Do note that there's a ton of media that is not very available via sailing the seas. For example, reality TV has very low availability, typically only currently airing seasons at best. Thus if you're trying to convince a family to cancel all the big streaming platforms, you may have a hard time when they learn that they can't watch old episodes of "The Real Housewives of the middle of nowhere" from 2012.
Kalman filters are very cool, but when applying them you've got to know that they're not magic. I struggled to apply Kalman Filters for a toy project about ten years ago, because the thing I didn't internalize is that Kalman filters excel at offsetting low-quality data by sampling at a higher rate. You can "retroactively" apply a Kalman filter to a dataset and see some improvement, but you'll only get amazing results if you sample your very-noisy data at a much higher rate than if you were sampling at a "good enough" rate. The higher your sample rate, the better your results will be. In that way, a Kalman filter is something you want to design around, not a "fix all" for data you already have.
Thats just a consequence of sample rate as a whole. The entire linear control space is intricately tied to frequency domain, so you have to sample at a rate at least twice higher than your highest frequency event for accurate capture, as per Nyquist theorem.
All of that stuff is used in industry because a lot of regulation (for things like aircraft) basically requires your control laws to be linear so that you can prove stability.
In reality, when you get into non linear control, you can do a lot more stuff.
I did a research project in college where we had an autonomous underwater glider that could only get gps lock when it surfaced, and had to rely on shitty MEMS imu control under water. I actually proposed doing a neural network for control, but it got shot down because "neural nets are black boxes" lol.
True. I have often encountered motion controllers where the implementer failed to realize that calculating derived variables like acceleration from position and velocity using a direct derivative formula will violate the Nyquist condition, and therefore yields underperforming controllers or totally noisy signal inputs to them. You either need to adjust your sample or control loop rates, or run an appropriate estimator. Depending on the problem it can be something sophisticated like an LQR/KF, or even in some cases a simple alpha-beta-gamma filter (poor version of a predictor-corrector process) can be adequate.
I agree that Kalman filters are not magic and that having a reasonable model is essential for good performance.
Higher sampling rates can help in some cases, especially when tracking fast dynamics or reducing measurement noise through repeated updates. However, the main strength of the Kalman filter is combining a model with noisy measurements, not necessarily relying on high sampling rates.
In practice, Kalman filters can work well even with relatively low-rate measurements, as long as the model captures the system dynamics reasonably well.
I also agree that it's often something you design into the system rather than applying as a post-processing step.
Yeah, I try to err on the side of not using them unless the accuracy obtained through more robust methods is just a no-go, because there are so many ways they can suddenly and irrecoverably fail if some sensor randomly produces something weird that wasn't accounted for. Which happens all the time in practice.
True. It's about managing the risk rather than eliminating it. If you remove an outlier, you get a missing measurement and, as a result, higher uncertainty (error). But it is still better than keeping the outlier.
For some definition of work, yes, not every definition. Their product is not without flaw, leaving room at for improvement, and room for improvement by more than only other AI.
> There are no vulnerabilities
That's just not true. There's loads of vulnerabilities, just as there's plenty of vulnerabilities in human written code. Try it, point an AI looking for vulns at the output of an AI that's been through the highest intensity and scrutiny workflow, even code that has already been AI reviewed for vulnerabilities.
Reading around a bit, yes to Netflix adding anti-piracy measures, maybe to folks recording HDMI/DisplayPort.
Apparently, Netflix is using steganography/content watermarks in their 4k content itself to trace users who are pirating. This is from a totally unsourced Reddit thread[0] but they do reference a real company which claims to do this watermarking[1]. The claim is that in addition to Netflix requiring 4k content to be available only on platforms with Trusted Execution Environments[2], Netflix also encodes each ~10 second "chunk" of the video stream into at least 2 different versions: an Y and a Z version. Then, they serve each customer a unique series of chunks when that customer streams their content, e.g. YYZYZZZYZYYZYZYYZZYZYYZ. Then when content leaks, Netflix can examine each chunk of the leaked content to extract the ID of the user who streamed the content. Apparently, Netflix can encode a lot more than just the userID, they can also encode stuff like the individual device ID, the TEE key ID, etc.
I know you might be thinking "I could do something to defeat that" and you're probably right (e.g. take streams from multiple users and intercut them so that the bits of the watermark through time are being constantly shuffled), but I'll also bet that there's many layers of steganography we don't know about, and unless you get them all, you'll not escape scot-free.
But the only real world impact is that the device that was used to stream that 4K content gets blacklisted at the hardware level.
To workaround this, piracy groups try to batch 4K rips because they know that the device will be burned soon after they upload the content. They then acquire another device, and the game of whack-a-mole continues.
Not that I would ever pirate a movie because I'm a good boy, but I remember the Cinavia DRM that affected Blu-ray players thirteen years ago.
I'm not 100% sure how it worked, but I guess it could do a similar kind of steganography-style thing to the audio track, where they would embed keys silently and the blu-ray player would check against that.
I'm not sure if anyone actually ever managed to defeat it, I think they just stopped implementing it in streaming boxes.
What are they gonna do? Ban your account? You don't need to go through KYC to get a netflix account, so what's preventing you from using a prepaid card to sign up for another account?
Yes, when they work overtime they get paid more for that overtime than regular time.
The money doesn't somehow make it sustainable for the people burning out their lives. Working 7 days a week, including overnight shifts, for 20 years to collect a pension seems like WELL earned compensation.
That's seems unrelated to "we have so few" and "we enmiserate the one's we do have".
I think rahimnathwani's point was not that they get extra pay so it's fine, but that it seems economically irrational to overwork fewer staff if it's actually more expensive.
Here in Norway it's similar with doctors, they get paid a lot because they work crazy hours. But the doctors' association is fighting to keep it that way, as the old timers who didn't burn out along the way enjoys the high pay more than their spare time.
It's hard to argue you're underpaid if, as a result of short staffing, you're getting paid more (both in absolute terms and per unit of effort) than you signed up for.
Mostly yes. Upright fridge and freezer designs trade off efficiency for convenience (rooting around in a chest fridge/freezer can be annoying). https://youtu.be/CGAhWgkKlHI
The video down thread shows, the internal food-supports are all wire meshes with big gaps. The cold air is not squirted up and out like a syringe, it's more like the food is kept in a birdcage that's lowered and raised out of a pool of cold air.
Fly is not saying "just ignore SOC2 compliance". Fly is saying "yes, get SOC2, we had to become SOC2 compliant, and also, you can work with your auditor to achieve SOC2 compliance in a more sane way than if you just do whatever is recommended upfront."
Basically, they are saying that you should tailor your SOC2 implementation so that it's actually useful without being a horrible overbearing process, that you have that option and should take it.
Who can know what the world will look like as we "transition"? I sure don't, but I'm thankful the author here has taken a stab at it. I feel like this is one of the first stories I've seen to try to imagine this post-transition world in a way that isn't so gonzo as to be unrelatable. It was so relatable (the human-ness shining all the brighter in a machine-driven world) that I cried as I finished reading. I've felt very anxious about my own future, and to see one possible future painted so vividly, with such human and emotionally focused themes, triggered quite an emotional reaction. I think the feeling was:
> If the world must change, I hope at least we still tell such stories and share how we feel within that change. If so, come what may, that's a future I know I can live in.
Thank you for this comment, I'm so glad it made you feel a little bit better about the future, if even for a little while!
This is really the whole idea behind this project with Near Zero. I think there's a lot of anxiety out there around AI and the future, I was there for a while too. Ultimately I've ended up pretty optimistic about it all, and inspired by what the group at Protocolized is doing, found science fiction a great way to help express that.
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