skysight-inc/HackerNews huggingface dataset:
Yes. Corporations really do just lose your info and move on as quietly as possible. You can try to not give real info to anyone that isn't the government.
At least $500 would pay for my mortgage almost just as well as when I got it.
they just need new development methods
Edit history is an awesome learning data (as they show the train of thought), but I can imagine that models will easily learn to generate it.
Wow those ads are intrusive, could barely find the start of the article let alone read it.
> For me the hardest part of learning ML was getting over imposter syndrome. It felt like I needed a PhD and hardcore math skills

ABD (all but PhD dissertation) here with strong math skills. I get the imposter syndrome, but let me absolutely assure you that the community at large does not have strong math skills. I routinely talk to people doing diffusion research that don't know what covariance is or pdf. People from top ranked schools, with high paper counts and high citation counts. Expertise is often more narrow than it appears. That's okay, as long as we're honest about it.

Don't get me wrong, I wish there was more math involved and efforts were more serious. But they aren't. The space is very noisy and little is being done to clean it up (there are some, and I do appreciate those efforts). I'll add that there's one thing more that you need besides motivation and patience: perseverance. ML systems are hard to debug and difficult to evaluate (maybe not for papers, but absolutely for systems that work in the real world). It's okay to not get things perfectly and it is totally okay to not have a model with decent generalization, but context is always important and part of the debugging process is trying to trace these down (which is difficult because you need to do more abstract versions of what is analogous to the silly or random inputs being passed to code). Detecting overfitting is often quite hard and honestly sometimes it is even desirable (GPT being overfit makes it great for information retrieval!).

Also, something I tell my students when I teach ML: you don't need math to train good models, but you do need math to know why your models are wrong. So I highly encourage math, but don't let that stop you from getting started. You can also just have a math heavy person on your team and get many benefits that way.
Maybe not 95%, but quite a lot of truck owners when surveyed essentially never use them for towing or hauling https://www.axios.com/2023/01/23/pickup-trucks-f150-size-wei...
I think that to most software people kernel means something like the Linux kernel, but to an ML engineer it is a specific mathematical term-of-art.
I've asked you similar in the past in comments on this site, but: what do you find lacking in the NestedText spec that a new YAML-like format might do better? Why not just embrace NestedText for the task?
More expensive than the corolla wheels.
Transformers are used outside of NLP
No shit. The majority of students I met in the Computer Science weren't skilled in math but took it as a requirement to code. Why would you expect them to just latch onto Machine Learning?
https://www.smithsonianmag.com/history/what-the-luddites-rea...

> They did not invent a machine to destroy technology, but they knew how to use one. In Yorkshire, they attacked frames with massive sledgehammers they called “Great Enoch,” after a local blacksmith who had manufactured both the hammers and many of the machines they intended to destroy. “Enoch made them,” they declared, “Enoch shall break them.”

... And another reference for the phrase...

https://www.nigeltyas.co.uk/nigel-tyas-news/post/enoch-the-p...

> And here’s the funny thing. The weapons they reached for to wield and smash the machines were sledge hammers made by ... the Taylor brothers of Marsden. This irony was not lost on the Luddites and as they swung ‘Enoch’s hammers’ to damage his hated machines they cried: “Enoch made them, and Enoch shall break them”.
> Douglas Hofstadter had this whole theory of consciousness and when he found out that an LLM was a simple feed forward network with no feedback loops he went into a crisis. Basically his whole theory in GEB was wrong, according to him.

LLMs are not conscious. The training process for an LLM is not a feed forward network. If we were going to try to fit the idea of consciousness a la humanity (which is really the only fully 'conscious' creature we know of) into LLMs, then 'running' an LLM is identical to cloning a frozen human, thawing it, firing some neurons, reading the result and then destroying the clone.

A better argument for actual consciousness would come from the training process, but that itself is also dubious. It's unlikely consciousness is an emergent phenomenon. Or rather, such a claim is extraordinary and would require an extraordinary amount of proof, which GEB does not provide, sorry.
I like the concept. This is how pelicans flow low over the water. However, I have sailed between the Hawaiian islands. The air and water are turbulent due to trade winds and currents getting pushed through gaps in the islands, especially between Oahu and Maui, the most popular route. I looked at the video on their website and it didn't appear stable enough in flight to withstand a big puff pushing it down into a double-size wave. It would probably only work in a narrow weather window.
+1

I'm sure it is possible, but I have spent so much time with it already without a consistent success, that I gave up.

I have come to terms with Windows doing this and I will keep complaining any time the topic comes up.
Are we sure Agile has failed? Did the author give feedback in a timely manner and await incremental improvement?

I'm willing to believe that a particular implementation of the Agile manifesto has failed, but agile is really just a set of common sense tenants which do not enforce a particular way of doing things. The alternatives are stultified bureaucracy or chaos... and Agile will always be able to run circles around that.
> fatally he never learned what the business actually was

What I find fascinating about this post is that it mirrors the same behavior I saw in a small tech company of < 10 employees after the founder sold it to a small group of investors.

Amazing to see a $1M company (1990's dollars) making the same mistakes as a multi-$Bn one.
Fair point. I'll add a prompt. I was also planning to give users the ability to choose how the variables are set in general.

Cleaning up after uninstall is also a good idea.

Thanks for the feedback!
Netflix cost $7.99/month in 2013. Just 10 years ago.

Inflation's been rough. It's been real rough.

But... even accounting for inflation, that's $10.50 today.

These Netflix price increases have gotten really wild and bizarre, from something where you would find a couple of things each month to watch and it would make it worthwhile, to "wow, I'm doing OK, and I can't afford this."
It would seem that selective abortions, and not a government policy per se, are to blame for the skew in sex.

Selective abortions are legal in many, many jurisdictions which do not limit family sizes.

Take, for example, the disappearance of Down Syndrome from Iceland. This triumph of medical science was achieved very easily through early detection and prevention.

These days, you can prevent almost anyone, especially young girls.
It also looks like the solution to the problem isn't to get rid of the regulations, but to change them so that light trucks and giant cars no longer get a break on emissions/fuel economy standards. Revised regulations that incentive smaller cars would solve a lot of problems.
Independent as in Freedom, Not Independent as in Alone
2-3 years ago, I was thinking something similar along the lines of "yeah, why doesn't Apple just stick with computers/phones/peripherals/software." But if anything's become clear in the last few years in the EV market are issues with: reliability, software/firmware, usability, aesthetics, build-quality, and high startup capital requirements. Apple is a perennial expert UX/design/durability/usability. Sure there's been a few boondoggles over slight decreases in QA and quality (butterfly keyboards)--but at the end of the day, most of us still love at least some of their products because they still, usually "just work". Apple is also quite good (whether or not you like it) at building walled gardens. Imagine if Apple released a rock-solid car and an absolutely kick-ass charging network that rivals Tesla's? There's be demand. The biggest, most-obvious reason why Apple could succeed at building a car is that they have massive amounts of cash. The #1 reason these fly-by-night EV startups fail is because they can't handle 5-10 years of negative margins coupled with massive capital costs. Apple could burn billions before their EV division becomes profitable and not even blink.
Well, I'm not actually sure which one they're referring to but there is two meanings that I know of. There's the Software Developer Kernel which is the core of an operating system, and there's the Linear Algebra Kernel which is the null space of a map. Most of us here are familiar with the operating system type but the linear algebra kernel describes the set of vectors which are sent to the null vector (0) by your transformation/map/operation. It's very useful in understanding what exactly your operator does and how it changes a space.
There's a big gap between training an algorithm on a toy problem, vs building a useful product.

Software engineers often are missing key skills. They can learn them, but won't automatically get them in their traditional training.

First, measuring success. Actually telling how well a production system is doing is tricky. There's an art to developing metrics that tell you if an ML system is delivering value, and a lot for engineers don't have the metric design skills. Often to productionize an ML system, you need a bunch of proxy metrics and a pretty good backtesting setup. This will often depend on the specific problem, and the skill of it is something you won't get in a standard software setting.

Engineers - and especially designers - also struggle with edge cases when things go off the happy path. It's often easy to make an ML prototype that works in 90% of cases, and get a project started - but a nightmare to solve enough the edge cases for a production grade system. Finding and papering over and designing around all those edge cases effectively can require a deep bag of tricks a pure software engineer won't have.

Finally there's a struggle with tactics and culture.
A lot of the bread and butter tactics of high performing software delivery are the opposite of what you need for ML projects. E.g. In high velocity frontend work you want to lock a design early, and your designer can probably do a lot of iteration before engineering starts. In ML projects you want to keep the design floating and low fidelity, as you prototype, and lock it late in the project.

So many development tactics, and cultural patterns, that lead to high performing software teams, in a SaaS setting, say, are anathema to ML projects.
Yes, but those countries also have different energy cost.
The right lanes are generally explicitly intended to be slower lanes. Making them optionally faster lanes can be dangerously disruptive. As well as, when the rightmost lane is used to pass, difficult for new vehicles to merge from side roads.

These laws are made so people know what to expect for safe driving. When we're all being chauffeured in autonomous vehicles it'll be safe to rethink them.
to me, it would make a lot more sense to replace the lines of numbers on top of the keyboard with the numeric keypad (instead of getting rid of it)... it is so much easier to type numbers with it....
What is the suggested replacement framework?
Waymo operates in all of SF
Haha, true story! But you gotta do $500 before you can get to $1k. ;)

Let's say, $500 *or more*. The previous year's submissions definitely had ones that were more. :)
Probably because it wasn't a great thesis. Agile is an abstract idea based on common sense observations; as such it will never go away (nor did it originate in our lifetimes). What will go away are those who vilify it, as the referenced article going 404 demonstrates.
I'd like to have been a fly on the wall when they designed the study!
It would never happen, but I'd like to have a no-keyboard option. I never use my laptop keyboard because I have an HHKB, rendering it unnecessary. Instead of a keyboard, I'd like a flat surface where I can rest my HHKB and maybe an L-shaped connector to plug in the USB-C.
I am a professional software developer. I have had Firefox updates disabled for years. I run uBlock Origin with a custom JavaScript whitelist, and it works wonderfully. The only issue I have is when someone is using some bleeding edge web API. in 9 years, I have NEVER had a security issue due to disabled updates.

Stop the scare tactics.
It was just last week I was reading a comment that made it seem like you shouldn't really use -ffast-math[0], but here looks like a non-rare reason why you would want to enable it.

What is correct idiom here? It feels if this sort of thing really matters to you, you should have the know how to handroll a couple lines of ASM. I want to say this is rare, but I had a project a couple years ago where I needed to handroll some vectorized instructions on a raspberry pi.

[0] https://news.ycombinator.com/item?id=39013277
> Tesla has no special sauce that I'm aware of.

At first, Musk's stated goal was to make EV's viable. I feel like that Tesla is well on the way to that, in ways nobody thought possible.

Assuming he hasn't changed his mind, there may come a day he just calls it quits.

But to your point, I would agree - Tesla has no particular special sauce. I am waiting until Waymo FSD finds its way into consumer cars you can drive all over the country before I buy one of them.
Kernel is also used in convolutions... Ugh
I mean setting a static traffic control limit was generally a high water mark, and in general even if you had excess bandwidth you didn't want to exceed it.

Now, to get around that some devices perform regular speed tests and dynamically adjust the high water mark. This said there are some limits at which you should perform these tests as too often and you may affect the actual applications you're trying to run.
$500/month doesn't even pay property taxes anymore, sadly.
CTO position is not being backfilled. There will be a VP of engineering, not quite the same.
You mention cheat days. I cheated a bit on the weekend with a few not-terrible but also not-great things and it's had a disproportionately negative impact. Also, I forgot to mention sleep playing a big role too. I stayed up way too late and paid for it today. Also had half of a no-sugar no-alcohol drink but the gas for whatever reason really hung around for a while. Back to straight water it is. It's surprising how quickly sugar takes effect.

Seems like there is a bit of a buffer but I blew through it

The older I get, the more sidecars tack onto my pods and I'm now having to prune them with more effort
> Large vehicles are important part of American economy and mostly driven by blue collar workers doing their work

Aaaaaaaabsolutely not! Trucks outnumber cars in every U.S. state. "Blue Collar" workers represent something like 16% of the U.S. workforce. The vast majority of truck drivers are not blue collar workers.

Other countries have blue collar workers too. And trucks! Have you seen what they look like? Check this bad-boy out. This is peak performance when it comes to manly-man workin' trucks. [1]

[1] https://c8.alamy.com/comp/2FA3BTR/a-small-blue-pickup-utilit...
This is cool, they even have some parts like the buttons and glass in different colours. So you could even use it to pimp your phone (I wouldn't break the waterproofing just for that but if you need to get in there anyway...)

One thing that's annoying though is that with the S23 you need to buy a new screen when you want to change the battery. The battery is only available as a screen+battery kit. Weird.

I mean, when you replace the screen it makes sense to stick a new battery in, sure. Especially because the old battery might be a few years older or have damage from the impact (safety). The other way around, not so much. Why waste a perfectly good screen just to change the battery? This is really dumb and drives the price up. It also causes unnecessary e-waste.

Now, this is in Europe where Samsung have a real parts shop of their own ( https://samsungselfrepair.shop ), I see in the US it's different because it has to go through iFixit somehow. Edit: Nope, iFixit doesn't seem to sell batteries separately either.
But no matter how well the gene therapy works, the researchers recognize that Aissam may never be able to understand or speak a language, Dr. Germiller said. The brain has a narrow window for learning to speak beginning around ages 2 to 3, he explained. After age 5, the window for learning spoken language is permanently shut.

Wow that's incredibly sad, but I am glad that this will eventually get into the ears of thousands of deaf newborns. Incredible medical advancement. Gives me hope that one day my tinnitus may have a cure.
Britain's Dragonfire laser weapon engages first aerial targets
You can call the limitations of your knowledge about the exact state of a molecule a temperature, but that doesn't mean that any single molecule has an actual physical temperature in the same way as a collection of particles. You can say that a passing car had a speed between 60 mph and 70 mph because you couldn't measure it more exact, but the car has at any given moment an exact speed independent of your knowledge of it, not a distribution of speeds.
It would be interesting to implement Homa on top of this.
Google only does it for phones though. If you have a watch and you break the screen, their only solution is to just buy a new one. Even though replacement isn't hard. They just don't bother making spare parts available. https://arstechnica.com/gadgets/2023/09/11-months-after-laun...
did you mean deep learning?
But mainly, if you know the use case, you can ship iphone-equivalent device with the sensors needed, not an expensive miniaturized laptop. Vision Pro is an user research platform.
Not silly. Here's why:

1. Passing on the right, i.e. passenger side, means being in the driver's blind spot longer.

2. On- and off-ramps are almost always on the right, as are police making traffic stops, ambulances, cars pulled over on the shoulder, sidewalks, pedestrians, cross streets, etc.

3. Slower traffic is supposed to be in the right lane (because of #2), so a car accelerating to pass the car in front of it, suddenly in a lane of slow traffic, is a safety hazard to the slower drivers, regardless of #2.

I'm writing from the US, so for me left lane = driver's side.
I was waiting for the rest of the images to load, good to know they were just ads (using an adblocker)
Multiple people have mentioned this study that shows ChatGPT performs better when the user is nicer to it but I have never been able to find it.

Does anyone know the name of the study or have a link to it.
Waymo cars don't have a driver, and they don't let a passenger take over driving. That's level 4: https://www.sae.org/binaries/content/assets/cm/content/blog/...
Frontend: Whatever I'm using at work. Backend: Rust with Sqlite. It's simple, but with the amenities of a higher-level language, it's performant and the compiler has my back.
Aren't they cheaper than the Ford F150 'Lightning' (electric version, so comparable)? Or is that also 'hyper-luxury'? (Genuine question, I suppose I'm not really familiar enough to know what the top end would be, maybe that's it, I know Lamborgini makes a tractor, but I'm not aware of a 'supertruck'.)
> why is it significant that we slice like a[i:i+4:i+4] rather than just a[i:i+4]?

Well I had never seen that "full slice" expression syntax before. It turns out that it's important because it controls the capacity of the new slice. The capacity of the new slice is now i+4 - i.

So by using the full slice expression you get a slice of length 4 and capacity 4. Without doing this the capacity would be equal to the capacity of the original slice.

I suppose that by controlling the capacity that you eliminate the bounds check.
I was merely listing stuff that can break or severely restrict tree-shaking.
> Someone in 2006 asked what Apple would bring to the cellphone market, too.

And that would be a fair question. The iPhone never did anything others weren't already doing, nor has Apple ever done that in recent history. They sell products not because they're better, but because they've convinced people Apple is cool.
> In the F150 Lightning the batteries even on a standard range weigh as much as a Volkswagen.

Even a Smart Fortwo is minimally 1800 lbs curb weight. How old is this Volkswagen? :)
For EA it is less about datamining and more about flagging behavior that matches that of a cheater evading a ban. Cheaters reduce the fun, and therefore value, of a game.
> The average A64 instruction does slightly less work than the average AMD64 instruction so the net result is that it makes sense to have slightly wider decoders

I'm not sure that the difference is that big. A64 actually has quite powerful instructions, and some of them do more work than similar x86 instructions (madd and ubfx come to mind). In my testing A64 code often has fewer instructions than x86: https://www.bitsnbites.eu/cisc-vs-risc-code-density/

> X86 CPUs don't quite use a "RISC-like encoding". The µops support RMW for memory, for example.

I would love to learn more about that. Do you have any references? I was under the impression that internal instructions followed the load/store principle since I assume that the internal pipeline is a load/store pipeline?

> The Power CPUs call it "cracking" when complicated instructions are split into simpler µops.

Yes, it's the IBM term AFAIK. They call it cracking in zArch too. I also suapect that at least some ARMv8/9 implementations do cracking too (many AArch64 instructions have multiple results, which might be better handled as multiple internal instructions - I think it's partly a code density thing).
Basic operations and properties of tensors are exactly what is taught in linear algebra, in addition to (in my experience) more accessible proofs. More or less through singular value decomposition and/or least squares.

The core algorithms all build on top of each other. The `algebra` part of linear algebra refers to a `field`, but it might as well also be called arithmetic of tensors.
Ok but also, who cares? It is almost assuredly not the reason they are having these issues. I don’t know why you have this crusade against DEI stuff. I also think it’s lame, but the problems with Boeing are more likely that they are run by people who feel the need to make every single dollar they can and will cut costs wherever they need to do that. DEI is a screen they can hide behind.
yeah. people really have a hang up on VR and AR, but it’s almost entirely simply because the electronics and power aren’t there yet. once it is, it will almost already be game over, because… i mean literally everyone eventually will have one. it will be the most significant compute platform in history.

you can see this immediately btw if you book some time on the expensive industry AR and VR devices. but even those aren’t any smaller than the Apple device, for reasons of physics.
> we just need some core work horse libraries

But these do exist: plain Jax or Pytorch only give you basic linear algebra, differentiation and some basic layers. And there's a plethora of more or less advanced libraries that add specific functionality, for example torch geometric for graph data and lightning to reduce boilerplate.
https://yamlscript.org/ was posted here a while back: https://news.ycombinator.com/item?id=38726370

I thought I remembered more comments on that thread, but I guess nothing more than what's there needs to be said.