What would be a good way to backup the passwords stored in Bitwarden? I am worried that someday suddenly bitwarden could stop working and I will lose access to all the stored passwords? Should I have a physical copy of all the passwords stored in a vault at home?
The simplest way of doing this would be to export your bitwarden vault in plaintext (as a json or csv) and then store it as a password protected zip file.
This should be easy to encrypt and decrypt on all operating systems, and would make it easy to move your vault to a new password manager.
If you have some sort of home server, I'd recommend hosting vaultwarden (an open-source implementation of the BitWarden server). It works fine with the official apps. Their enterprise model requires a standard API, so it's not going to break anytime soon.
This does not take the need for separate backups way though. In fact, I'd argue it makes it even more important to maintain a 3-2-1 backup of your vault.
Running vaultwarden on a home server is one small disaster away from losing everything. Homelabs typically don't enjoy the same level of protections and redundancies compared to a commercial DC.
Use the export feature and just save the file somewhere safe, mine is in a Cryptomator vault. You could also import to Keepass and then delete the file.
Frankly I would worry about that with any third party that holds my data. There are a few Bitwarden exporters on Github that also account for attachments (something the builtin exporter doesn't for some reason).
BW synchronizes all your data on each client... if you logged in before, and your server goes down, you can still log in to a recent client, it just won't be able to update
Ya, I am a runner myself but I have heard this from some other friends. They all can play sports involving a lot of running but cannot seem to enjoy running for it's own sake. It might be personality thing, I am introverted so tend like running more because it doesn't need people or coordination. Plus it is highly accessible wherever I go.
I guess I am a likely target audience for such a tool since I work in marketing & we consume such research, so I read through the website and there is a lot of text about "AI" & how this revolutionizes market research ,etc. But I still have no idea about how it actually works. I will not be able to explain to someone why should they invest in this tool. At some level, it sounded like a wrapper on existing LLMs and I am also not clear on what exactly does it automate. It would help to have a detailed example of what exactly this tool does and why I should use this instead of directly using Claude or ChatGPT.
MarqtAI is a SaaS market research application, which uses 4 user inputs to perform automated market research online. The tool consists of multiple specialised AI nodes, making it a multi-model AI. It works by taking your parameters to contextualise the research it does for your company. It will then collect this data, often hundreds of different sources. For example, focusing it on the right segment or product. The user selects one of 20 research areas to pinpoint which marketing area you are working on, such as branding, trends or segmentation, etc. After that MarqtAI will collect data around specific research questions. Various LLM agents will go through a process of compiling that data, analysing it and eventually, produce a balanced report that contains all findings and recommendations. It is specifically trained to only use the data that has actually been collected. We recommend you use those findings with the chat assistant which is grounded on the collected data, instead of using LLM knowledge.
The major differences are:
- All the expertise needed to perform market research and analyses is built in.
- MarqtAI collects much larger datasets and through that achieves a higher accuracy.
- It is grounded to research data, so you are unlikely to see hallucinations or mistakes.
I can relate to this. I am also partially color blind and when bouldering without glasses, I so often mess up the foot holds. My partner often thinks I am cheating until I tell her that I couldn't make out the color.
Interesting that glasses seem to help for you differentiating colours?
I guess without glasses everything is a bit worse in general, but they don't really help me see colours better. (But if I got the holds right for my hands, my memory is generally good enough to avoid 'cheating' with the feet not a problem.)
I keep meaning to try giving my climbing partner a later pointer, so they can point out the next coloured hold more easily than with vague descriptions.
There are glasses that, AFAIK, shift the wavelength of incoming light in some certain way such that a colorblind wearer can differentiate real-world colors that they'd normally have trouble telling apart.
It doesn't magically allow colors to show up that they're physically incapable of perceiving, but AIUI it shifts real-world colors that they'd have difficulty telling apart into other colors that they can tell apart, if that makes any sense.
I'm not sure about shifting wavelengths (that seems way too complicated), but you could just block all out the red light on the right eye and all the green light on the left eye, and that would do the trick for someone who's red/green blind.
Maybe, though that assumes they have two fully functioning eyes. I'm not colorblind, but my two eyes can't work together because they don't converge. I wouldn't be able to rely on building a complete image from two incomplete signals; I need a complete image in my left eye in order to see.
Instead of putting these two filters on different eyes, you could put them one after another in time, I guess.
Or you could put a green-blocking filter on the left side of your view (on both eyes) and a red-blocking filter on the right side of your view (on both eyes), and you would move your head around a bit to figure out green from red.
Or you could have a checker-port pattern with the two filters or so.
I'm not sure about straight-up glasses, but there are a few effects you can exploit to enhance hue distinction in the normally afflicted regime (necessarily always at the cost of some other sort of distortion).
The simplest example is just (for red-green colorblindness) red-tinted or green-tinted glasses. You lose some dynamic range and add a distortion across the spectrum, but you gain brightness as a channel whereby you can distinguish many reds from many greens. I used to use strongly orange-tinted glasses to help spot orange buoys in the ocean, which otherwise wouldn't stand out very well against the greenish notes in the water. They'd appear quite bright against a dark background.
A usually less disruptive and less effective strategy is something like what enchroma does. Real objects aren't just red or green. They reflect a variety of rays across the spectrum. If you add a notch filter to remove the light between the two affected cones, green objects will activate the green cones nearly the same as before and the red cones less than before (and vice versa for red objects). That doesn't matter for pure colors like a red or green laser, and it doesn't allow you to see new colors, but it makes most red things a little more red and most green things a little more green, slightly improving hue discrimination (also making some objects nearly black if they hit that notch filter exclusively).
And so on and so forth. Normal lenses won't have any photon upconversion or downconversion or anything, so your only available mechanism is altering the transmission spectrum, blocking some wavelengths more than others, perhaps differently in different eyes or parts of your field of vision. You can give up some other information to add a little resolution to that hue distinction information channel.
With computers in the mix, you can tune that a little better by also shifting hues. Doing so "correctly" is a little hard though. You'd like to do something like just move the problematic wavelengths somewhere else (ideally bijectively, squishing other wavelengths to make room for the displaced ones), but your computer monitor doesn't output a whole spectrum of wavelengths; it outputs mixes of three (three distributions really, but we don't really care). Red and green are two of them, and those are the very things you'd like to distinguish better, so your only real option (realness being measured in ability to help you strongly distinguish red and green) is to add or remove some extra blue (e.g., adding a lot when red dominates green or a little at the other extreme) or to alter the brightness in response to red/green discrepancies. Most OS's want to keep brightness invariant in their colorblindness settings, so the only option is messing with the blue channel. Doing so removes your ability to distinguish some colors relying on the blue channel and adds the ability to tell red from green, with varying degrees of efficacy depending on who coded it and how many details they accounted for.
You could, in theory, have something like a VR (AR? You're augmenting the existing data, but the tech capable of doing that is closer to a VR headset) experience to do a transformation like that on real-world visual data. Maybe simpler when climbing, AR could add stripes or some other distinguishing feature to handholds of a certain color.
Anywho, maybe try sunglasses strongly tinted as the color of the handholds you'd like to spot.
Thanks for the write-up. As far as I can tell, what you are describing in your first three paragraphs is exactly what I was trying to describe? Block specific wavelengths. (EDIT: sorry, I was mixing things up. My comment that I was referring to is https://news.ycombinator.com/item?id=41066579 but yours wasn't in reply to it.)
I don't think wearing any goggles with screens in them is realistic for climbing at the moment.
Yes, adding more distinguishing factors to the climbing holds works. A laser pointer's dot can be seen as a very temporary distinguishing mark.
I am on a 10 year old Kindle and looking to replace it but most of my ebooks are from Amazon. Would it be seamless to transfer my books to Kobo via Calibre or some other software or it will be pain in the butt?
From family with a mix of kindles and kobos: yes, this is painless.
You can check beforehand by installing Calibre with the de-DRM plugin and transferring a few books: Once they are on Calibre you are good to go.
One thing I only learned today is that you can set up web sync from Calibre to Kobo [0], [1], but just plugging in to sync has been working fine for me.
For the initial sync, it used to be you could directly de-DRM your whole collection from the storage of the kindle desktop app. At some point the desktop app was using a DRM that had not been broken: I do not know if this is still the case, or if there is another way to download everything from your account.
>The European Commission, the executive body of the EU, launched a probe in July, saying that the proposed deal could result in Amazon hindering iRobot rivals from competing on Amazon’s online marketplace. The commission argued that Amazon could delist or reduce rival products’ prominence in search results or elsewhere.
Amazon more than once hindered competitors on their marketplace, so their previous behavior is the reasons for the objection by the EU.
This is one of the things that makes me full of wonder and awe! When we humans put our heads to something we can kick ass. Unfortunately, off late our heads have been into kicking each other instead of building something.
where does this fit in? I am reading Intro to statistical learning, so wondering if this should come after it or I can directly jump to this when I reach the unsupervised ML techniques.
Using meetup to find a local running group has been an interesting experience. I am not buddies with them but it is nice to get out of the work bubble.
