If LocalSend is running on iOS and Windows does LocalSend have the ability to send photos?
Yes, I use it all the time.
Both devices need to be on the same network (LAN / WiFi), however. LocalSend does not use Bluetooth.
If LocalSend is running on iOS and Windows does LocalSend have the ability to send photos?
Yes, I use it all the time.
Both devices need to be on the same network (LAN / WiFi), however. LocalSend does not use Bluetooth.
You could even have something like an MCP to which the LLM could pass "topics", and then it would return products/opinions which it should "subtly" integrate into its response.
The MCP could even be system-level/"invisible" (e.g. the user doesn't see the tool use for the ad server in the web UI for ChatGPT/Claude/Gemini.)
Doing that for years
> Used as supplied, Google Tag Manager can be blocked by third-party content-blocker extensions. uBlock Origin blocks GTM by default, and some browsers with native content-blocking based on uBO - such as Brave - will block it too.
> Some preds, however, full-on will not take no for an answer, and they use a workaround to circumvent these blocking mechanisms. What they do is transfer Google Tag Manager and its connected analytics to the server side of the Web connection. This trick turns a third-party resource into a first-party resource. Tag Manager itself becomes unblockable. But running GTM on the server does not lay the site admin a golden egg...
By serving the Google Analytics JS from the site's own domain, this makes it harder to block using only DNS. (e.g. Pi-Hole, hosts file, etc.)
One might think "yeah but the google js still has to talk to google domains", but apparently, Google lets you do "server-side" tagging now (e.g. running a google tag manager docker container). This means more (sub)domains to track and block. That said, how many site operators choose to go this far, I don't know.
https://developers.google.com/tag-platform/tag-manager/serve...
Interestingly enough, printed QR codes physically degrading as described in the article is actual bit rot, albeit a form often overlooked.
I mean, they could be better (to put it nicely), but there is a legitimate use-case for them and I'd love to see more work in this space.
https://machinelearning.apple.com/research/introducing-apple...
The clever LLM scrapers sound a lot like residential traffic. How does the author know it's not? Behavior? Volume? Unlikely coincidence?
> random User-Agents that overlap with end-users and come from tens of thousands of IP addresses – mostly residential, in unrelated subnets, each one making no more than one HTTP request over any time period we tried to measure – actively and maliciously adapting and blending in with end-user traffic and avoiding attempts to characterize their behavior or block their traffic.
They accomplish this by providing home users with some app that promises to pay them money for use of their connection. (see: HoneyGain, peer2profit, etc.)
Interestingly, the companies selling the tunnel service to companies and the ones paying home users to run an app are sometimes different, or at least they use different brands to cater to the two sides of the market. It also wouldn't surprise me if they sold capacity to each other.
I suspect some of these LLM companies (or the ones they outsource to capture data) some of their traffic through these residential proxy services. It's funny because some of these companies already have a foothold inside homes (Google Nest and Amazon Alexa devices, etc.) but for a number of reasons (e.g. legal) they would probably rather go through a third-party.
They must have a way to decrypt payloads or otherwise get into the system they built and control. The fact that they let law enforcement know when someone is stalking someone with an AirTag shows that the data is available to them. It’s silly to think otherwise, paper or not.
Not technically correct. Apple devices (and Android phones with the appropriate app) detect if an unknown AirTag is moving with them and makes it home, possibly signalling a stalking attempt.
The heuristics for this happen locally; Apple isn't "aware" of this happening. That said, when you first set-up an AirTag, the serial is tied to your account. Therefore, when you physically find an unknown AirTag and report it to law enforcement, they can then subpoena (or get a warrant?) Apple for information on the AirTag owner's identity.
The serial itself, and any personal identifiers, are not used in the locating process, however.
This is well documented in the paper above, in articles, as well as in reverse engineering efforts.
This screen: https://i.imgur.com/jRS7Ffx.png
If there is a setting somewhere I can toggle so I get a "full" reboot, I would appreciate someone pointing it out to me.
SpringBoard is the process that shows the home screen, and does part of the lifecycle management for regular user apps. (i.e. if you tap an icon, it launches the app, if you swipe it away in the app switcher, it closes the app)
It is restarted to make certain changes take effect, like the system language. In the jailbreaking days, it was also restarted to make certain tweaks take effect. Of course, it can also just crash for some reason (which is likely what is happening to you)
I would just consult a fan wiki, but that doesn't work if the title isn't popular or if the book is too new. This seems like the perfect tool if it can somehow maintain coherency across multiple books.
That said, I do understand (and share) a lot of the frustration and hesitancy that people here have around AI tools; I don't want an app that takes away the act of thinking (like that post recently about teachers using AI to make banal lesson plans, and students in turn using AI to write essays -- what is the point then?). I hope you don't take it too much to heart, and try to showcase use cases where your app can actually provide value.
Another piece of feedback is it would be great if this could be all packaged up into a docker image that would make it easy to deploy on a local machine (or like on a home server/NAS). Right now it seems there are still a lot of manual steps and scaffolding.