skysight-inc/HackerNews huggingface dataset:
> But almost everywhere else needs people. Badly. Across retail, restaurants, manufacturing, trades, and on and on, companies are struggling to hire. And this brings us back to the cross-country trip observation and that “signing bonus” sign in a McDonald’s window.

For jobs that pay just enough to not qualify for food stamps or Medicaid but not enough to buy food medicine and rent.

Previously it was more possible to earn little enough to qualify for benefits and live if not well but the numbers have become misaligned and don't account for differences between expensive and cheaper parts of states.

Given present concerns the situation doesn't change appreciably unless you go all in on automation implement UBI or both.
Could we in theory just build up any kind of creature from scratch if we write out its genome? How would we compile it into organic matter?
It's true. The original sentence was sarcastic.
Foreach Derp with Csh
> Apple told me it would cost 2300$ to fix it

They are probably going to keep the laptop in ICU for a few days post key replacement.
The DNA contains all the code that creates and regulates the proteins.
Yes and Apple even lets users rent the tools instead of having to buy them. This is key because the tools for taking apart an iPhone are not trivial!
The US prioritises an ability to swim through a river, climb a small fence, and/or trudge across some desert.
I guess nih will update this soon: https://www.ncbi.nlm.nih.gov/assembly/GCF_009914755.1/ since it was gap-less except for Y chromosome
SpaceX employees can't sell their RSUs period, since it's a private company. They're counting on a big payday at an IPO that will never happen if it gets nationalised.
What you're describing was literally my hope when Baxter came out as a robot. Generalization of low income tasks, which would in return force governments to find a more sustainable way to manage our societies.

With the idea that people cannot be hired anymore compared to a robot, because the economic incentive isn't there anymore.

My hope for basic income is still there, as this would allow a shift from a system that only has economic incentive to a system that has creativity and an aspirational incentive. Basic income would provide that, because nobody needs to work just to be able to exist, and they can then focus on "what they actually really want" in life. The argument that nobody wants to work in life is a little stupid, because I think that people want to do something when they're way too bored.

Whether that's just shitty prank videos or research is up to our society, and if we make it "famous" to be smart then the incentive is much higher to do research.
> games are still coming out that only run at ~70 fps on a 3080, etc.

Graphical fidelity in games improves until it maxes out current hardware. This is natural. You can always turn the settings down to get higher FPS, but you can't turn down the high FPS you get in older games into more modern graphics.

> Avg FPS are not going up fast enough in my opinion.

FPS isn't the one and only metric. Audiences generally care more about graphical fidelity. FPS just has to be good enough and stable. Typically that sweet spot is 60fps, though we're slowly moving to 144fps being the standard.
Two when you include -2, which I certainly think we should in this circumstance.
I don’t tend to run into that. But you should be able to fix it right clicking the pom and choosing Maven -> Reimport.

The number of times I actually needed to clean my cache I could probably count on one hand over the last 10 years.
if you pay everyone 10% more, the difference between a $30k worker barely scaping by and a $100k worker that is cofortable simply increases by $7k.

I'm not saying everyone can't get a pay raise, but we can't think linearly here. Semiconductor workers aren't exactly applying for food stamps.
yup, although with sugar drinks i eventually realized that getting them with ice meant i'd dilute the drink and consume less sugar. tough choices...
This is WAY better than any old school YAGNI post I've ever seen.

It's not another "Keep it simple" rehash, it's about not reinvention the wheel at the platform level.

I don't know why there's always such a temptation to write your framework and THEN write the actual product but it's always there.

Maybe because framework dev is unlimited creativity only vaguely tied to the real product, without even the constraint of having to work and not have bugs.

You might not find out about some of them till you actually try to use it, so you can pretend your framework is great when it's complete crap and will need a year of work to fix, which you'll have to do while you're also doing the actual product.

Hobby project are even more vulnerable to this, because there's zero pressure to actually do the project.

How many people wanted to make a game, so they made an engine, and 5 years later never made a game with it(Occasionally someone else does though, which is kind of cool)?
Doesn’t your use of scare quotes around “also” imply that they were, in fact, laundering money?
I'd argue the trans and gnederfluid movement is counterculture in that it is a major shift in social norms, language and self-presentation and isn't yet sufficiently mainstream to be noncontroversial.

Aside from identity, is there no counterculture, or is everything so interconnected and observable via Internet and social media that nothing is in a "dark corner" anymore? I can see that argument.
It's not a matter of "oversupply" or not. The harder it is for companies to hire, the more they are willing to pay, so long as they can still generate revenue at those wages.
The code how to build a sperm and an egg is inside the human DNA, isn't it?
There needs to be more money and/or a non 4 year degree path for more of these jobs if they want to fill them.
Long baseline stereo matching has a trade off of poor depth resolution in short ranges and requires wide angle lenses which result in an uneven distribution of data after correcting for distortion. The wider the lens, the more distortion increasing as you move away from the center of the lens as pixels are no longer square; you also need higher and higher resolution sensor to get good matches around the edges.

This makes it very hard and computationally expensive because you need to search progressively larger areas of the image to do matching to get the same FOV at longer range. Large baseline also is more likely to suffer from occlusion (even self-occlusion) by objects in the foreground resulting in holes in the depth map. In addition to being harder to keep the cameras rigid between calibrations (but I guess they figured this part out).

Instead of a depth map like they show it would be much more useful if they instead show a map of the reprojection error of a flat calibration target at the minimum and maximum depth ranges. Even if they are not aiming for geometric accuracy it would give a much better idea of the actual performance of their system.

The problem with these stereo camera companies is they get obsessed with maximizing certain metrics when the fact is there is a fine balance of trade offs to maintain that is highly specific to the desired application and even scene. Sure, you can increase the baseline and figure out how to mitigate calibration but that creates many more problems to solve that only become apparent when you try to apply it to some application.

Anyone interested in long stereo baseline should check out this blog which has been around forever: https://www.elphel.com/blog/2017/09/long-range-multi-view-st...
It's much the same in Japan, though education, work experience, and salary count for more than the language.
Not really, because it depends on who the target is. If the greyhat for example maliciously targets a Mexican cartel or Iranian nuclear centrifuge, are they really the bad guy?
Readers won't pick it up from the title since the corporate speak won't fit in the title, so it will be missing the necessary details
> That's a little weird to me ... it seems to be confusing the metalanguage and the language being implemented.

Well, that's sort of the point. It's perhaps a little less important if you're writing a compiler for a separate programming language, but that's a relatively rare use case. GADTs are mainly used for implementing DSLs to be used elsewhere in the same program.

> Is the more abstract GADT solution supposed to "save" you some work of writing a type checker by somehow letting you reuse Haskell or OCaml's type system to express that?

Yes. Writing your own typechecker and integrating it into an existing compiler pipeline is a ton of work, easy to screw up, and a potential compatibility nightmare.

> I also wonder how all that is actually implemented and expanded into running code. The GADT syntax seems to get further and further away from something I imagine can be compiled :)

GADTs are syntactic sugar for constrained type constructors. So this

data Example a where
Example :: Int -> Example Int

becomes this

data Example a = (a ~ Int) => Example a

which is then compiled to a type coercion in the intermediate language
The Supreme Court requires 51 senators to vote for you :) Expertise is definitely not a requirement.
I’m not objecting to what you say. The latter part of my comment is simply considering cases where you only want to replace a part of the function (the author have some examples on the project page), where a decorator wouldn’t be flexible enough to support. Of course you can also argue those can be easily rewritten to be function scoped, but that is a design tradeoff you make that author did not (or didn’t want to).
I switched to Arq Backup the last night BB increased their pricing and refused to honor their promise to let me pay for another year at the current rate.
I was particularly puzzled by the 2x2. High productivity is a no brainer, but why should we necessarily seek high displacement as its own goal? Low displacement would increase employment and GDP, is that not flourishing?

And what's with using the research scientists who authored Transformers as examples of surplus middle management? Google generated 1.4M per employee in 2022, second only to Apple. Armchair engineers will say they could do as well with a handful of employees, but if this is "low productivity" then sign me up.
It's missing from sales, too. Once upon a time, as a salesperson who needed to travel to meet with potential clients, you'd also spend time outside the office - maybe you'd take the client to dinner, maybe the client would host you for a home-cooked meal. It gave you a chance to build rapport with the client and truly understand them and their needs. You'd come to understand when a client was squeezing you for a discount because they legitimately needed one to make the deal happen, versus a client trying to get a discount so that they'll look better to their boss.

When vendor discussions move entirely to Zoom, everything is empty platitudes and keeping the relationship purely transactional. Something is missing. People make up their minds to buy before reaching out, or ghost you when they're no longer interested. The salesperson is just a point-of-contact answering questions and shuttling order forms and contracts. Nobody has a chance to work to earn someone's business anymore.

Zoom is leading the enshittification of the sales process.
Android really did drop the ball on building decent native file browser apps for Mac/windows. Frequent adb disconnections or needing to reboot the Mac for the USB host/adb handshake to work...
If you can't communicate effectively in one of your host country's main languages, you're not going to be able to support yourself and survive.
I guess you can keep cheerleading UBI then.
Sure, although I'm not aware of anybody who is contemplating quite the level I believe is necessary to really nail the problem into the ground. When I worked at Google, I proposed that Google build a datacenter-sized sequencing center in Iowa or Nebraska near its data centers, buy thousands of sequencers, and run industrial-scale sequencing, push the data straight to the cloud over fat fiber, followed by machine learning, for health research. I don't think Google wants to get involved in the physical sequencing part but they did listen to my ideas and they have several teams working on applying ML to genomics as well as other health research problems, and my part of my job today (working at a biotech) is to manage the flows of petabytes of genomic data into the cloud and make it accessible to our machine learning engineers.

The really interesting approaches these days, IMHO, combine genomics and microscopic imaging of organoids, and many folks are trying to set up a "lab in the loop", in which large-scale experiments run autonomously by sophisticated ML systems could accelerate discovery. It's a fractally complex and challenging problem.

Statistics has been key to understanding genetics from the beginning (see Mendel, Fisher) and so at a big pharma you will see everything from Bayesian bootstrappers using R to deep learners using pytorch.
Start your own company then, that's a product people would use.

(I'm making my own and agree with you, it works)
No one is trying to solve the world's economic problems here.

That would do nothing to solve the knowledge worker shorter with this chip factories.
Over 2 months I monitored block-list data for the shared IP pools that Marketing Automation vendors offer their customers (Act-On,Campaign Monitor,Eloqua,Hubspot,MailChimp,Marketo,Pardot). Now that I have the data, I'm analyzing it and writing an article. I'll be sharing figures for average MTBF, MTTR and the 2 main approaches vendors use to manage their IP pool. If you can think of other insights that people would be interested in, or are interested in doing an initial reading, then do reply!
True. Premature deaths and sickness are all made up.

/sarcasm

You can argue that these numbers are invalid but the idea that literally killing people and making them sick is made up is ridiculous.
The real world has many trillions of parameters.

Also, doing stuff in the real world is all about sensors. Progress on integrating millions of sensors into a robot has been slow.
I don't waste a spoon or a stirring stick

but you waste a straw instead. i don't see any net benefit wrt this particular aspect
It’s a step in the right direction but only the tip of the iceberg when it comes to keeping AI free of pollution.
> The primary author of the shotgun assembly was Gene Myers, who previously had written BLAST...

So... um... BLAST processing?
So glad I switched to Arq Backup the last time they raised prices, or I'd probably still be with them and paying way more. And it was silly because all they had to do was honor their promise to let me extend my subscription one more year at the current rate.

But now I'm paying $50 a year for 2 computer backups instead of $200. Their loss!
Yes, but it currently requires developmentally mature individuals to build the gametes, and the "code" is so complex you couldn't really decipher it from first principles.
Just catching up to years of undershooting inflation. In real terms still worse than 1969.
Most immigrants do not arrive via the southern border.
Here you go: http://www.paulgraham.com/hackernews.html, https://en.wikipedia.org/wiki/Arc_(programming_language)
i suppose that it is theoretically possible that someone drinking from a glass/cup leaves something sticking to the rim that does not get cleaned off.

but if i would take this consideration seriously then my conclusion would be to not consume anything at this place rather than assuming that the rim of a glass is the only place that is less likely to be clean.
Lets not forget how Perl Saved The Human Genome Project [1], which I remember seeing in a print magazine at the time.

As someone who is in the genomics world now as a software person, I find it amusing that I've gotten more into perl over the last year or so. It has its place, in the way that grep/sed/awk/etc does.

[1] https://news.ycombinator.com/item?id=30327812
Don't think a robot needs millions of sensors. 90% of the information that a human uses comes through the eyes - so just 2 sensors. Really in terms of doing most types of work all a robot would need is vision and hearing.
You're needlessly complicating this and also changing what the parent comment I was responding do takes issue with. There are two things to be evaluated here:

1) Is ingestion of copyrighted material as part of the model training process an infringement itself? I say no - it is equivalent to a human going to a library and reading all the books there. The knowledge gained by the human is equivalent to the weights that end up in the model.

2) Is the output of copyrighted material from a model infringement? Yes, obviously. In the exact same way as a human regurgitating a duplicate or close-to-duplicate of someone else's book/song/script/whatever is. We already have an entire body of copyright law to cover this and don't need to reinvent the wheel just because we swapped a human creator for a machine.
Oh, I thought you meant time of flight for light, e.g. lidar. That would be very surprising.
It doesn’t matter, because “the media” doesn’t work as a concept. It’s a bunch of amateurs trained on nothing more than hiding the fact that they are not an expert.

How much of the reporting from the media revealed that Theranos was a fraud? Anything that wasn’t was fucking useless because it’s just a megaphone for corporate PR, despite what they think.

The entire concept of a weekly news is risible, let alone daily news. A fully investigated story actually worthy of the term journalism requires probably 2 employee years worth of actual work.

Look at how many articles the NYTimes publishes daily, multiply it by 700, and then compare that number with the actual number of journalists they have. It’s a complete farce.
Not quite sure what I missed here, how is this AI rather than machine learning?
the project started around 1990, they announced a draft completed in 2000, "completion" in 2003 (this was more a token announcement based on a threshold than a true milestone). Even then the scientists knew that major parts of the centromere, telomere, and highly repetitive regions were not fully resolved, and that was fully admitted. The work by Karen Miga at UCSC and others is more of a mop-up now that genome sequencing is a mature technology and we have much better ways at getting at those tricky regions.

another "completion" happened 3 years ago, before this announcement. but this is the last one. I promise.
I like this reasoning. The act of stealing from a dollar store indicates that a person is not starving because a starving person would plan out a more efficient theft at an establishment that carries larger items.
Which part is made up?
This is going to be a bit unrelated to what you said, but I recommend looking into Mermaid diagrams in your MD files as a replacement for draw.io. It saved us a bunch of time and has given us documentation diagrams that developers actually want to update because they don’t have to spend 9 years aligning lines.
This entire piece is based on one massive, unsupported assertion, which is that LLM progress will cease. Or, as the author puts it, "we are at the tail end of the first wave of large language model-based AI... [it] ends somewhere in the next year or two with the kinds of limits people are running up against." I want to know only one thing, which is what gives him the confidence necessary to say that. If that one statement is untrue, the thesis of the piece completely fails, and I do not know how any one person alive today can be certain that that statement is true. Has Paul Kedrovsky or Eric Norlin spent $150M training a 2T parameter model that no one's heard about? Do they have access to classified OpenAI docs which state that GPT5 exists already, and it's no better than GPT4? Without this sort of information, "LLMs are not going to get smart enough for widespread practical use" is an unsubstantiated bet, and nothing more.
Apple’s brand is so strong that anything that happens on an Apple device is perceived as Apple’s merit, but also more often as Apple’s fault.
Apple is aware that its main competitive advantage is also their main Achille’s heel, unless they keep control.
When it comes to software that’s easy, and that’s why they’re so against side loading.
When it comes to hardware that’s much harder.
When someone goes to a random store, gets their screen swapped with a random part and that starts behaving uncontrollably and degrading the experience, who do you think that customer is holding accountable for that? Themselves? The repairer? Nope, it’s Apple. If you want proof, ask any acquaintance who works at an Apple Store about the complaints they get from customers.
Pressured by a growing outrage about repairability, Apple found a smart way out: sure, repair it yourself, these are the parts and tools you should use, if you mess up it’s your problem.
It can still dent Apple’s brand a bit but it’s better than forced regulation for them.

This argument wasn’t in Apple’s defense, but an attempt at showing that Apple’s approach doesn’t come from an ideological dislike of repair per se, but from pure business calculation based on their current status as a brand and user-experience-focused company.

Now, if you want the ideological bit, that’s a different one and more generic and it’s the old Steve Jobs tenet: users don’t know what they want until you show it to them. I personally believe that’s still true, and yes I believe it applies to the right to repair when taken beyond a small bubble of entitled electronics enthusiasts.

Edit: oh no, I dared say something against the right to repair! Hasten! Bring in the downvotes!!!
I think even just losing the ability to prompt an LLM with "...in the style of the New York Times" would be interesting. You'd probably end up drawing from parodies of the Times, which is quite different.

Of course OpenAI probably still has a full dump of LexisNexis or something.
Those sound like techniques to fool a polygraph.

There are new infrared sensors in development that should see much more complex behavior in the brain, than say EEG. I’m sure even those could be gamed theoretically, but it will clearly become increasingly difficult as the technology improves.
>don’t say GitHub

Gitlab, Bitbucket.

I don't really know what to expect. You want to see good production code, and the FOSS community is way way WAY better at this than some of the bubble gum you'd see in a professional setting.

Your question is too general, so I can't exactly give you a specific repository. I could direct you to BGFX[1] for a decent architecture of a cross platform renderer, but if you're not a graphics programmer, that may be a bad exercise, as you'd spend more time learning jargon than studying clean code. Or it uses patterns (or lack of, given graphics programming) that don't apply to your domain.

[1]: https://github.com/bkaradzic/bgfx
We don't know that it fully defines a human until we can create one without the starting condition of being inside another human. It's prototype-based inheritance.
Q: But if the robot has no nose, how will it smell?

A: Awful!
Not only that, real users actually want to use the service, not overload it. A real user might only make one request a second. A botnet device is trying to make a thousand requests per second to overload the server. Even if they each have the same CPU as a normal user, now each node in the botnet can only make as many requests per second as a user or the user can outbid them.
China is totalitarian, but it's a stretch to call it communist in any practical sense.

China is paying the price of rule by KPI.
since we would now have a digital engine of truth.

What are we living in, a dystopian sci-fi universe?
Yeah, derp. My brain is failing me these days.
I see a lot of similarities to Golang.
California nearly drought free in wake of Hilary's historic rains
Just started playing with this, there's a tool called ollama that runs Llama2 13B on my 16GB M1 Pro really smoothly with zero config.