He said “which bank”, which could be determined by the sniffing DNS requests, or seeing which IPs his computer is connecting to.

Not a breach of his personal information (assuming the bank that he’s using and the client he’s using after putting everything in TLS properly).

I took a flyer on some GME back during the excitement. Got in at about $35, set a limit order at $420.69 (nice) for the lolz, and was pleasantly amused when that order got filled.

Source: trust me, bro

That’s nobody’s business but the Turks.

Yes, let’s spend money on a system that only helps people in a specific set of buildings only during specific parts of the day and year when the buildings are occupied, rather than doing anything that would help society at large, at all times and anywhere in the country.

Like I said, it’s impossible to know what the right thing to do here, much less actually do it.

Hmmm, one involves fleecing school district funding in a grift, the other reduces profits to armaments manufacturers.

I really can’t figure this out! How is it possible to know?

That’s basically what Netflix did in the beginning. The challenge for Netflix is that the media companies they were licensing content from weren’t dumb, so the licensing agreements were time limited. The media companies caught up and built their own streaming platforms and now Netflix is at the receiving end of disintermediation.

Drive through seems like a great proving ground. Record every drive through customer / cashier interaction. Match each recording up with the transaction entered into the register. Train a model by having the model “listen” to the recording to predict what the order should look like, then match it to the items on the transaction receipt.

Then, phase 1 of implementation is to use the model in real time by listening to the live conversation at the drive through, predicting what it thinks the order should be, then prompting the cashier to double-check the order to see if the human made a mistake entering the order if the prediction doesn’t match.

Phase 2 is human-supervised, where the order taking system interacts directly with the customer to take the order, the human checks the result, and is able to step in / take over if there’s a mistake or a special case the order system can’t handle.

Phase 3 is “fuck your entry level employment” and no human is monitoring the system.

All 3 phases seem completely doable to me at this point, depending on how much backlash MCD is willing to deal with.

Imagine if musk could make billions of dollars on his stock if he quit his job, lol.

Ah yes. The Ballmer manoeuvre.

Passkeys sound great. Where’s the support for Firefox, Proton Pass? Bitwarden has it.

They outline it pretty well here:

https://annas-blog.org/how-to-run-a-shadow-library.html

https://www.bhphotovideo.com/c/product/1652499-REG/lg_65ep5g_b_ep5g_b_series_65_class.html

Amazon and several other companies hired like crazy during pandemic. Now they’re trying to shrink the workforce via a combination of outright layoffs and tight policies to make anyone on the verge of quitting go ahead and do it so they don’t have to pay severance.

Bonus points for shedding older, more experienced, more expensive employees vs. cheaper early in career employees.

https://www.statista.com/statistics/1324557/quarterly-number-of-amazon-employees/

https://simplelogin.io/docs/custom-domain/add-domain/

Similar vein, “Dave’s Old Porn”. I’ve found seeds for a few episodes, but never have tracked down the full set.

I’m not OP but I was curious and went looking.

I think this is it: https://librex.devol.it/

I run wireguard VPN, qbitorrent, most of the *arr apps, and Jellyfin all in containers on a headless Raspberry Pi 4, with storage backed by a NAS. It works surprisingly well, I just ensure that I never need to do transcoding.

It’s a really small dollar investment to try it to see if it meets your needs.

I’ve recoded a bunch of x264 to AV1 and routinely gotten file sizes that are 10-15% of the original file size (a little more than 1/10th the original size)

What I’ve found is that source content often has a lot of key frames. By dropping key frames down to one per 300 or one per 150 frames (one per 10 or 5 seconds for 30fps) and at scene changes, you can save a LOT of space with no loss of quality. You do give up the ability to skip to an arbitrary point in the content, however. You may have to wait a few seconds for rendering to display if you scroll to an arbitrary point in the content.

If you’re just watching the content straight through, no issues. I set CRF to achieve 96 VMAF and I can’t tell any difference in quality between the content with that setup.

I had one corpus of content that I reduced from 1.3 TB down to 250 GB after conversion.

Unfortunately, only the most recent TVs have AV1 playback built in, and the current Fire sticks, Chromecast don’t have support for playback from a LAN source. I’m hoping the next crop of Chromecast and similar devices get full support, I’m assuming it’s just a matter of time until AV1 decoding is included in every hardware decoder since it’s royalyy-free.

AV1 is the shit. Still doesn’t have broad support on consumer devices yet, but it will come.

Another option for very cheap VM, storage, bandwidth: Oracle Free Forever

https://www.oracle.com/cloud/free/

Enom