skysight-inc/HackerNews huggingface dataset:
I don't think there's a polite way to put this, but to be honest this comment is an excellent example of what the parent is talking about.

All companies have needs that engineers tend to be very poor at, and if the engineers are dominant and see the other members of the organization as parasites, that's a serious dysfunction and not by any means "normal".
Not a typo, this is is actually an industry trend.

Companies think they need a "data scientist" but they actually want a "software engineer with enough stats/data background to implement data science algorithms in production."

The result is that a lot of "data scientist" jobs are mostly data engineering or ML engineering and that is reflected in the list of requirements. It makes finding a good job extremely difficult, and it's for the better that the "data scientist" title is being eroded, because it makes it easier to tell when a "data scientist" job is actually data science as opposed to something else.

Not that "data science" is a good name anyway, but that's another story.
Countries like Finland and Iceland are consistently in the top 5 of happiest countries in the world. Of course that has many non-related reasons, but the effect of intense winters can't be too bad.
Is there not a point where ignoring what you’re allowed to do and doing what’s best if it prevents massive human catastrophe is the correct option regardless of personal consequences? Nobody is going to jail for saving hundreds of lives. The media outcry would likely prevent any job loss…or was it that their systems wouldn’t allow them?
As a Kiwi now living in the UK, "unpaved roads" are not an excuse for the American excess found in vehicles like the F150, F350 etc. Unless you're literally crawling over raw grassy hills, a standard sized Japanese car (like a civic etc) will still do gravel roads just fine.
Why should scaling matter? I thought google tried to solve problems regardless of scale? Or maybe youre commending google for its ability to more effectively commodify datacenter labour in the past decade?
Let's put aside the technology not working for a second...

Isn't it ultimately leadership's responsibility to prevent these situations from occurring in the first place? Shouldn't they have been testing/auditing this system beforehand, addressing risks, and ensuring there were adequate operational plans ready in the event of an issue?

It's easy to blame software (even easier when that software clearly doesn't work), but blame ultimately should be on the people making the decisions along the way that led to this outcome.
The same reason Democrats blocked Tara Reade and RFK Jr. got censored?
Can it handle events driven within table components managed through tabbed navigation?
This isn't too far off base. High levels of inequality lead to depression and anxiety. It isn't a great feeling to almost get hit by Maseratis every other day walking to the grocery store when you can barely afford the rice and beans you eat because your rent is 75% of your income.
Hiring is always profitable as it lowers the average cost of your engineers. Layoffs are a way to accelerate that cost averaging.
It's probably pretty typical for "The Register" but the caption, "Gravy SEALs maybe, but they made a swatting call impossible" on the picture seems inappropriate for a journalism post.
It's not just about money, there are cultural changes that you can see from a distance, but when you are not in the middle of it.

For example, I used to play soccer when it was thought that doing weights made one slow or "tied up." When using any form of data was inapplicable because "soccer is different." When using a psychologist was considered weird, queer or a waste of time. And me lifting weights (I watched volleyball players and baseball players coming to the same gym I was going to doing weights all the time), using the little data available to help me better understand the game (I am a scientist after all), and being interested in the psychology of performance was seen as the quirky guy who partly you tolerate, and partly you make fun of. I was right, but I was there too soon.

Now everyone lifts weights, everyone uses data to inform decisions, and most professional players use the services of a psychologist or are interested in the psychological aspects of performance.

One thing that has changed in a major way is that what was done by the 0.001% of athletes, with the Internet, social media, and the ubiquity of cell phones, has become visible, and even the most stubborn, conservative, and skeptical people have seen how the top-of-the-food-chain trained and operated. It became impossible to deny it, to say "but for us/in our sport, it is different". It was not.
This is why it is important to take genetics into account when looking at these studies.

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5460084/

Not all of us were meant to live at higher altitudes.
To me this is a bit exemplary of how science sometimes gets functional myopia. Conceptionally obvious: Playing with step sizes gives you higher chance of getting closer to the global (not local) optimum initially, because you can scout , but you want to get your algorithm working, so let's slap on a heuristic and let's first converge for local optima with learning rate decay.
Then most people in the scientific community seem to forget (for example) about this heuristic, because it's Always Been There and direct all their focus on improving the status quo, forgetting that the assumption we put there is also a construction area. Lumpers and splitters, I guess. This sounds bitter, I'm actually happy Mr. Grimmer took this on!
> Bonus if the vague comments relate to some refactoring that you'd like to do

I am extremely ashamed to say I have left a comment like this before. At the time, I was frustrated about never being able to discuss anything over a call. There is no excuse, though.
Completely tangental: Higher air pressure makes me feel happier.
Here's the meat of the article.

> Senate Bill 680 would allow the government to prosecute platforms for promoting harmful content about eating disorders, self-harm, illegal firearms and drugs like fentanyl. Lawmakers are trying to combat online child sex abuse material too, but they’re bracing for the possibility that tech companies will attempt to block new online safety laws like they have in the past.

So it's another attempt to try and regulate "harmful" content and "misinformation" this time, by tying it to the fact teens use social media to score drugs.
Some (maybe Apple) ought to make a Swift -> Windows/Linux cross compiler...
If anything, these are orthogonal.

I had a front-row seat to some really revolutionary ideas in Google getting to the prototype stage before being squashed in the gears of "We're chasing a market and that's not how users see this product working." Stuff where, if it caught on, it'd be a paradigm shift... But it turns out users don't want every paradigm shift that comes down the lane.

Because Google has (traditionally; this has changed in recent years) a real push-pull in authority between management and engineering leadership, the company can't commit fully to building a quality implementation of a status quo. Nor can it commit fully to chasing entirely new ways of doing things that could shake up an established market. In general, this... Actually kind of works out fine for them, more fine than critics often realize, because neither of those answers are always correct. Sometimes you get Gmail. Sometimes you get Google Drive. And sometimes you get iGoogle or Wave. And sometimes you get the stuff in between, like Reader or App Engine (really popular among the users, but the users don't have the money to make it profitable to commit to it).
> But SO seems like an interesting case where they allow entitled behaviour of some devs to get out of control and it led to problems.

This is hard to quantify, and to make objective.

E.g. in a previous company HR once sent an email asking for feedback from employees, and one of my engineers gave some - polite, thoughtful, and clear. This caused quite an incident as the HR staff in question were not used to getting anything but encouragement in feedback, and I advised him to filter feedback through me, his manager.

Being "made to feel unwelcome" is both very real when you feel it, but looking slightly deeper it's not being made to feel unwelcome; it's feeling unwelcome. A mismatch of what's welcoming doesn't mean the person feeling unwelcome is correct; there may be no "correct" in that scenario. But it will be reported as though it is correct.
Where does the performance difference come from? And in what kind of processor & gpu? I didn't even know llama.cpp had a 32 bit option. For now I'm pretty suspicious it's a fair comparison.
If statements that either add conditional statements or blank lines to the SQL block. There are a lot of tradeoffs to the pure SQL method but I prefer being able to look up exact snippets in the codebase to find things.
Wow... so you have to pay tax on money you actually don't have in your wallet yet? This would be a bit of bonkers since, in fact, you may never get to the point when you get real money from your shares... Can US citizens do anything to pay when they actually get money on their bank account (i.e. when they liquidate their shares) and not before?
My god, object-relational impedance mismatch seems to be more polarizing than US politics. I've been observing this field for more than 15 years, and it's always "JUST WRITE SQL!!!!!" versus "DRY!!! DRY!!! USE ORMs SO YOU DON'T HAVE TO WRITE SQL!!!! BUSINESS LOGIC!!!" shouting matches. It's like this topic itself takes 30 IQ points away from each participant and the conversation then devolves into complete chaos.

Maybe there's some professional trauma at work, as many of us have been traumatized by shitty databases and shitty code working with them alike, ORM or not. But ORMs do come and go, promise bliss, deliver diddly, and I'm reading the same stuff I've been reading in 2008, as if nothing ever changed since.
Most engineers create tools, Google is not special in that way.

But even when there's a similar open-source tool, it may be difficult to integrate with internal systems. There's a lot of benefit to a consistent set of technologies (data formats, storage systems, etc) so that's often a reason to write internally.

There is a lot of open source software in use at Google so I wouldn't say there's a lot of reinventing the wheel. And when there is an internal clone, the requirements are often necessarily different enough to warrant writing an internal version.
DISCLAIMER 1: Current Googler here, but opinions are my own.

DISCLAIMER 2: I think from a hands-on-keyboard SWE there is a lot of useful stuff. What you mentioned about Google culture of killing products and such I am not gonna talk about.

I recommend chapters about testing first and foremost. Among all the codebases I saw (both OS and proprietary) Google tests are the most comprehensive and reliable. However, If you are in a startup-like environment you should pick and choose and not try to follow every single principle listed as they could sink your velocity drastically in the short run.

Other interesting points (IMHO) are Monorepo, Build System, and Code Reviews.

For the Monorepo I discover being a huge lover although I was skeptical. The sad thing is that it's a rather niche practice and tools like Git don't play ball very well (i.e. each time you pull you have to retrieve changes for all the codebase, even files you never saw/heard of managed by another team). I think there's no nice off-the-shelf offering for running monorepos out there. However, not having to fight with git submodules, library versions, ... is great. If the change I am submitting breaks something else in the company you are immediately aware and so can act accordingly (e.g. keep the old implementation alongside the new one and mark it as deprecated so the other team will get a warning next time they do anything).

The build system is a bit more controversial. I learned to love blaze/bazel, but admittedly, the OS version is a bit messy to set up. Additionally, being so rigorous about the build rules felt like a massive chore at the beginning, but now I appreciate it a lot. I can instantly know the contacts of all the teams that use a build rule I declared and hence can be contacted to warn them about bugs, ... . I can create something experimental and have private visibility so only my team can use it and only later expose it to the wider world with just a one liner.

Finally, the code review AKA Critique. Google has the best review tool I had the joy to use hands down. It's clear about what happens, at which stage is the review of a particular section/file and is focused on discussion. The evolution of each change is easy to follow along. These are things I really miss when using GitHub/GitLab PR view. The tooling is incredibly confusing to me. Luckily (I am not affiliated in any way) an ex-Googler (I believe) is working on an alternative that works with GitHub (https://codeapprove.com/).
You can generalize it to every market where the proxy owns the relationship with the client and captures the generated value. UI or whatever, if ChatGPT kills Stack Overflow, we will be in a situation where the shared knowledge will be at the level of 2021 and everything later will be with declining quality due to lack of data.

I'd say that it is in OpenAI's interest to pay for SO and Redit so that they don't kill the hen with the golden eggs.
I work for a 'hard' engineering company. Hard in the sense it makes physical things and does physical things. They don't give a shit about software and any of the engineering around it. And I consider that a pretty good deal from working at a finance place where I was doing support dev work on their data warehouse. There they just saw me as an expensive cost center (I was probably not paid enough in retro)

Anyway. Shoes on the other foot at SE.

What surprises me about SE is that it has all these smart people and a big community but it has let google and the parasites scrape it to death.
First of all, thank you for SQLAlchemy! If I ever had to make a final choice in how I would interact with a database for a very large project that involves a considerable dev team, I would always bet on SQLAlchemy. Not that I would necessarily like all aspects of it, but when it comes to Python and SQL - “Nobody ever got fired for picking SQLAlchemy.”.

With that out of the way, despite ORMs doing much more than "just writing SQL", it is exactly on that point that I flinch: Most devs should be exposed to SQL. And if your project allows you to build around simple enough abstractions so that you aren't reinventing the wheel, you should definitely be writing SQL. Especially if you don't know SQL yet - which is the growing case of new devs coming into the job market.

You can achieve a lot with SQlAlchemy Core, a tool that I absolutely recommend, but my post is just a simple alternative to get developers to think about their approach. If that results in some devs reconsidering using "full fat" SQLAlchemy and to try SQLAlchemy Core, that's a win for me!

Your gist tries to highlight the difficulty of doing certain things without an ORM. Migrations (as just 1 example) doesn't need to be hard, simple tools like flyway, or migrate (https://github.com/golang-migrate/migrate) achieve a similar result (while also keeping you on the path of writing SQL!). Deep and complex relationships between objects also don't need to be hard - typically people approach this subject with a requirement to be very flexible in the way they want to build queries and objects, but that to me in a sign that maybe they should reconsider their business logic AND reconsider that, just maybe, their project doesn't require all that flexibility, it is fairly straightforward to extend objects and introduce some more complex representations as and when it is needed - will all of this make me write code faster? Absolutely not. That is why you have spent so much time perfecting SQLAlchemy, but then again, I am not advocating for devs to go and replace their usage of ORMs, just presenting an alternative that may or may not fit their needs for a new project + give devs the chance to learn something that the ORM might have taken away.
Same, but since I'm only using a personal computer I attach it at home mostly to a huge monitor and is ok that way.

For work, at least 2 is desired.
Delivered on a CD?
I haven't been able to. I attempted to yesterday also with no luck. Their site mentions availability after recovering from DEF CON or something to that affect.
C++ stdlib didn’t have string_view for ages. Also, until recently, C++ sucked for things like convert to/from strings and string buffers. std::stringstream is awful.
Utilizing AI in Web Development. What Tools Do You Use?
What AI tools or technologies do you utilize in your web development process, and how do they enhance the overall design and functionality of your websites?
Our company is looking into similar solution
I think a high lr + SGD does maybe a piece of what you're talking about, and I think the most important piece. That is, the curvature can be ignored as the noise from a high lr implicitly optimizes for flatter valleys in parameter space, and I would assume that implicitly carries over to second order stuff as you could make an argument for an implicit sensing in the update step of the diagonal of the empirical Fisher via the noise of ultra high lr gradient steps.

This would imply a more genetic side component to optimization here, I believe? Since this is not a directly differentiable thing, and all of this occurs as the natural effects of a higher lr? (I.e. the evolutionary update rule being, "the parameter spaces that survive, survive". Since the parameter spaces that like to survive tend to be flat, and flatness seems to correlate with generalization, then we have a good thing our our hands.)

Adam on the other hand, I believe explicitly regularizes the update step relative to a biased (I believe, since it's not subtracted from momentum?) approximation of the diagonal of the empirical Fisher, hence being sort of a "anti-SGD" in that sense, I believe. This I think makes it really effective for models where you'll often see the data only once, and the model is ODE-like and needs information>>regularization, which we see with many LLMs these days.

Not sure if that helps any or if that's just rambling at this point, that's what I've got and what that made me think of! <3 :))))
From my experience, interacting with stack overflow and other software related sister communities has always left a bitter taste in my mouth. Ignoring the elephant in the room that I do use SO everyday with some success, but it’s mostly replaced by ChatGPT.

The ridiculous (IMHO) moderation under the guise of “we have only one purpose” often didn’t even align with that goal.

The writing was on the wall.

So many questions that could have served answers are locked, deleted, and unfortunately, never asked due to the unpleasantness of dealing with the moderation.

I speak for myself.
In Spain, people usually have one or two names, then two last (family) names. No hyphens. In Catalonia, the two family names are sometimes "anded". Example: Miquel Martí i Pol.
You may want to consider, how much that bogus science has set us back. How long have we removed tonsils, ate the food pyramid into Type 2 Diabetes, measured people's skulls for criminality, and convicted people on the results of polygraph tests?

Bogus science can move us forward, but also backwards.
Feel free to reach out internally! But in general, it seems to work ok for many popular tools. I haven't attempted to do it, maybe it sucks as the maintainer?
Give me a 3 year old laptop from anywhere else, I'd say they have dated.
Then how do they report back to the advertisers that the ads weren't skipped?

Edit: Or make them unskippable?
> the answers that are technically correct but "weird"

In ChatGPT's instance they can be downright wrong and I have to verify if what it's saying is indeed correct on many occasions.
It depends how you look at it. A lot of products created by Google were good/high quality but were killed anyway. It's sad to see things being killed because they were not "big enough".
You lost me at javascript
Optimizing/maximizing the output of art is an awfully mechanical way of looking at ART.
ADS-B is not guaranteed to be available from all aircraft in most of the airspace below 10K feet MSL. (Basically, if a transponder used to be optional before, ADS-B out is also optional.) Mode-C (altitude encoded transponder replies) are also not required, but the equipage rate is very high at this point, which is less the case for ADS-B among GA aircraft.

https://www.aopa.org/go-fly/aircraft-and-ownership/ads-b/whe...
That was the intent though. How can I buy cheap Chinese mass-produced products (usually low on the quality scale) but still have some basic quality bar that the products are not fraudulent? That they wouldn't fail basic safety standards or cause a fire or contain highly toxic ingredients. If I cared about higher quality for a given purchase, I wouldn't be choosing Amazon Basics. But for plenty of products (garbage bags, whiteboard markers, shop towels, etc ...) I just want the cheapest thing thing that actually will do the bare the minimum job.
Just use forScore, which is what every single professional musician I know uses. It's vastly better software, it's been around a lot longer, and the company isn't evil.
ML works well, when it is only trained on correct data.

ML trained on all the things ever written about programming is going to get things wrong quite a lot of the time, and you'll only have the context of its reply to you, for you to figure out whether the ML answer is correct. And of course, ML always wants to please you with an answer.

SO, on the other hand has accepted answers, and upvoted answers that are easier to decide on whether they're correct (or what you're actually looking for). And there's more nuance to it as well.
you're not going to go to a networking event once and magically make new contacts and change your life. it may take time, esp. in a setting where there are a lot of presentations and less interactions.

in a room full of aspie nerds, all of whom are kinda awkward, you may need to be the one who breaks the ice.

think of small talk like the wheels on a plane -- it's there to get you up into the sky, or to land you after a long chat, so deploy it just enough to get you in and out of more meaningful convos, onto new topics, etc.
A book on software engineering but totally missing how decisions are made around what features to build, what bugs to fix. I would have love to read more on how Google engineers prioritise work, what makes them more creative in terms of building innovative features and products. Also would have love to read how UI engineering is done while working with designers etc.
Minimum 5 days hurt. Too real. If there’s one way to destroy productivity and morale it’s to leave a vague comment on a review and not come back to it for a few days.
Nailed it. There’s a laundry list of stuff to be done, but lots of people are either still traveling or hibernating after a very hectic few weeks!
A Quickstart Guide to Privacy
If this document is intended as a how-google-does-it for applicability outside of Google, then the leadership section (Ch9) should include a heavy dose of your-mileage-may-vary. It is very good advice, but requires great cultural and executive support.

All the adages listed here make perfect sense, but they don't succeed in a vacuum. Servant leadership is great, until individuals disagree with product strategy and priorities. Addressing low performers is great, until a company's HR policies make doing so onerous.

I could go on, but there are often many things outside of your control as a leader that directly affect your capability to manage. It's all part of the job and something to account for, but set your expectations accordingly.