, I'd love to hear it.

The answer is that this does not happen because the optimizer does not have any concept of dependence between the two columns, or (perhaps more importantly) between values in these two columns. So it can't say that for some departments it's not correlated but for ID 10 it is (and should use a different plan).

Maybe it would be possible to implement some new multi-column statistics. I don't think any of the existing optional extended statistics could provide this, but maybe some form of multi-dimensional histogram could? Or something like that? But ultimately, this can never be a complete fix - there'll always be some type of cross-column dependency the statistics can't detect.

> A fourth question is, "How do other databases perform on this and similar queries?"

I'm not sure what all the other databases do, but I think handling this better will require some measure of "risk" or "plan robustness". In other words, some ability to say - how sensitive is the plan to estimates not being perfectly accurate, or maybe some other assumptions being violated. But that's gonna be "better worst case, worse average" solution.
To those who are swinging towards monorepos, I don't think that is a good solution. The reason being is that developers simply cannot be trusted to "do the right thing" on data and module boundaries. Someone comes in new to the project and does something they don't know they shouldn't. It is the honor system backed by weak linters and tooling.

In our monorepo, everyone passes around django orm objects and boundaries are practically non-existent. N+1 queries abound. Tests are full of patching and mocking and are _slow_. Our build takes over an hour to run tests. Someone on team A can and absolutely will mess up what someone on team B is doing. We are now having to spend quarter upon quarter as we define and enforce domain boundaries within the python code base. It is all bolted on checks. Tests are getting worse and people are actively trying to figure out ways around the testing system because it sucks.

Compare to my last gig. We had several hundred production repos. Each repo starts from a template with its own build pipeline. All production repos are gated so that any PR must pass tests before it can merge. Any merge has to pass tests before it could be deployed. As the base build processes matured, teams could, at their leisure, pull their services up to the latest and greatest. We even migrated from Jenkins to Buildkite; yeah, it took N pulls into N repos. Not a big deal. Most projects' tests and builds could get code out to production in under 10 minutes, including all those checks. Due to the network boundary, you couldn't accidentally get around someone's abstraction. And if one team blew up their build doing something dumb? No problem, it only affects that one team.

The argument is "gah, managing all those services!" Keep data behind APIs. Keep APIs backwards compatible. Keep dependencies acyclic. This is _possible_ with monorepos, but you have to do extra work compared to networked services -- yes, when any particular team/service can deploy in minutes due to low build system complexity you are winning. Can you get that wrong and make strange cyclic dependencies and introduce performance issues due to network hops? Yeah, of course. However, we were processing, literally, 10s of billions of api requests on this system and teams could work untethered from one another. The new gig does eerily similar software, but is several orders of magnitude slower in their ability to process data and their ability to move new features.

yes, yes, you could have networked services and a monorepo and you can leverage tooling like Pants to minimize the testing to only account for changed files. It is just fighting what I have found to be a better model. Keep things separate. Keep things fast to change.
lol cmon guys don't be too hard on me it does say "inputs"
Wow. This is an awesome education on why you can’t just regulate the world into what you want it to be without regard to feasibility. I’m sure the few who are allergic are mad, but it would also be messed up to just ban all “allergens” across the board - which is the only effective and fair way to guarantee that this approach couldn’t ever be used to comply with these laws. There isn’t much out there that somebody isn’t allergic to or intolerant of.
There's an interesting and detailed PDF linked from the first page that is packed with history and statistics about Russia's present and past manufacturing of missiles.

https://assets-global.website-files.com/65ca33870401867f9de4...
I worked at Reddit in the not so distant past. The entire recommendation system lived in 3 repos. I'm pretty sure there are just 2000 repos because the onboarding tutorials have you create one, and that number is probably around the number of engineers that have worked there. I'd guess 100-200 have some production component.
For a more technical dive, we just interviewed Mikey (CEO) on the pod: https://www.latent.space/p/suno
Yeah, especially given we don't know what baseline is. Like, did 58 people die of a heart attack and 38 of them had intermittently fasted?

Without knowing what these numbers mean really hard to draw any conclusion. Also, somewhat irresponsible for eurekalert to publish something like this on an unreleased study.
True, but given that cardiovascular disease is one of the leading causes of death, I don't think that in this specific case it's negligible.

By far the bigger problem IMHO is not controlling by weight (at least, the article seems to hint that doing so might happpen in further research...), which is highly correlated both to cardiovascular disease and the chance of being on a restrictive diet plan. "Fat people more likely to have a heart attack, and also to be on a diet" doesn't have the same clickbaity ring to it.
What if new AI tools negate the thousands of hours experience to generate realistic VFX scenes, so now realistic scenes can be made by both non-AI VFX experts and AI-assisted VFX laymen?

Do we make all usages of VFX now require a warning, just in case the VFX was generated by AI?

I think this is different to the bow v gun metaphor as I can tell an arrow from a bullet, but I can foresee a future where no human could tell the difference between AI-assisted and non-AI-assisted VFX / art

I believe this is evidenced by the fact that people can go around accusing any art piece of being AI art and the burden of proving them wrong falls on the artist. Essentially I believe we are rapidly approaching the point of it not mattering if someone uses AI in their art because people won't be able to tell anyway
How do you decide which one to enter?
Very nice work!!

I've been very interested in LoRaWAN ever since I first heard about it, and I am excited to see more projects like this pop up!
I assume you're talking about the “nondistro build”?

The difference between -g (--call-graph fp) and --call-graph dwarf is large even with perf linked directly against binutils, at least in my experience (and it was much, much worse until I got some patches into binutils to make it faster). This is both on record and report.

There are also weird bugs with --call-graph dwarf that perf upstream isn't doing anything about, around inlining. It's not perfect by any means.
A quick Kagi found a few of them, apparently a Waffle House has to be a certain size, and if they can do more business, it spawns another one.
It's pretty common; the Framework 13 and Framework 16 for instance has a lot of possible CPU's.
> from all walks of life come together.

that's an interesting take and i suppose in a way you're right. Another way to describe waffle house at last call is imagine you picked up a zoo and shook it really hard for about 5 minutes then set it down and walked in.
Im sure if you spent your whole life sleeping on the ground youd work something out to make it more comfortable
It’s clearly a cheeky comment to give a sense of levity to the presentation.
The wording of the questions also matter a lot but are near impossible to find. In this case, no one can read the actual paper since it is embargoed at this time.

This isn't how science is supposed to work, imagine if Maxwell published just a headline and hid his formulas behind paywalls.
"journalism is printing what someone else does not want printed; everything else is public relations."
I would be surprised if Sam's team didn't clearly mentioned beforehand what questions could be asked regarding the whole debacle.
The sad thing is that they used to be good. At least not that long ago, the one near me was my go-to for corned beef hash. However, after the last visit barely 5 years ago, never going there again.
With enough collective anger, social pressures will factor into business decisions.

It's a nebulous proposition, I get that, because you can't precisely engineer an outcome. My hope is there's enough of us organizing together to trigger the right shifts.

We'll see.
There is also music for other functions: entertainment, background, dancing. Perhaps it finds niche there, because -let's be honest- most of the music in that category is made on the automatic pilot anyway.

But I also find it an idiotic attempt. It doesn't inform us about anything, and it makes any idiot with a mouse think they can create. Instead, they're listening to music that's worse than what YouTube has to offer.
As someone with an architecture, building science and accessibility background I challenge that.

Done well, building new affordable housing with appropriate accessibility does nothing to cut into profit margins for builders. The tax breaks and other pubic dollars almost always deliver more than the cost of ensuring common areas are accessible and a few units have slightly varied doors and bathrooms (mostly.)

That builders don't want to build more affordable housing is its own problem, but not because of ADA requirements. In general, the ADA doesn't say much about low income housing except explicitly government owned and managed housing, BTW. The ADA is overwhelmingly concerned with public accommodations (businesses open to the public) and government and public spaces, not private home construction.)

It's almost exclusively the lower profit margins for price capped construction and not the minimal a11y requirements easily covered for anyone taking public money and who is building affordable housing and not taking government money, that are the root of our affordable housing shortage.

Accessibility is an unalloyed good and your bogus attempt at providing an alternative example is easily shot down. Pick an example you actually know something about and try again.
This is great, thanks for making it!
I'm not a compiler engineer, but I think it's a diminishing returns issue. Modern optimising compilers are already impressive, and they get more impressive year on year, but only quite slowly. We don't see compilers producing code that runs 30% faster than the code generated last year, for instance.

Such improvements can happen with compiler updates, but not when the starting point is a compiler that's already of decent quality. I recall some GPU driver updates from ATi (years ago) delivered pretty drastic performance improvements, but I believe that's because the original drivers were rather primitive.

(Perhaps a drastic improvement to autovectorisation could give a 30% boost, or better, but this would apply only to certain programs.)

You could grant a compute budget 100x the typical build set-up, but no one has built a production-ready compiler to take advantage of that, and if they did I suspect the improvements would be unimpressive. They may also run into a 'complexity ceiling' issue, as the compiler would presumably be even more complex than today's ordinary optimising compilers, which are already enormous.

As Filligree says, superoptimisers tend to only be practical for very short programs. They can't be applied to monstrous codebases like Chromium.
Inversion: Fast, Reliable Structured LLMs
It has one, seemingly. Not much activity though. I wonder how the site is hosted

https://github.com/squirrelinhell/bewelltuned
If you use the fetch API you can get a readable stream and party on without too much difficulty. You can also implement a transform stream in ~10SLOC that will make the reader vend parsed JSON objects and can be reused easily.
This. It's not "hallucination", it's "error".
Nope, just when you think Olive Garden is awful, Applebee's manages to dig the hole deeper.

TBF, we should just agree that they're all nasty at this point.
Jensen revealed later that the LLM inference is 30x due to architectural improvements, it's massive. I don't know if it's latency or just 2-3x performance boost with 30x more customers served in the same chip. Either way, 30x is massive.
And I'd add that nuclear power is worse here than even standard capitalism. In the US, the federal government provides a massive subsidy in the form of free insurance: https://en.wikipedia.org/wiki/Price%E2%80%93Anderson_Nuclear...

And that's before we get to all of the other subsidies, cataloged here: https://www.ucsusa.org/resources/nuclear-power-still-not-via...

I'm a big fan of free and fair markets, and think that they have been woefully underapplied in recent decades. Happily there's an uptick in antitrust regulation, so maybe we're moving in the right direction.
That's a good idea and we considered FDW (for this and more stuff), but having a middleware makes it more flexible - FDW has limitations around pushdown with subselects, we are still constrained to a single postgresql instance for execution, when in theory we could parallelize (certain) queries across nodes.
You know with GPT you can do these steps in a language you are not familiar with and it will still work. If you don't know some aspect of the language or it's environmental specifics you can just chat until you find out enough to continue.
> I'm just saddened by the prospect that, for me, "adapting to change" would mean "no longer being able to make a living doing what I actually enjoy". that's why if this is the future, it's a career-killing one for me.

Ok and? You don’t think any of the others put out of their work by other forms of computing like you might’ve enjoyed their jobs? You don’t think it might have been career ending for them?