skysight-inc/HackerNews huggingface dataset:
Pair it with the fact that by-and-by, apartments are extremely expensive, and in short supply, so that service jobs are often not near where people are forced to live, and that you have to pair the cost of a car with the cost of gas, and rent. Public transit is a joke, a hollow underfunded mess in most cities.

It is absolutely brutal out there, and the response is inhumane.

I don't want to discredit the experience of grad students. I've known more than a few Grad students (anecdote warning), and they are also stuck in a special kind of hell. As the article mentions, they often can't seek other employment, so they're stuck with what the university pays. But even if they could, they can't - universities may stipulate that they expect X number of hours a week, but that's a joke. Every task given over to graduate students comes with piles of mandatory overtime under crap conditions that are unpaid.

The university may talk about 'valuable experience that will pay dividends' (conveniently not paid out by the university), but grad students often deal with losing proof of that experience when their work or ideas appear under the byline of their advisor. What do you do? Your relationship with your advisor is crucial to graduating.

Suffer all that, and _maybe_ you'll get your PhD. I've met a couple of phD students who dropped out simply because their advisors were intolerable, or really disinterested in any part of the advising process except squeezing work from their student workers.

Looking from the outside in, there's a weird sorta hazing elitist mindset going on. Professors say, "My PhD program sucked, so now I'm going to make it suck for you. Can't hack it? Well, you probably don't 'belong'".
I like the very web3 middle ground where the attacker negotiates with the company and returns a part of the money, the rest being the lawful reward for reporting the vulnerability.
Not saying they should be the first tool of choice, saying that the study doesn't compare GB to more modern DL techniques like transformers. This is a good analysis https://arxiv.org/pdf/2106.11959.pdf and finds there isn't a go to architecture
What does it look like to fire someone in Europe? As an outsider, all I’ve heard is that it looks very different from the US. What does the author mean by ‘associated compensation’?
I was until a week or two ago part of a team that build datasets with extensive dependencies (thus, complicated DAGs)

v1 of the system built before I joined was Step Functions and the like. It gets hairy just as you say.

v2 I built and designed with the lead data engineer, we called it Coriaria originally. We're hoping/planning to open source it eventually, although it's a little wrapped around our company's internal needs & systems.

It chooses neither "config" strictly speaking nor "code" for the DAG, instead the primary representation/state is all in the PostgreSQL database which tracks the dataset dependencies and how each dataset is built. It's a DAG in PostgreSQL as well.

To make dataset creation and management easier, I also wrote a custom Terraform provider for Coriaria. This made migrating datasets into the new system dramatically faster. The provider is really nice, supports `terraform import` and all that. Currently we have it setup so that there are separate roles/accounts that can modify an existing dataset, but reading state only requires authentication, not authorization. This enables one team to depend on another team's dataset as an upstream data source for their datasets without granting permission to modify it or create a potentially stale copy of the dataset. Terraform's internal DAG representation of the resource dependencies is leveraged because "parent_datasets" references the upstream datasets directly, including the ones we don't build.

We're able to depend on datasets we don't build ourselves because the system has support for Glue catalog backends to track and register partition availability.

Currently, it builds most of the datasets using AWS Athena & S3, however this is abstracted over a single step function. There's no DAG of step functions, it's just a convenient wrapper for the Athena query execution.

The system also explicitly understands dataset builds and validations as separate steps. The dashboard makes it easy to trace the DAG and see which datasets are blocking a dataset build.

We're adding more integrations to it soon so that other ways of kicking off dataset builds and validations are available.

If people are interested in this I can begin lobbying for open sourcing the system. My colleague wanted to open source it as well.

All else fails, I'll rebuild it from scratch because I don't like the existing solutions for managing datasets. We've been calling it a data-flow orchestration system or ETL orchestration system, not sure what would be most meaningful to people.

I think the main caveat to this system is that I'm not sure how much use it'd be for streaming data pipelines, but it could manage the discretization of streaming into validated partitions wherever streamed data is sunk into. Our operating assumptions are that you want validated datasets to drive business decisions, not raw event data streamed in from Kafka. Making sure the right data is located in each daily (or hourly) partition is part of that validation.
Thank you for this comment, it's changed my perspective. I too had a spat of homelessness in my early 20's when i lost my mom & job at the same time.

You seem to have a gift of gab, have you ever tried copywriting on upwork/fiver? Might be a promising direction to get you some stability and a small safe studio.

Work from library's until you can afford a cheap room on craigslist.
My Instagram account was hacked and two-factor authentication didn't help
This messes up alt modifier (event.altKey is always false), which is an instant deal breaker for me as I have many `alt-*` shortcuts in tridactyl.
Goldman Sachs Employee Fatally Shot on Manhattan Subway in Unprovoked Attack
This https://arxiv.org/pdf/2106.11959.pdf would say differently. It shows there isn't a goto architecture when compared to modern DL
There's a minimum critical mass for fission weapons that means they are never going to be earwig-size [1]. Fusion weapons require a fission trigger so they are no smaller than the smallest fission weapon. The only earwig-size nuclear explosive that might theoretically exist is one based on antimatter, but with present and currently foreseeable technology that is the stuff of science fiction.

[1] https://en.wikipedia.org/wiki/Critical_mass#Critical_mass_of... Note that explosive compression lowers the critical mass, but it soon requires more than one gram of high explosive to trim the fissile material budget by one gram, so minimal-size devices are still in the range of kilograms.
Brilliant article
Try nitter.net
> Dot product with what?

Meant to say “two 4-vectors”.

> Don't you want to do dot products on hundreds or thousands of pairs of 4-vectors?

Unfortunately not. I was thinking of a raytracer there, and it doesn’t have any more data available. I could speculate some more data or rewrite the program entirely to get some more, but the OoO and multi-core CPU is a good fit for the simplest pixel at a time approach to raytracing.

In the other case I’d use SIMD for, video codecs, there is definitely not any more data available because it’s a decompression algorithm and so it’s maximally unpredictable what the next compressed bit is going to tell you to do.
> This is interesting/ strange to me. I grew up in the Midwest and a modest garden in the backyard was often the case. I’ve never heard of them being banned. I don’t doubt they are some places.

Backyard gardens are generally unobjectionable, it is the front yard that gets neighbors riled up when they see dirt and messy looking plants. Even then, if you make an effort to have it present as ornamental (eg. herbs, cherry tomatoes, mini peppers, etc. in attractive raised beds and containers that don't displace the entire lawn) you may be able to get away with it.

Oh, and definitely keep the compost pile out of sight.
> accusations in general, if they're vague enough, are impossible to defend against

General accusations are easy to defend against, you just ask for specifics.
> If your stipend is $19K, a single student's take-home pay is $16,734, less ~$1,600 in required departmental fees. So, you've got about $1261/mo to pay for everything. If you split a 1-bedroom for $2.2K (not including utilities), that means you've got $161 for electricity, food, phone, internet, fun, literally every other expense for the rest of the month.

Where is this? When I started my PhD in the early 2000's, my after tax monthly income (state school) was $1400-1500 per month, which is more than what you listed above. Granted, we got paid only 11 months of the year, and yes, did pay university fees, so the total per month may have been similar, but: Seriously, this was almost 20 years ago - I'm sure they pay more now. Either your numbers are off, or your school sucks (sadly, quite likely).

When I went to grad school, my original goal was Berkeley. But when I found out how expensive it was to live there, I picked a top school in a cheaper town. The monthly stipend was only $100/mo less than at Berkeley, but rent was several hundred dollars cheaper.

Edit: Hard to find numbers quickly, but just checked and one of the engineering programs there currently pay $2300/mo (11 months a year). That's $25K vs your $19K. Of course, in some cities, that's still not enough.
Semantic versions can't be sorted trivially, it's true. For projects that benefit from the "semantic" part of semantic versioning the benefits outweigh that minor inconvenience. But not everything needs semantic versioning.
The comment pool on HN is massively over enriched for people who bombed out and have a chip on their shoulder about it. The overwhelming majority of the people I know who did a PhD regard it as one of the happiest and most intellectually stimulating periods of their life. Not everything is about money.
You're almost describing the Russian Orlan-10, except you've got the cost off by an order of magnitude (they cost around $2,000 each).

$200 is an incredibly ambitious target that's unlikely to be hit, but it's also not necessary to bring costs that low. Our military budget is $800B/yr and our current drones cost way more than $2000. Simply bringing the costs down a bit would get us sufficient quantity.
Their complaint hinges on an interpretation of what the correct level of abstraction for describing the transactions is. Their argument, "to mislead token holders to part with tokens on terms they never would have agreed to," is literally a counterfactual that presumes both fictional market conditions as well as intentions of anonymous owners.

The second argument is an analogy, "disable a security measure, like disabling the security system at a bank," and the limit expressed in the code was definitely an expressed preference by the contract author, but if they wanted it to be a legal contract subject to human interpretation, they would have specified this in English. Instead, they created a software tool, and they did not take into account how that tool might be used by the public.

The argument about this is whether code written for the express purpose of partipating in risky transactions can be imbued with any other coherent intention. The closest analogy would be that Medjedovic was at their gambling table and was counting cards, except there was no policy keeping him out of there, or against card counting.
Definitely making the mistake all the time to go all in on a new topic :) But it is better to do it step by step and practice it.
You haven't presented enough evidence to show that there is a problem. If the alumni relations department is bringing in donations greater than their salaries, they are a net benefit to the university. Even if they don't bring in that amount every year, it might still be a net plus: it might bring in better students, spread the word about the university, and it might lead to big gifts later down the line.
That's entirely fair, I'm a big proponent of making colleges either free, or extremely heavily subsidized by the government. I completely agree that it's still ridiculous to leave with $30,000 of debt.

I'm just saying that, for someone working an engineering job, that is not generally a life-ruining amount of money, especially in comparison to the increased earning potential that a degree affords you (which is, I suspect, why they get away with charging such exorbitant tuition in the first place).
Around 700 people will be let go (source: https://www.di.se/digital/sparpaket-pa-klarna-sparkar-10-pro...)
What I'm missing in this conclusion is weighing it against other options. At all.

Sure, it's expensive. It is also expensive as compared to buying farmland for solar panels and getting food from elsewhere? And as compared to finding enough people that are okay with wind turbines nearby? (If you can't just get it all from the sea of course.) From my point of view we ought to work on both fronts, I'm not sure this was addressed elsewhere in the video but at least it's not hinted at in the conclusion.

The suggestion of leaving it to the market sounds good in principle, but forgets that we've been using the "low hanging fruit" space so far, making nuclear seem like a terrible investment for any market party that optimizes short/medium-term gain. It also ignores the political aspect: try building one of these things and getting a license to handle enriched uranium or whatever and see what the German government suddenly thinks about leaving it to the market. No sane investor is going to waste billions on that gamble, so a government needs to publish assurances at minimum. Both of these things ought to be factored in when you want to create a level playing field to let the market figure it out. Kinda weird to opine that creating a level playing field is "insane".

That said, it's a more accurate conclusion than I expected from a link-only comment. Usually such comments link sources rather than speaking for themselves due to extreme opinions, but that's not exactly the case here.
Your critics are more applicable to the similar robotics kits of NVIDIA and Qualcomm, which range from a little overpriced to extremely overpriced, in comparison with their alternatives like single-board computers with ARM chips from Rockchip or the like, small computers with Jasper Lake or even with cheaper Tiger Lake models, NUC-like computers with Intel or AMD CPUs, or bargain laptops (all these are under $500, while the ARM or Jasper Lake/Elkhart Lake systems are under $300, with many slower ARM SBCs under $100; the NVIDIA and Qualcomm kits range from $400 to $2000).

These kits from AMD Xilinx, i.e. Kria KV260 and Kria KR260, are very cheap in comparison with the other development systems that include an FPGA so powerful.

Their main defect is that Xilinx makes extremely few of them, so if you want to buy one you might have to wait many months or even years.

For projects that would not benefit much from a FPGA, a cheaper SBC or even just a microcontroller board of $10 or $20 would be a better choice.

However, if you have a clever idea that could be implemented with an FPGA, these new development kits are better than most FPGA boards that have been available previously.

Their main alternative are various boards with Xilinx Artix-7 FPGAs. There are boards in the same price range of a few hundred $, with FPGAs of similar size to those of the Kria kits. However the older Artix-7 FPGAs are significantly slower than the UltraScale+ used in the Kria kits, and they also do not have the 64-bit ARM cores included in UltraScale+ (which has a quadruple Cortex-A53 running Linux and also two 32-bit Cortex-R5F ARM cores, for hard real-time applications).
> In every company you have people do this for the business.

The subject is called "business continuity planning", which includes threat and risk analysis.

https://en.wikipedia.org/wiki/Business_continuity_planning#T...
For workflow stuff, I more or less do the generalized version of the xkcd Worth the Time (0). There's always initial friction bringing something new into a workflow, both from a learning and practice standpoint, which I treat as an expected upfront cost. But pretty much once I start spending more time (actively) learning about a tool than I get back in saved time, that's about the end for that workflow update. I can always revisit it if I hear about a new feature of the tool, and of course I'm passively picking up stuff as I use it.

(0) https://xkcd.com/1205
Another indicator consumer spending is dropping and costs are going through the roof. This is probably the first of a bunch of layoffs sadly. I expect Finances (Banks / Mortgage providers) are going to be aggressively reducing headcounts in the near future. One side of my family is heavily in that industry and they're all extremely nervous.

Sorry for anyone that lost their role, it's always tough to lose a job regardless of the company they worked for. I wish them all success and luck finding their next endeavor.
Sounds like a rant about Google search
More Typical Corporate Algorithmic Idiocy.

They assume that Naloxone prescription correlates with drug use which correlates with high death rates, therefor deny coverage. Yet this is literally a statewide prescription for EVERYONE AND ANYONE, but they ignore that fact, aaand collateral damage ensues.

Same as software and insurance companies assuming that high braking and cornering forces are automatically signs of bad driving when they are literally the hallmark of highly trained/skilled drivers (the difference is that the highly skilled drivers know where is the limit of adhesion and rarely exceed it while the ignorant teenager will often sail right past the limit of adhesion and slide into a tree or something).

Same as Google or Amazon deciding to ban all of a user's accounts for some reason that triggers some algorithm that maybe sometimes correctly identifies fraud or system abuse, but creates huge collateral damage when wrong.

It is pretty obvious that managers deploying technology either don't know or don't care about such consequences - they are externalizing their failures on the general population.

I don't know how to fix this sort of thing short of legally requiring companies to provide reasonable recourse and imposing costs if they don't (e.g., the damaged party can demand prompt & effective recourse and if they don't get it can easily sure and collect damages.)
Then create a blog without using any of this tech and you'll soon realise it goes nowhere.
It's not semantic versioning, but a project I am on started using calendar versioning[1]. I was hesitant to try it at first, but it's kind of growing on me. It's really easy to organize and sort. We have a pretty regular release cadence so it was easy to implement, but I could see it being more complicated for certain projects.

[1]: https://calver.org/
"Who are the future professional musicians?"

By the looks of things, it's the ones that take off the most clothes and do the most scandalous things. But maybe I'm just turning into a grumpy old man.
It is an example that nature absolutely can overcome nurture. Kids in similar situations usually fails, yes, but if they were talented enough they would have succeeded just like that guy. You can still have empathy for them and see that they struggle, no kids should have to go through that in an ideal world, but you can't say that those kids fails only because of that situation as we can show plenty of examples where talented kids makes it through.

We should help all kids from poverty, but we shouldn't ignore the huge factor talents plays in how well they will perform in school. Saying things like "rich kids only do well because they get good support" is ignorant. That support helps, but parts of it is genes as well, both are important factors, and understanding how those factors interacts is important to give each kid the best help they can get.
A big bottle of soda is 1000 or 2000 cubic centimeters. A can of soda is 200 or 300 cubic centimeters. A glass of water has 200 or 300 cubic centimeters. 92 cubic centimeters is half a glass of water.
Yeah you kinda expect a swarm of drones like a small ocean fleet. With smaller drones to protect the main cruiser.
The whole point of an NFT is that the ownership is on the blockchain and guaranteed by said blockchain - if the courts can "force" return of the NFT than the NFT isn't actually synonymous with the ownership, and so then is kinda pointless.
more trends that could benefit from more intentional long-term thinking - vegan meat-substitutes, lab-grown meat, DNA/gene editing [what else? would love to hear more from others].

In general, these trends offer nice openings for new businesses to be a first-mover and grow quickly (these days, businesses are not even making profits in the short-term).
Why not just model the json as objects in (insert favorite language) and then use that code to generate the json?
We'd need about 50 TWh of batteries. We can build that faster than we can build a single nuclear plant.

And what do nukes do during peak periods of they are supplying base power?
>It's not exhausting, you're just refusing to understand the other side of the argument.

Do you also accept the "other side" of the argument that the author of the blog post could be wrong?
Aside from the appeal to authority ("we" say X therefore X is right), you bring up some good points (although in a fairly unpleasant tone which I don't appreciate in the slightest), you still haven't answered my question - what is the fundamental difference between concurrency and parallelism?
Agreed. I think it’s appropriate to walk away from medium-interest opportunities over this because there are too many out there to consider.

With a high interest opportunity it’s less likely to come up, because those are worth the time to strategically target with custom projects, which works pretty well in my experience.

I don’t mind tech screening or leet code challenges at the right times, but an oversized amount right off the bat seems too inefficient, a ham handed way to connect with good candidates.
The coral reefs are not "largely already dead". They are actually in rude health with coverage being quite high lately:

https://www.netzerowatch.com/peter-ridd-record-coral-cover-o...
It's worse than that. I remember bars, restaurants and even sporting events were open prior to schools. Children were an afterthought.
it's kind of a lie.

The blockchains are huge and slow.

So all it means is that you have a public/private key. You end up sending and receiving money by signing stuff you don't really verify, and trust some other 3rd party website for any chain verification.

So you have a private/public key, and the rest is website. You don't really do anything on the chain by yourself
Ive installed and used Ghost several times in the past, sadly, the versioning and resource hogging is just too much. (Im specially picky on resource utilization). Nevertheless, I may try the new features and see if its worth it now. Congrats on the release!
Human drone pilots are cheap and reasonably easy to train. The "AI" that you need is the targeting and guidance system. If I can see any enemy drone on a camera, all I need to do is get a lock and fire.

The problem is that precision guided munitions are fairly expensive. Drones are cheap, but giving them any kind of offensive ability increases the cost significantly. A switchblade drone only costs about $6,000 and there still aren't swarms of thousands of them. Maybe once the economics enable massing hundreds of thousands of drones, autonomous control will become more reasonable.
It can be argued that the credential to land a PhD in CS in any of these university would have most of the time guaranteed a much much higher paying job in the industry, and potentially less stressful one at that.