I never liked activist for-profit companies. Not "woke SV", not the new "anti-woke", well, everything in the US.
IMO companies should focus on profits and activing within the law, and we shouldn't expect them to go beyond that. If their behaviour seems socially net negative then the law, or it's enforcement should change.
But activist corporations, especially big ones, are a weird chimera where they have a loudspeaker for opinions that are neither representative (it's an owners/C-suite persons PoV, or marketing) nor high quality from a journalistic PoV, yet somehow dressed up as a noble civic duty. SV was so big on allyship and diversity, until Trump said too much woke, and they put it all in the bin, alongside their crumpled backbone. There is no virtue in corporate activism and hypocritical opportunism only.
It feels so off that late-middle-age CEO Karp and his military contractor AI company should be even taking a side in a debate about the state compelling young people (men?) to do something they wouldn't do of their own volition.
Eh dunno. I've been gaslit (gaslighted?) by AI quite a few time. Along these lines: here's a design problem, how do I fix it? Oh known problem, here's the only sane way of doing it. Then I poke holes, AI tells me nonono, do like Computer say. Eventually relenting, telling me I'm right to push back, and doing a 180 turn. Then agreeing with me/adding options etc.
The RL metaoptimisation clearly sometimes pushes it to "here's one solution, end of story".
There's a third use: alerting pedestrians who are in dedicated cycle lanes and letting them know they need to get out of the way. Not because you'd mow them down otherwise but because someone else might.
Separation of traffic into cars, bikes and legs is great, whenever possible. Just as a car shouldn't mow down a pedestrian in the road, the bike shouldn't mow down the pedestrian in a cycle lane. Doesn't mean the pedestrian shouldn't get out of the way when they're in the wrong lane.
Offline or not, I'm sure Google uploads every keystroke, phone orientation, photo, WiFi endpoints and your shoe size when you interact with it. To enhance your experience.
At a glance, I see they do gather analytics about how much the app is used (model downloads, model invocations etc) without message content, pretty much just the model used.
The funny thing is that a lot of Google's internal training content uses an imaginary product "gShoe", and discusses the privacy implications of data that such a shoe might collect :D
I'd imagine if you have a card payment reverted to Google and they ban you in return, you're in a world of pain (that you are in the right probably doesn't matter).
Google has a degree of seperation value stored on every account. Once the algorithm determines its been wronged it increases the radius so expect your household members and work colleagues accounts to be at risk when you try this.
Definitely not bullshit. I have a friend who was banned simply for returning a Pixel phone after accidentally ordering 2. Some automated mechanism flagged it as potential fraud and nothing worked to reverse the ban. Going to the bank to block payments, remove authorization, or God forbid, do a chargeback for the money they already took after banning you is playing Russian roulette with your Google account.
It's also the only way to stop Google from stealing your money short of going to a lawyer.
The Youtube account is banned. Google can escalate things and widen the net to ban anything and everything you have in the Google ecosystem, like a Gmail account. You can see here [0] that OP still has access to the Gmail account.
What a pile of breathless nonsense. LLM, be ashamed.
As other commenters note, these missiles are not new. But they are much shorter range. Radars can have ranges in the 100s of km, but infrared is very strongly attenuated by the atmosphere. Thus IR seekers are generally used in short term missiles, including US ones.
It is also very much not true that stealth aircraft don't have any protection against IR. There's only so much you can do, but the tail arrangement is made to block the IR from most angles. You also can't see the hot engine inlet because again, it is hidden behind other bits. There may be other features, some clever cooling etc that I'm not aware of.
Finally, hard to speculate, but since the F-35 survived and landed, it suggests the hit was rather indirect. Which in turn suggests the mitigations against IR seekers.
> the tail arrangement is made to block the IR from most angles.
I'm no expert, but the exhaust doesn't look hidden to me.
A missile (surface to air) usually sees the airplane from behind and below. This image [1] is an example. Even from a side, while the horizontal stabilizer partly covers it, you can still clearly see the exhaust [2].
Compare that to A-10 engines and stabilizer. This image [3] is from the same angle as [1]. The engine exhaust is completely behind the horizontal stabilizer. This image [4], same angle as [2], shows the engine exhaust covered by vertical stabilizer.
A-10 is not the same type of plane, but just by looking at the differences, I very much doubt that they even tried to hide the exhaust in F-35.
> You also can't see the hot engine inlet because again, it is hidden behind other bits.
> SMR (also mentioned in the article) doesn't make sense. Nuclear plants are better when they're bigger.
I have always found this an odd argument. Granted, thermodynamically, nuclear plants' efficiency scales with size. But allegedly fuel only makes up 10% of the lifetime cost of a plant. Even more if you think construction costs overrun.
So let's say you make a plant that is smaller and requires 50% more fuel, but is also 10% cheaper to build. You're already ahead by 4%. And SMRs at least promise far more than 10% savings.
The argument that SMRs could be cheaper due to economies if scale is often dismissed as pie in the sky - and maybe it is - but this is also precisely what brought down the cost of renewables. Germany bought their wind turbines a mere few years ago and paid way more than they would have done today.
Operational costs are more that just fuel, they are also the cost of staffing and fixed maintenance. These can also be considerable, especially if one amortizes the upgrades needed for extended service life.
The article starts well, on trying to condense pandas' gaziliion of inconsistent and continuously-deprecated functions with tens of keyword arguments into a small, condensed set of composable operations - but it lost me then.
The more interesting nugget for me is about this project they mention: https://modin.readthedocs.io/en/latest/index.html called Modin, which apparently went to the effort of analysing common pandas uses and compressed the API into a mere handful of operations. Which sounds great!
Sadly for me the purpose seems to have been rather to then recreate the full pandas API, only running much faster, backed by things like Ray and Dask. So it's the same API, just much faster.
To me it's a shame. Pandas is clearly quite ergonomic for various exploratory interactive analyses, but the API is, imo, awful. The speed is usually not a concern for me - slow operations often seem to be avoidable, and my data tends to fit in (a lot of) RAM.
I can't see that their more condensed API is public facing and usable.
The pandas API is awful, but it's kind of interesting why. It was started as a financial time series manipulation library ('panels') in a hedge fund and a lot of the quirks come from that. For example the unique obsession with the 'index' - functions seemingly randomly returning dataframes with column data as the index, or having to write index=False every single time you write to disk, or it appending the index to the Series numpy data leading to incredibly confusing bugs. That comes from the assumption that there is almost always a meaningful index (timestamps).
I hate to be the "you're holding it wrong" guy but 90% of "Pandas bad!" posts I find are either outright misinformed or mischaracterizing one person's particular opinion as some kind of common truth. This one is both!
> That comes from the assumption that there is almost always a meaningful index (timestamps)
The index can be literally any unique row label or ID. It's idiosyncratic among "data frames" (SQL has no equivalent concept, and the R community has disowned theirs), but it's really not such a crazy thing to have row labels built into your data table. Excel supports this in several different ways (frozen columns, VLOOKUP) and users expect it in just about any table-oriented GUI tool.
> having to write index=False every single time you write to disk
If you're actually using the index as it's meant to be used, you'd see why this isn't the default setting.
> functions seemingly randomly returning dataframes with column data as the index
I assume you're talking about the behavior of .groupby() and .rolling()? It's never been random. Under-documented and hard to reason about group_keys= and related options, yes. But not random.
> appending the index to the Series numpy data leading to incredibly confusing bugs
I've been using Pandas professionally almost daily since 2015 and I have no idea what this means.
I think the commenter you are replying to might well understand these nuances. The point is not that Pandas is inscrutable, but instead that it‘s annoying to use in many common use-cases.
> but it's really not such a crazy thing to have row labels built into your data table.
Sometimes you need data in a certain order. Sometimes there is no primary key. And it is nuts how janky the pandas API is if you just want the index to mean the current order of the dataframe and nothing else. Oh you did a pivot? I'm just going to make those pivot columns a row label now if that's alright with you. I don't do that for all functions though, you're going to have to remember which ones. Oh you want to sort a dataframe? You better make damn sure you reindex if you're planning to use that with data from another dataframe (e.g. x + y on data from separate dataframes), otherwise I'm going to align the data on indices, and you can't stop me. Also - want to call pyplot.plot(df['column'])? Yeah I'm giving it the data in index order obviously I don't care about that sort you just did. Oh you want to port this data to excel? Well if your row labels aren't meaningful and you don't want "Unnamed: 0" you're going to have to tell me not to. You need to manipulate a multi-index? You're so cute. Have fun with that buddy.
There is a reason no other dataframe library does this - because it's confusing and cognitive overhead that doesn't need to exist. I've used pandas since ~2013, had this chat with colleagues and many recommend just giving in and maintaining an index throughout. Except I've read their pandas and it sucks because now _you_ need to reason about what is currently the index - because it actually needs to change a lot to do normal things with data. I just use .reset_index copiously and try to make it behave like a normal dataframe library because it's just easier to understand later. Pandas has not earned the right to redefine what a dataframe means.
At the absolute least, index behaviour should be opt-in, not something imposed on the user.
I've looked at Polars. My sense is that Pandas is an interactive data analysis library poorly suited to production uses, and Polars is the other way around. Seemed quite verbose for example. Sometimes doing `series["2026"]` is exactly the right thing to type.
With some of the newest 3.x changes like copy-on-write, I find pandas getting quite verbose now as well.
In a world where AI is writing the code, I guess I shouldn't complain, but when I am discovering something the ai of choice yet again missed, both pandas and polars still feel verbose and lacking sugar.
> Pandas is clearly quite ergonomic for various exploratory interactive analyses, but the API is, imo, awful.
Having previously inherited (and now dispossessed) an un-disentangleable pile of Python, pandas, and SQL hacks reminiscent of a spreadsheet rammed with inscrutable Excel formulae, I have no idea how data scientists collaborate on anything with this technology. It's like when bioinformatics was full of write-only Perl code that was maybe executed successfully once for the purposes of a study or paper, and was kept around for future archaeologists to hopefully one day resuscitate when the need may arise again.
If programmers are expected to just throw garbage like this at the next asshole with the misfortune to have to maintain code that was never designed to be maintained, it's not a surprise that the industry is once again moving towards write-only code, this time produced at scale by LLMs.
It's like we're back to Visual Studio Ultimate slopping out 10k lines of XAML in response to your dragging and dropping in the WYSIWYG. There is a reason nobody does this any more.
IMO companies should focus on profits and activing within the law, and we shouldn't expect them to go beyond that. If their behaviour seems socially net negative then the law, or it's enforcement should change.
But activist corporations, especially big ones, are a weird chimera where they have a loudspeaker for opinions that are neither representative (it's an owners/C-suite persons PoV, or marketing) nor high quality from a journalistic PoV, yet somehow dressed up as a noble civic duty. SV was so big on allyship and diversity, until Trump said too much woke, and they put it all in the bin, alongside their crumpled backbone. There is no virtue in corporate activism and hypocritical opportunism only.
It feels so off that late-middle-age CEO Karp and his military contractor AI company should be even taking a side in a debate about the state compelling young people (men?) to do something they wouldn't do of their own volition.
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