hospadar
If that's not plunder I don't know what is.
Problems like "how do we build better automated surveillance robots? it's so inconvenient to have to actually have a human remotely piloting the kill-bots"
Sure, but why would the billionaires who own the warehouse full of GPUs permit that to happen? There's a ton of better ways capital could be distributed, and the barriers to implementing them seem to be primarily extant rich people, not the lack of super-awesome ai venture capitalists.
I'd guess that stability is concerned with their legal liability, also perhaps they are decent humans who don't want to make a product that is primarily used for harassment (whether they are decent humans or not, I imagine it would affect the bottom line eventually if they develop a really bad rep, or a bunch of politicians and rich people are targeted by deepfake harassment).
[1] https://www.cagoldberglaw.com/states-with-revenge-porn-laws/...
^ a lot of, but not all of those laws seem pretty specific to photographs/videos that were shared with the expectation of privacy and I'm not sure how they would apply to a painting/drawing, and I certainly don't know how the courts would handle deepfakes that are indistinguishable from genuine photographs. I imagine juries might tend to side with the harassed rather than a bully who says "it's not illegal cause it's actually a deepfake but yeah i obviously intended to harass the victim"
"this thing we sell might destroy humanity?!"
"but yeah we're gonna keep making it cause we're making fat stacks from it"
Is the move here just trying to seem like the good guy when you're making a thing that, however much good it might do, is almost certainly going to do a lot of damage as well? I'm not totally anti-ai, but this always smells a little of the wolves guarding the henhouse.
I wonder if this is what it felt like back when we thought everything was going to be nuclear powered? "Guys we made this insane super weapon!! It could totally power your car!! if it leaks it'll destroy all life but hey you only have to fill the tank once every 10 years!!"
It seems pretty logical to assume to me that you'd almost always have fewer ped fatalities if more people were biking instead of driving.
[1] https://www.theguardian.com/commentisfree/2018/mar/08/killer...
That's (probably) good for getting the most important papers to the top, but it also strongly disincentivizes whole categories (often very important paper). Two obvious categories are replication studies and negative results. "I tried it too and it worked for me" "I tried it too and it didn't work" "I tried this cool thing and it had absolutely no effect on how lasers work" could be the result of tons of very hard work and could have really important implications, but you're not likely to make a big splash in high-impact journals with work like that. A well-written negative result can prevent lots of other folks from wasting their own time (and you already spent your time on it so might as well write it up).
The pressure for impactful work also probably contributes to folks juicing the stats or faking results to make their results more exciting (other things certainly contribute to this too like funding and tenure structures). I don't think "don't care about impact" is a solution to the problem because obviously we want the papers that make cool new stuff.
But making regulations is much easier if you’re very wealthy, so you advocate for regulations that keep you wealthy with a very expensive loud voice and that creates a pretty strong feedback cycle.
One way out (seems to me) is chopping the top off the wealth curve and redistributing - it might matter less that poorer folks are getting money and more that extremely wealthy folks have less insanely disproportionate power to make a world that suits only them.
omg switching away from jenkins (in our case to gitlab CI) was a revalation. SO much easier to use. There were a ton of things we were avoiding doing in CI (or at all) that we started doing (easily) once we switched.
> it must work properly, and I don't expect it to be pretty
Too often it really _didn't_ work properly, or the gap between where we were and "working properly" was a mysterious foggy ocean with no clear path.
To be fair, we drove it pretty hard, we had some jobs that ran thousands of tests on big clusters of nodes to validate and deploy huge ETL pipelines, but man it was nice to have that work smoothly with a nice UI that made sense with super-well-documented pipline commands. It did _basically_ work with jenkins, but the experience of troubleshooting problems and adding new features was a constant pain point that really dragged out a lot of work.
For safety stuff, justice-related decision-making, etc I think explainability is critical, but on the other hand for something like "match doodle to controlled vocabulary of shapes" (and tons of other very-simple-for-humans-but-annoyingly-hard-for-computers problems), why not just use the tiny model?
Maybe if we get really good at making ML models we can make models that invent comprehensible algorithms that solve complex problems and can be tweaked by hand. Maybe if we discover that a problem can be reasonably well solved by a very tiny model, that's a good indication that there is in fact a decent algorithm for solving that problem (and it's worth trying to find the human-comprehensible algorithm).
Sure maybe you’ll bootstrap an amazing product with some secret sauce that’s magically hard to copy, but more likely you’ll need a bunch of people (we’ll call them “investors”) to give you their approval (we’ll call it “money” or “capital”). If your great idea with no investors is competing against someone else’s pretty-similar-but-not-quite-as-good-idea-except-they-have-a-hundred-million-dollars, you’re probably going to lose.
If the group of people who can access that capital is very homogeneous (and it is in real life), we’re probably missing out on designs and ideas and innovations that would otherwise make everything better.
Also worth noting that this isn’t just about gender and race/ethnicity, disability is a great practical example: disabled folks are more likely to create things that are accessible for disabled folks, but non-disabled folks very often benefit from that accessibility (i.e. stuff is easier to use). We’d be shooting ourselves in the collective foot to have only non-disabled folks making stuff.
/s
This kind of attitude is a wide-open door for racist and classist attitudes to penalize kids of color, kids from poor homes, kids with unsafe or unstable home situations. Suspending and expelling kids almost always makes things worse for those kids.
There are HUGE racial and gender disparities in the rates of suspension and expulsion[1].
Anecdotally, I know a lot of educators and child social workers who are strongly opposed to suspension & expulsion as a punishment or a "solution". None of them cite "metrics obsession" as their reason, but rather the fact that the kids who are getting kicked out of school need more support, not less.
Maybe it seems fine to kick [other people's] kids out of school "for the good of the many", but happens next? What if parents loose their job because they have to stay home for childcare? What if folks end up homeless because they can't pay the bills? What if those kids end up in prisons (that our taxes pay for)? Just from a financial perspective, school is an EXTREMELY cost-effective early intervention compared to prisons, inpatient mental health, welfare systems, etc. Well educated folks often end up making money and paying into tax systems rather than drawing from them.
[1] https://nces.ed.gov/programs/raceindicators/indicator_rda.as...
Not sure we want china firing freshwater ice at utah on a ballistic trajectory?
<this is a funny joke post don’t freak out man>
Why else would uber be so desparate to prevent their drivers from being classified as employees?
https://luxurylandyacht.wordpress.com/
I've built some small boats and stuff, but this was a whole-nuther dimension Took about 11 months of pretty intense almost-every-day work by two people.
High impact journals [6] tend to prefer exciting, novel, and positive results (we tried new thing and it worked so well!) vs negative results (we mixed up a bunch of crystals and absolutely none of them are room-temp superconductors! we're sure of it!).
The result is that cherry picking data pays, leaning into confirmation bias pays, publishing replication studies and rigorous but negative results is not a good use of your academic inertia.
I think that creating a new category of rigor (i.e. journals that only publish independently replicated results) is not a bad idea, but: who's gonna pay for that? If the incentive is you get your name on the paper, doesn't that incentivize coming up with a positive result? How do you incentivize negative replications? What if there is only one gigantic machine anywhere that can find those results (LHC, icecube, etc, a very expensive spaceship)?
There might be easier and cheaper pathways to reducing bad papers - incentivizing the publishing of negative results and replication studies separately, paying reviewers for their time, coming up with new metrics for researchers that prioritize different kinds of activity (currently "how much you're cited" and "number of papers*journal impact" things are common, maybe a "how many results got replicated" score would be cool to roll into "do you get tenure"? See [3] for more details). PLoS publish.
I really like OP's other article about a hypothetical "Journal of One Try" (JOOT) [2] to enable publishing of not-very-rigorous-but-maybe-useful-to-somebody results. If you go back and read OLD OLD editions of Philosophical Transactions (which goes back to the 1600's!! great time, highly recommend [4], in many ways the archetype for all academic journals), there are a ton of wacky submissions that are just little observations, small experiments, and I think something like that (JOOT let's say) tuned up for the modern era would, if nothing else, make science more fun. Here's a great one about reports of "Shining Beef" (literally beef that is glowing I guess?) enjoy [5]
[1] https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6668985/ [2] https://web.archive.org/web/20220924222624/https://blog.ever... [3] https://www.altmetric.com/ [4] https://www.jstor.org/journal/philtran1665167 [5] https://www.jstor.org/stable/101710 [6] https://en.wikipedia.org/wiki/Impact_factor, see also https://clarivate.com/
One of the biggest issues with any attempt to extract information from an fMRI scan is resolution, both spatial and temporal - this study used 1.8mm voxels which is a TON of neurons (also recall that fMRIs scan blood flow, not neuron activity - we just count on those things being correlated). Temporally, fMRI sample frequency are often <1hz. I didn't see that they mentioned a specific frequency, but they showed images to the subject for 3 seconds at a time so I'd guess that's designed to ensure you get a least a frame or three while the subject is looking at the image. You can sort of trade voxel size for sample frequency - so you can get more voxels, or more samples, but not both. So detecting things that happen quickly (like, say, moving images or speech) would probably be quite hard (even if you could design an ai thingey that could do it, getting the raw data at the resolution you'd need is not currently possible with existing scanners)
Also, not all brain functions are as clearly localized as vision - the visual cortex areas in the back of the brain map pretty directly to certain kinds of visual stimulus, while other kinds of stimulus and activity are much less localize (there isn't a clear "lighting up" of an area). You can get better resolution if you only scan part of the brain (i.e. the visual cortex) (I don't know if that's what they did for this study), but that's obviously only useful for activity happening in a small part of the brain.
ANYWAY SO COOL!!! I wonder if you could use this to draw people's faces with a subject who is imagining looking at a face? fMRI police sketch? How do brains even work!?
we could call it a "credit card"
In my experience, the benefits of a SQL table for a problem like this are real big - easier to see what's in the queue, manipulate the queue, resolve head-of-queue blocking problems, etc.
[1] http://large.stanford.edu/courses/2016/ph240/holmvik1/docs/d...