The flip side of this laziness is that now, when my elected representatives tell me "these are just license-plate readers that don't record video", I have evidence to show them that's false.
If Flock had done a more competent job of securing their system, it would be harder to demonstrate this in a compelling way. To a technically-inclined person, it's obvious from the get-go that somewhere in Flock's pipeline, video is being recorded and archived, and is therefore vulnerable to misuse. But the more they're allowed to keep the implementation proprietary, the easier this is to sweep under the rug.
Exactly. It helps they also control who can even run for office in any meaningful way. Nobody fights the left harder than Democrats. Good luck finding a representative that is against data centers, flock, Israel, congressional stock bans and pausing and regulating AI, views overwhelming popular with the majority of the actual American public.
Funny. In my experience, nobody fights the “leftists” harder than the Democrats. I think the Republicans fight the Democrats harder than anyone else, and aside from the “leftists”, no political group seems to really fight the Republicans.
You are misunderstanding basic political terminology then, if you think it's somehow odd that leftists are against Democrats. Democrats and Republicans are both capitalists and liberal in the classical sense, both of which leftists oppose.
>Good luck finding a representative that is against data centers, flock, Israel, congressional stock bans and pausing and regulating AI, views overwhelming popular with the majority of the actual American public.
That is rapidly becoming Democratic party orthodoxy. At the very least there are a sizable number of Democrats who fit that.
Don't know why you're getting downvoted, but hackernews is very anti-democratic in nature. One thing politicians quickly realize, especially local ones, is that you do have to be accountable to voters at the end of the day. One or two bad stories is enough to sink a local race too, or at minimum require a massive spend to overcome the negativity.
Local politics is where you understand how effective a handful of people can truly be.
Happy to read people are understanding the true power they have collectively instead of as individuals.
Separately from how you present the number, the very concept of "uptime" as a single number is a bit muddy in the context of a distributed system, where different components can be differently available for different users.
Also, 0.1% downtime in the form of a 45-minute outage per month is very different from 0.1% of requests failing in brief bursts. You often see downtime reported as "increased error rates" which is so vague as to be meaningless.
Exactly. If my build and test CI takes several hours and it gets interrupted, it really doesn’t matter how long the interruption was. It impacts me all the added time of realizing it stopped, investigating and confirming why it stopped, triggering another run, and continued monitoring.
If anyone was tracking that time they'd realize running your own build servers is cheaper. But capex is kryptonite to MBAs so you get a shitty unreliable cloud service instead.
There was a push to take the Datadog/whatever dashboard, full of lots of different meters and graphs and numbers, and simplify it all down to a single, easy-to-read-at-a-glance number. Which of course loses all sorts of details on what's actually going on, but it meant that someone who isn't an expert in the system could at least know if something is up or not. That's the trade off, and Goodhart's law applies. The reality is you can't meaningfully boil a complex system down to one simple number. Expertise is still required, and as with all leaky abstractions, to do a good job, you really do need to dig into the systems guts and get your hands dirty and really get to know the details.
Beyond "not working", concurrent editing is likely to silently lose data, or corrupt data, or possibly just fill up your drive with lots of "conflicted copies" that you have to manually reconcile.
When I read about this project, it doesn’t seem like concurrency is much of a concern. I think it’s _supposed_ to be treated like sharing a document with someone else.
If a capsule is a recipe, like in one of the examples, that’s pretty cool. If a capsule is a recipe _manager_, then I think it would get messy.
For anyone who finds themselves in the vicinity of Atlanta. I can highly recommend the Mimms Museum of Technology and Art. Which was also formerly called the Computer Museum of America, but AFAIK has no relation to the one in San Diego.
Anyway, it's clearly a labor of love. They have some very cool artifacts from the space program (e.g. a some of the Space Shuttle and Apollo main computers). And a large fraction of the floor space is devoted to a new, very comprehensive exhibit on the history of Apple, with just about every product they ever made plus some internal prototypes.
The blog post doesn't seem to mention what strikes me as the most interesting application of a model like this, namely extracting semantic information from its latent space. It mentions robotics applications, but only in the context of generating realistic world models for simulation.
If you have a robot deployed in an environment, generating synthetic views of the environment you're in doesn't have any obvious value. What does have obvious value is the latent knowledge that the model could have used to generate those synthetic views.
For instance, the fact that Atlas is capable of identifying regions of the input images that look like "floors", and smoothly interpolating them and filling in gaps with more floor, suggests that it has a concept of "floor-like walkability" which it's learned from the examples in its training data. And being able to identify the regions of 3D space that correspond to that semantic label would obviously be useful for robot path planning.
There's plenty of literature about e.g. using neural networks to estimate walkable areas from a point cloud. And you could imagine just bolting one of those methods to the front of Atlas, using the synthesized point cloud (instead of traditional photogrammetry or LIDAR) as input. But that seems like it's throwing away a lot of potentially useful semantic information, on top of being needlessly inefficient.
As a World Labs customer, I suspect they are using existing 3D assets when creating their environments. For one thing, a vendor of 3d models for AI mentioned Word Labs as a customer on a webinar.
I don't know if that undercuts what you're saying entirely. But if they're just protecting the splat in real-time based on the camera path through a 3d world, would the model truly understand that it's a floor?
I am not sure why creating synthetic view of the environment should not have any value.
When you plan your path to go somewhere you can imagine how it would look like based on what you know and when new information comes in that contradicts it it gets updated to what it's really like.
The robot could do the same thing. It could create images/views of what path it wants to take and start acting on it without knowing the real situation yet.
Granted, the 3D representation that atlas also provides is probably more useful than just an image but the idea remains the same, we are giving robots a kind of idea how the current world around them most likely is based on previously learned data of other locations
What is the scenario you're thinking about? This is kinda what happens with VLAs, the latent knowledge of an LLM can help in action generation pipelines, but it's also kinda slow.
Surely there are all kinds of interesting and constructive classroom discussions to be had about lawbreaking.
Classrooms teach about reality (among other things) and there are many things in reality that don't involve obedience to the law, as it exists at a particular time and place.
Another interesting non-hypothetical example: many US states have so-called "blue alerts" which are used to send cell phone alerts whenever a police officer is attacked or injured. I used to live in Texas and blue alerts were a fairly frequent occurrence.
The stated justification for blue alerts is to warn the public of dangerous criminals. But they are only issued in response to attacks on cops, regardless of the level of danger to any other people. Also, at least in Texas, they're broadcast statewide. Texas is an awfully big state, and so the alerts are guaranteed to be irrelevant and non-actionable for the vast majority of people who receive them.
So it's fairly obvious to me that blue alerts are first and foremost a propaganda operation, aimed at perpetuating the stereotype that policing is a uniquely dangerous job. (It is indeed more dangerous than an average office job, but it has a much lower rate of fatal injuries than construction, or farming, or driving garbage trucks.)
> However, on issues events, github.event.pull_request is always null.
This is extra dumb because even if you thought this condition was correctly testing the user's identity, it shouldn't have "appeared protective" upon even a moment's thought. If it worked correctly, it would obviously just exclude one bot user while allowing all other users, so it wouldn't provide any protection at all.
But more likely, this condition was never intended to be "protective" at all, and it's only being described that way because the writeup is LLM slop.
If Flock had done a more competent job of securing their system, it would be harder to demonstrate this in a compelling way. To a technically-inclined person, it's obvious from the get-go that somewhere in Flock's pipeline, video is being recorded and archived, and is therefore vulnerable to misuse. But the more they're allowed to keep the implementation proprietary, the easier this is to sweep under the rug.
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