I use --format-sort +res:1080, which, if my understanding of the documentation is correct, will make it prefer 1080p, the smallest video larger than 1080p if 1080p isn’t available, or the largest video if nothing 1080p or larger is available.
res is the smallest dimension of the video (so for a 1080x1920 portrait video, it would be 1080).
Default sort is descending order. The + makes it sort in ascending order instead.
Ah, you’re right - Trilium doesn’t use file-backed notes at all - it saves them in a database (I think Sqlite but I’m not positive).
Trilium supports writing notes in multiple formats, including Markdown.
Does your script handle bi-directional sync or one-way only?
https://github.com/TriliumNext/Notes is a fork that appears to be actively developed. Found it near the end of the issue linked from the maintenance notice.
Thanks for that! I recommend anyone who wants to minimize risk to follow their instructions for self-hosting:
Is the source code available and can I run my own copy locally?
Yes! The source code is available on Github. Its a simple static HTML application and you can clone and run it by opening the
index.htmlfile in your browser. When run locally it should work when your computer is completely offline. The latest commits in the git repository are signed with my public code signing key.
Generally people don’t memorize private keys, but this is applicable when generating pass phrases to protect private keys that are stored locally.
Leaving this here in case anyone wants to use this method: https://www.eff.org/dice
Doesn’t their API also require you to allow-list IPs, making it basically useless for dynamic DNS?
From https://www.namecheap.com/support/api/intro/ under “Whitelisting IP.”
In the game, this happens even when housing is available and affordable - the bug is that the homeless people are wealthy and there are vacant, affordable houses that they can move into, they just choose to be homeless. There isn’t even a markup from landlords, because an update already deleted them.
In real life, the problem is that we still have landlords. Idk why we don’t just delete them like the game devs did.
Reverse proxies aren’t DNS servers.
The DNS server will be configured to know that your domain, e.g., example.com or *.example.com, is a particular IP, and when someone navigates to that URL it tells them the IP, which they then send a request to.
The reverse proxy runs on that IP; it intercepts and analyzes the request. This can be as simple as transparently forwarding jellyfin.example.com to the specific IP (could even be an internal IP address on the same machine - I use Traefik to expose Docker network IPs that aren’t exposed at the host level) and port, but they can also inspect and rewrite headers and other request properties and they can have different logic depending on the various values.
Your router is likely handling the .local “domain” resolution and that’s what you’ll need to be concerned with when configuring AdGuard.
It isn’t, because their business practices violate the four FOSS essential freedoms:
- The freedom to run the program for any purpose
- The freedom to study and modify the program
- The freedom to redistribute copies of the original or modified program
- The freedom to distribute modified versions of the program
Specifically, freedom 4 is violated, because you are not permitted to distribute a modified version of the program that connects to the Signal servers (even if all your modified version does is to remove Google Play Services or something similar).
This particular scenario involves the MacOS desktop app, not the phone app. The link is showing just an image for me - I think it’s supposed to be to https://stackdiary.com/signal-under-fire-for-storing-encryption-keys-in-plaintext/
That said, let’s compare how it works on the phone to how it could work on MacOS and how it actually works on MacOS. In each scenario, we’ll suppose you installed an app that has hidden malware - we’ll call it X (just as a placeholder name) - and compare how much data that app has access to. Access to session data allows the app to spoof your client and send+receive messages
On the phone, your data is sandboxed. X cannot access your Signal messages or session data. ✅ Signal may also encrypt the data and store an encryption key in the database, but this wouldn’t improve security except in very specific circumstances (basically it would mean that if exploits were being used to access your data, you’d need more exploits if the key were in the keychain). Downside: On iOS at least, you also don’t have access to this data.
On MacOS, it could be implemented using sandboxed data. Then, X would not be able to access your Signal messages or spoof your session unless you explicitly allowed it to (it could request access to it and you would be shown a modal). ✅ Downside: the UX to upload attachments is worse.
It could also be implemented by storing the encryption key in the keychain instead of in plaintext on disk. Then, X would not be able to access your Signal messages and session data. It might be able to request access - I’m not sure. As a user, you can access the keychain but you have to re-authenticate. ✅ Downside: None.
It’s actually implemented by storing the encryption key in plaintext, collocated with the encrypted database file. X can access your messages and session data. ❌
Is it foolproof? No, of course not. But it’s an easy step that would probably take an hour of dev time to refactor. They’re even already storing a key, just not one that’s used for this. And this has been a known issue that they’ve refused to fix for several years. Because of their hostile behavior towards forks, the FOSS community also cannot distribute a hardened version that fixes this issue.
I understand that
I’m not convinced
Is it possible to force a corruption if a disk clone is attempted?
Anything that corrupts a single file would work. You could certainly change your own disk cloning binaries to include such functionality, but if someone were accessing your data directly via their own OS, that wouldn’t be effective. I don’t know of a way to circumvent that last part other than ensuring that the data isn’t left on disk when you’re done. For example, you could use a ramdisk instead of non-volatile storage. You could delete or intentionally corrupt the volume when you unmount it. You could split the file, storing half on your USB flash drive and keeping the other half on your PC. You could XOR the file with contents of another file (e.g., one on your USB flash drive instead of on your PC) and then XOR it again when you need to access it.
What sort of attack are you trying to protect from here?
If the goal is plausible deniability, then it’s worth noting that VeraCrypt volumes aren’t identifiable as distinct from random data. So if you have a valid reason for having a big block of random data on disk, you could say that’s what the file was. Random files are useful because they are not compressible. For example, you could be using those files to test: network/storage media performance or compression/hash/backup&restore/encrypt&decrypt functions. You could be using them to have a repeatable set of random values to use in a program (like using a seed, but without necessarily being limited to using a PRNG to generate the sequence).
If that’s not sufficient, you should look into hidden volumes. The idea is that you take a regular encrypted volume, whose free space, on disk, looks just like random data, you store your hidden volume within the free space. The hidden volume gets its own password. Then, you can mount the volume using the first password and get visibility into a “decoy” set of files or use the second password to view your “hidden” files. Note that when mounting it to view the decoy files, any write operations will have a chance of corrupting the hidden files. However, you can supply both passwords to mount it in a protected mode, allowing you to change the decoy files and avoid corrupting the hidden ones.
It sounds like you want these files to be encrypted.
Someone already suggested encrypting them with GPG, but maybe you want the files themselves to also be isolated, even while their data is encrypted. In that case, consider an encrypted volume. I assume you’re familiar with LUKS - you can encrypt a partition with a different password and disable auto-mount pretty easily. But if you’d rather use a file-based volume, then check out VeraCrypt - it’s a FOSS-ish [1], cross-platform tool that provides this capability. The official documentation is very Windows-focused - the ArchLinux wiki article is a pretty useful Linux focused alternative.
Normal operation is that you use a file to store the volume, which can be “dynamic” with a max size or can be statically sized (you can also directly encrypt a disk partition, but you could do that with LUKS, too). Then, before you can access the files - read or write - you have to enter the password, supply the encryption key, etc., in order to unlock it.
Someone without the password but with permission to modify the file will be capable of corrupting it (which would prevent you from accessing every protected file), but unless they somehow got access to the password they wouldn’t be able to view or modify the protected files.
The big advantage over LUKS is ease of creating/mounting file-based volumes and portability. If you’re concerned about another user deleting your encrypted volume, then you can easily back it up without decrypting it. You can easily load and access it on other systems, too - there are official, stable apps on Windows and Mac, though you’ll need admin access to run them. On Android and iOS options are a bit more slim - EDS on Android and Disk Decipher on iOS. If you’re copying a volume to a Linux system without VeraCrypt installed, you’ll likely still be able to mount it, as dm-crypt has support for VeraCrypt volumes.
c. Phrase "Based on TrueCrypt, freely available at http://www.truecrypt.org/" must be displayed by Your Product (if technically feasible) and contained in its documentation.”
reasonable expectations and uses for LLMs.
LLMs are only ever going to be a single component of an AI system. We’ve only had LLMs with their current capabilities for a very short time period, so the research and experimentation to find optimal system patterns, given the capabilities of LLMs, has necessarily been limited.
I personally believe it’s possible, but we need to get vendors and managers to stop trying to sprinkle “AI” in everything like some goddamn Good Idea Fairy.
That’s a separate problem. Unless it results in decreased research into improving the systems that leverage LLMs, e.g., by resulting in pervasive negative AI sentiment, it won’t have a negative on the progress of the research. Rather the opposite, in fact, as seeing which uses of AI are successful and which are not (success here being measured by customer acceptance and interest, not by the AI’s efficacy) is information that can help direct and inspire research avenues.
LLMs are good for providing answers to well defined problems which can be answered with existing documentation.
Clarification: LLMs are not reliable at this task, but we have patterns for systems that leverage LLMs that are much better at it, thanks to techniques like RAG, supervisor LLMs, etc…
When the problem is poorly defined and/or the answer isn’t as well documented or has a lot of nuance, they then do a spectacular job of generating bullshit.
TBH, so would a random person in such a situation (if they produced anything at all).
As an example: how often have you heard about a company’s marketing departments over-hyping their upcoming product, resulting in unmet consumer expectation, a ton of extra work from the product’s developers and engineers, or both? This is because those marketers don’t really understand the product - either because they don’t have the information, didn’t read it, because they got conflicting information, or because the information they have is written for a different audience - i.e., a developer, not a marketer - and the nuance is lost in translation.
At the company level, you can structure a system that marketers work within that will result in them providing more correct information. That starts with them being given all of the correct information in the first place. However, even then, the marketer won’t be solving problems like a developer. But if you ask them to write some copy to describe the product, or write up a commercial script where the product is used, or something along those lines, they can do that.
And yet the marketer role here is still more complex than our existing AI systems, but those systems are already incorporating patterns very similar to those that a marketer uses day-to-day. And AI researchers - academic, corporate, and hobbyists - are looking into more ways that this can be done.
If we want an AI system to be able to solve problems more reliably, we have to, at minimum:
In terms of what they can accept as input, LLMs have a huge amount of flexibility - much higher than what they appear to be good at and much, much higher than what they’re actually good at. They’re a compelling hammer. System designers need to not just be aware of which problems are nails and which are screws or unpainted wood or something else entirely, but also ensure that the systems can perform that identification on their own.
Must’ve typoed “awesome”
Apparently it’s still being actively developed! I’m impressed.
April 15, 2024 Lynx v2.9.1 release
I haven’t worked with Scribus but I’ve heard good things about it, so I don’t think you’d be making a wrong choice by going with it. For this use case, the main reasons I can think of for why LaTeX would be preferable would be:
If I’m in a fight, I’m fighting. If I’m on a walk, I’m walking. On a hike? Hiking. If I’m at a party, I’m partying. If there’s rain in the air, it’s raining. If I’m applying butter to my toast, I’m buttering my toast. If I’m on a boat, I’m boating. If I’m in the middle of a fall, I’m falling.
Is it hard to understand that someone is referring to the act of entering Fall (or being in the middle of Fall) when they call it “falling?”
Regardless of whether you find that difficult to understand or to accept, it’s a well-established linguistic phenomenon known as “verbification.”
You’re wrong on several counts.
First, you don’t suffer “falling damage” from falling. You suffer it from landing after falling (refer to page 183 of the PHB if you don’t believe me). However, casting Feather Fall is a reaction that you can take when you or another creature “falls,” so it was appropriate to cast it at the start of the season.
Second, “falling” is not the present tense of “fall.” The simple present tense of “fall” is “fall” or “falls,” but other “present tenses” include: the present perfect simple (“He has fallen”), present progressive/continuous, and present perfect progressive.
“Falling” is the present participle, and it can be used both as an adjective (“The falling bard”) and as part of the past continuous/progress (“The bard was falling”), present continuous/progressive (“The bard is falling”), and future continuous/progressive (“The bard will be falling”) verb tenses, as well as with their perfect variants (had been falling, has been falling, will have been falling).