skysight-inc/HackerNews huggingface dataset:
What's the normal meaning of 'kernel'?

EDIT: Hacker news won't let me respond, but the answers below all seem to be because the original meaning has been lost on everyone.

In English, the word 'kernel' means 'core'. An OS kernel is the core of an operating system. In linear algebra, the kernel of a matrix (or a linear transformation, same thing) is the set of vectors it maps to zero, which is also in a sense the 'core' of the mapping (in so far that zero can be seen to be at the 'core' of the vector space / number line).

So actually, the definition is the same, it's just that the word kernel is rather rare, despite having a well understood meaning. Nevertheless, it is the kernel of many common English idioms such as a 'kernel of truth'.

Going to ML kernels... the etymology is a bit convoluted. I believe they come from operator theory and support vector machines. But nevertheless, the 'normal' meaning of kernel works out because kernels are typically the core fundamental operations supported by a machine learning framework atop which the other operations are built. In that sense, regardless of the etymology, the name actually fits.
Ray Dalio – Society Needs These Two Things in Order to Be Successful [video]
Understandably but at the same time, an electrical engineer who specializes in power systems isn’t going to know the in and outs of microprocessor design and there’s nothing wrong with that.
The article did not say "Berlin area", so your "DC area" is not the same.

If something happens over your house, is it "over Washington"?
or one of these: https://www.ebay.com/itm/304770714900?chn=ps&norover=1&mkevt...
> If they were budgeting, they wouldn't be living paycheck to paycheck

You are insultingly out of touch.

I'd like to paint you my picture of my life in 2009 and then compare it to today's numbers.

I was making $10.75/hr at a Subway, working ~38 hours/week. That's ~$1600 pretax, about $1,200 post-tax. Expenses:

Rent (Single-bedroom apartment): 650
car insurance: 75
water/sewage/garbage: 40
internet: 30
phone: 30
electricity: 50

That left me with $325/month to pay for gas (luckily I loved only ~3 miles from work, so that didn't cost me much), food, and entertainment. $10/day for food wasn't terrible, but it's not exactly steak and seafood, either. And remember, that $10/day is supposed to include entertainment as well. Honestly, it wasn't really THAT bad. Buuuuut....

Minimum wage increases have happened, but rent has gone up too. That job would now pay $15/hr, ($2280 for 38 hours pretax, ~$1710 post-tax), but the rent on that exact same unit is now $1,200/month.

Assuming all other bills remained the same (they wouldn't), I'd now be left with only $285/month for food. And with over 15 years of inflation, that $285 is worth significantly less.

At that point, even with budgeting, I'd still be living paycheck-to-paycheck. When wages don't keep up with the cost of living, you can't budget your way out of it.

To make it worse, that kind of living starts to take its toll on mental health. You feel like you're constantly drowning. That $4 coffee or the meal at Taco Bell will be your only source of real joy between each paycheck.
Why and how do marketing blog posts so light on information or originality get to the top of the feed?

Is it just the provocative title?
I really just think that repealing the system that imposes artificial scarcity on ideas would be the best at this point. It doesn't encourage creative work. No one decides to make art because they want to own its likeness. Tons of people have certainly stopped or decided not to start because we aren't allowed to stand on the shoulders of previous generations anymore though.
Society needs, in order to be successful, good education and an environment where to express its benefits - the two enablers for productivity.

> History has shown that there are only two things a society needs in order to be successful: the first is the ability to provide a good education to most people, that teaches them skills and civility so they can be productive - in other words the development of human capital from the start. This teaching typically comes from parents and teachers, who instill good values and principles to be productive with others. The second is an environment that gives people the resources so that they can be productive. At its best that environment provides financial capital that comes from investors banks and capital markets to invest in those who are capable of being productive. This environment must be a civil place to live work and raise one's families; ideally one in which there are many exciting people doing many exciting things - so that it is a creatively stimulating environment. In other words, having the right people in the right environment that supports productive creativity throughout the life cycle is what it takes

~~ Ray Dalio

(Transcript of the submitted short video, provided for convenience.)
honestly, I believe it. I would blame the truck ads that have brainwashed Americans into thinking that driving a truck makes you more masculine or tough.
Given the pace of inflation shouldn't we raise the bar to $1000/month side projects? I'm always in search of "I could pay my mortgage with that!" side projects...
99% of the time people say linear algebra is required for something, they mean knowledge basic operations and properties of tensors more than actual "algebra". I found this when doing computer graphics. Is that true as well here?
You can also look at things that are not cars, for example the road.
Understanding Deep Learning, by S. Prince (the pdf is free)
I believe the checks you're referring are local to a package. It doesn't do whole program analysis like deadcode does.
> We just need some core work horse libraries.

Do you mean like PyTorch, TensorFlow, or the others?
NLP is not the industry, and a lot of research still goes into other things, like RL

I've worked with several transformers competitors, and it def wont stay centralized on them
I have built three SaaS products using this stack. The services are mainly B2B, but one of them has a fairly large B2C-ish user base (recruiting teams). Everything I've built has been profitable and cost of running is very low.
The Minimal Phone pairs an E Ink screen with a QWERTY keyboard and Android
I can't read the article as the ads is overwhelming.
I agree with you, but Tesla did get things in gear fast enough to ship cars, early. If Apple's car ships in 2028 (and that's optimistic), then they'll be 20 years late to Tesla's party. The early mover advantage is worth something, not what investors value it at but still a hefty sum.
S/V sold 10 million copies in the first 3 days and ~25 million copies in the first year. Nintendo is doing fine.

To me the success of Palworld shows two things:
1, the survival-crafting genre is still a gold mine after all these years YET no AAA studio wants to touch it for some reason. Only Early Access indie games in the field.
2, Nintendo would break all records if they start releasing their games on multiple platforms.
It's the archaeologists saying, “Nobody knows for certain how the Romans used them,” and offering a variety of competing theories, while people on this thread are trying to finesse the facts to support the theory they like.

So saying, "archaeologists are doing it" is demonstrably untrue here.
I don't know what to tell you. I've tested dozens of pairs of headphones and some have a clearly, obviously larger soundstage than others, with the same exact inputs. Others have a more "inside" feel. I think we must simply be talking about different things, because what I'm describing is a commonly cited property in headphone reviews and discussions.
What are ML jobs about? I have this vague notion that you spend a lot of time gathering/cleaning data and throwing things at the wall, but maybe that's not accurate.

I've always been stronger at discrete type math/programming, which is why I tend to shy away from statistics-based stuff like ML.

One thing to note is that LLMs are indeed feed forward, however the generation of the text (from my understanding) is recursive in that you feed each output token to another forward pass of the neural network.
Nah, it's just a convention adopted from French after the Norman Conquest.
So the article doesn't site sources, but it looks to me like another dev sharing "expertise" based on 1 data point (his experience of one team, one product).

I work in technical diligence, we assess companies getting purchased, getting ready to exit, raising money, etc. I've done 50+ myself, read reports for hundreds more, and Crosslake (my employer) has done thousands. This is not our experience.

Overspend on dev team is occasionally an issue. Key person risks, tech debt, and other symptoms of lack of expertise are frequently serious issues. (No amount of juniours eliminates key person risk on a senior, only a similarly expert senior does). The companies I have seen that made policies of hiring smaller teams of the best people they can find and paying them well were, in general, kicking ass.

I would argue this article has it completely backwards. My opinion, based on anecdotal (because I didn't run stats on it) but much larger sample size is that the difference to your company over the long term of senior vs junior dwarfs the difference in cost. We are constantly saying "hire more seniors in X,Y,Z". We are rarely saying "cut dev spend".

My advice: for your core offering, buy the best devs you can and make them happy. For all the peripheral commodity stuff (the "not rocket science"), outsource to Eastern Europe and have a full time senior based locally who job is to run that team, interfacing with their lead and managing integration with your core.

Especially right now. Preferring juniors when the market is full of freshly unemploye ace seniors would be terrifically stupid.
Does this provide automatic updates? If not this should not be recommended as it is incredibly dangerous to use a browser that isn't getting updates.

The official instructions provide a way to subscribe to the repo to get updates: https://support.mozilla.org/en-US/kb/install-firefox-linux#w...
> Moravec wrote in 1988, "it is comparatively easy to make computers exhibit adult level performance on intelligence tests or playing checkers, and difficult or impossible to give them the skills of a one-year-old when it comes to perception and mobility".

The resolution to the paradox is so simple I must be missing something. The amount of data in datasets for 'mobility' is basically zero. You would have to manually construct such a dataset. Whereas, humans have for thousands of years been trained to symbolically encode their reasoning processes in a way that has been incredibly accessible to computers (prose).

If I understand correctly, the scaling laws for mobility are the same for language and reasoning. We need more data.
If you've never been to the northeastern US (Boston, New York, Philly, DC), it's like an entirely different country from most of the rest of the US. The map really speaks volumes.
I would say we have a complex organism bias though, really the most successful life is simple, more than 90% of earth's biomass is plants, ants, fungi, bacteria (obviously some of those are more complex than others, but none of them are posting on HN quite).
> I never understood the fascination with the Pi.

Ecosystem. Everybody was gaga over the RPi so if you wanted to do "Task X" you could find an online tutorial for it.

Of course, almost everything that doesn't involve an RPi Hat also works just fine on standard Linux machines. But not everybody gets that.

I watched this play out in real time. People wanted Octoprint to drive several 3D printers. They wanted one per printer and bought a whole bunch of RPi stuff. I pointed out that a used x86 desktop of any flavor was way cheaper and far more powerful, but shrug. Not my circus; not my monkeys.
It helps to differentiate between the foundational research and the application. Are you expecting to advance SOTA and get published? Then yes, you need a PhD. Are you building stuff in the enterprise world? Then no, it is like any other kind of engineering. Not everyone has to be James Clark Maxwell.
I'm one of the authors; happy to answer questions.
this arch is of course nice for high-resolution synthesis, but there's some other cool stuff worth mentioning..

activations are small! so you can enjoy bigger batch sizes. this is due to the 4x patching we do on the ingress to the model, and the effectiveness of neighbourhood attention in joining patches at the seams.

the model's inductive biases are pretty different than (for example) a convolutional UNet's. the innermost levels seem to train easily, so images can have good global coherence early in training.

there's no convolutions! so you don't need to worry about artifacts stemming from convolution padding, or having canvas edge padding artifacts leak an implicit position bias.

we can finally see what high-resolution diffusion outputs look like _without_ latents! personally I think current latent VAEs don't _really_ achieve the high resolutions they claim (otherwise fine details like text would survive a VAE roundtrip faithfully); it's common to see latent diffusion outputs with smudgy skin or blurry fur. what I'd like to see in the future of latent diffusion is to listen to the Emu paper and use more channels, or a less ambitious upsample.

it's a transformer! so we can try applying to it everything we know about transformers, like sigma reparameterisation or multimodality. some tricks like masked training will require extra support in [NATTEN](https://github.com/SHI-Labs/NATTEN), but we're very happy with its featureset and performance so far.

but honestly I'm most excited about the efficiency. there's too little work on making pretraining possible at GPU-poor scale. so I was very happy to see HDiT could succeed at small-scale tasks within the resources I had at home (you can get nice oxford flowers samples at 256x256px with half an hour on a 4090). I think with models that are better fits for the problem, perhaps we can get good results with smaller models. and I'd like to see big tech go that direction too!

-Alex Birch
What parts of the ML pipeline have you focused your work on?
AFAICT, that still doesn't support 8-bit integer dot product? (To clarify, I was using int8 to mean 8-bit integer, not 8-byte)
another problem with ML workflow is the difficulty of iteration - takes long to run, etc. - but SWE are super used to iterating quickly
Why not go with a simple LLC and then elect to be taxed as an S-Corp later when it makes sense?
Easily. Your Windows C: drive is in /mnt/c in WSL.

And your WSL root (/) is in e.g. \\wsl.localhost\Ubuntu on Windows.
But the shareholder value goes down if you have quality and safety issues? Boeing stock did go down.
Supporting actual quicktime from what I recall is a massive massive faff. The colleges that have dealt with QT first hand all seem to loath it with a passion.
Streets may not have gotten wider in a given city/town since then, but there's been a lot of population growth and development in that time in the sunbelt where urban planning has favored very wide roads. So even if roads themselves aren't getting wider, people have been moving to places where roads are wide.
why would the track even care? ... why would they care what happens off track, to someone else's betting operation?

The track exists, more or less, because of betting, and not just at the track. At least someone sees it as a threat to betting: "[Barry Orr, Betfair’s head of racing PR] worries that the imbalance in information across different bettors could lead to the demise of gambling on horse racing." If this is a legitimate concern, then it is in the track's best interest to make people think everyone has equal info, or else people will stop betting: "Martin Hughes, a longtime gambler based in the northeast of England who is a member of the Horseracing Bettors’ Forum, a voluntary body of gamblers, “I more or less stopped betting, because I'm so far behind it is pointless, really.”"

Rather than surveilling the track for violators, can't they stop taking bets prior to the start of the race?

Well, that would make them less money.
> 8 weeks plus 2 weeks per year seems light. 4 weeks for every year sounds more fair. The interview process was over 8 weeks

Well that would be a short severance for everybody who was hired in the last year.
Calling vtables "reflection" is a stretch.
The reason it's problematic is the same reason we need a new protocol in the first place: because the old one isn't enough.

You've spent longer talking about not deploying v6 than you would have done deploying it. I said this before, but I suggest you sit down and turn v6 on for your network -- and *just* that, don't start gaming out how to disable v4 or deal with devices that don't support v6 or anything else, *just* do the basic enabling v6 on the network part. That way you'll see that you're seriously overthinking it.

But you won't listen to me, because http://habitatchronicles.com/2004/04/you-cant-tell-people-an...
Ahh yes, thank you.

Rust doesn't have a -ffast-math flag, though it is interesting that you passed it directly to llvm. I am kinda glad that escape hatch doesn't work, to be honest.

There are currently unstable intrinsics that let you do this, and you seemingly get close to clang codegen with them: https://godbolt.org/z/EEW79Gbxv

The thread tracking this discusses another attempt at a flag to enable this by turning on the CPU feature directly, but that doesn't seem to affect codegen in this case. https://github.com/rust-lang/rust/issues/21690

It would be nice to get these intrinsics stabilized, at least.

EDIT: oops you figured this out while I was writing it, haha.
Mexico wins appeal in $10 billion lawsuit against US gunmakers
At least by me, 100% buyers wanting more space.

Each kid gets their own bedroom. A home office. Maybe a movie room.

Compare that to the 1950s boomer house, that has 2 kids in 1 bedroom, and no "extra" rooms.
Some users are unable to upload, download, and view files in Slack
Any plans for UHD display and a good keyboard?
Was at Multiflow (Yale spinoff with Josh Fisher and John O'Donnell) '85-90 and saw the VLIW problem up close (was in the OS group, eventually running it).

The main problem was compiler complexity -- the hoped-for "junk parallelism" gains really never panned out (maybe 2-3X?), so the compiler was best when it could discover, or be fed, vector operations.

But Convex (main competitor at the time) already had the "minisupercomputer vector" market locked up.

So Multiflow folded in early '90 (I had already bailed, seeing the handwriting mural) after burning through $60M in VC, which was a record at the time, I believe.
Suburbia is expensive in some ways, but suburbs are often built as a less expensive place to live or at least less expensive for a given size. Of course, it's often hard to find a studio apartment in the suburbs and it's hard to find a single story detached home in the city, so it's comparing different kinds of apples; they're comparable but not fungible.

I had a very nice visit to Paris and London for business many years ago. And I tried to get my boss to transfer me to the Paris office. But I moved from the suburbs to a ruralish community where I can live on a 9 acre wooded lot where I know my neighbors but rarely hear them.
> I've always been stronger at discrete type math/programming, which is why I tend to shy away from statistics-based stuff like ML.

I think there's a major misconception that ML in the form of deep learning is about statistics. There's no statistics in deep learning models. There are some statistical measurements made of final models, much in the same way a good computer science paper covering implementations of discrete data structures might make statistical statements showing the performance of the author's implementation, but like transformers and traditional neural nets and backprop have nothing to do with statistics.
How come you don't use an adblocker?
S hit infinity on my first car's tires
A tiny bit more. Once in a while someone does something elegant with eigenvalues, and Transformers represent their "thoughts" in a very LinAlg way (a linear combination of orthonormal basis vectors in a very high dimension) that was very hard for the only person with no LinAlg background in my study group to grok.
Here's the change that needs to be made (more accurately, reversed):

>>Boeing outsources a lot of the production of components for its aircraft because it’s cheaper as part of an overall shift in strategy that dates to CEO Harry Stonecipher who had been CEO of McDonnell Douglas,

>>>> "When people say I changed the culture of Boeing, that was the intent, so that it’s run like a business rather than a great engineering firm."

IOW, the McDonnel Douglas, now Boeing, CEO deliberately wrecked the engineering firm to make finance primary. In my book, that merits being tarred, feathered, drawn, and quartered. He's putting millions of lives at risk, risking the defense capabilities of the US, and already killed hundreds. All to line the pockets of himself and his cronies.

The only question is whether the engineering organization is too far lost to reconstitute.
Digitization is one direction but I think augmentation is perhaps a more likely one. Or a first one. Digitization can follow in a "Ship of Theseus" fashion.

And augmentation branches then in AI as symbiont versus AI as desktop assistant.
I’ve seen many vases and other such vessels in the homes of rich people that are not used to store liquids, but instead sit there empty on a console table in the hallway!
> This isn’t actionable, though.

Of course it is. If you bought Bitcoin five years ago, you'd be up about 1000% and could sell. That's actionable.

Long term Bitcoin investors believe it'll be significantly higher in the years to come.

If you bought $1000 worth of bitcoin in 2013, it would be valued at over $2 million at the end of 2023 [1].

[1]: https://www.goodfinancialcents.com/bitcoin-annual-returns/#b...
And who is going to care to do anything with an open source smart fridge stack that maybe 10,000 or 50,000 people use? Open source only helps if someone cares..
The video on the page sums up the study in simple terms. For Lean Mass Hyper-Responders, eating a low carb ketogenic diet increases cholesterol levels because the liver is effectively trafficking more fat due to low glycogen levels in the liver. An increase in carbs (from Oreos in this study) dramatically drops the cholesterol levels even more than statins for people with this specific body type.
Direct-die vapor phase change cooler? That tends to be the fastest way to get heat out of a chip and to a big radiator. For industrial applications the need to run a big fan & a compressor are less problematic.
The bit of code at the center of an operating system that mediates access between userspace code and the hardware.

Whereas in CUDA programming, a kernel is just the code running on the device. When I first heard kernel in relation to CUDA programming, I expected it to be a) the actual OS kernel, and then b) something akin to a GPU driver.

I can see how NVIDIA got there, but it's not immediately obvious if you're coming from a SWE context.
Agreed, tempted to flag this as thinly veiled spam.
Sounds like the complexity of life follows a power law distribution, where most of it is simple to moderately complex, but a few species are orders of magnitude more complex than the vast majority. Eg, the vast majority of complexity among living organisms derives from just a few species.
A Beaglebone Black is a FAR better fit for the description of "ARM, low power, and GPIO".

A Beaglebone Black actually runs off of a 5V 500mA USB interface unlike the RPis that require non-standard 5V multi-Amp USB supplies. And it's GPIO system (along with everything else) is well documented and doesn't require NDAs.

And the RPi was only dirt cheap while it was being subsidized by Broadcom. Now that it's not, the RPI is more expensive than low end x86s that run rings around them.
Amazon prime has https://en.wikipedia.org/wiki/Three-Body available, dubbed in English. I enjoyed it.