gnu

Reading the news while having breakfast, though it's now on my laptop instead of the newspapers I started this habit with.

I think the main problem with searching for fediverse posts is not that they're not indexed but the lack of a singular tag to append when you want to search for them. To search for reddit posts it was easy because you could put in your keywords and stick 'reddit' or 'site:reddit.com' onto the end, but now there's too many domains to keep track of and you can't rely on appending 'lemmy' pointing a search engine towards all Lemmy instances, let alone kbin/mbin instances.

I do like Whirlpool, an Australian forum primarily centred on technology. It's still active despite the general decline of forums, has a lot of useful info to turn up in searches, and I appreciate how it has remained clean and fast without the visual clutter and wasted data of modern web design.

I've found a plunger useful for a sink occasionally, a bit of back and forth plunging can loosen up a hairball or break a layer of fat/soap scum. On the other hand I've never needed to use a plunger on a toilet - I don't know how much of this is exaggeration on the internet but Australian toilets don't seem to have anywhere near the amount of issues the American designs do.

It'd be interesting to see how much this changes if you were to restrict the training dataset to books written in the last twenty years, I suspect the model would be a lot less negative. Older books tend to include stuff which does not fit with modern ideals and it'd be a real struggle to avoid this if such texts are used for training.

For example I was recently reading a couple of the sequels to The Thirty-Nine Steps (written during WW1) and they include multiple instances that really date them to an earlier era with the main character casually throwing out jarringly racist stuff about black South Africans, Germans, the Irish, and basically anyone else who wasn't properly English. Train an AI on that and you're introducing the chance for problematic output - and chances are most LLMs have been trained on this series since they're now public domain and easily available.

A broken wisdom tooth with one of the parts rubbing against the nerve that passes through that side of the lower jaw. Definitely would not recommend, it did cost me ~$2k to pull those wisdom teeth (or what remained of them for the lower ones) but it was well worth it.

Edit: Found the x-ray image of that tooth, the dentist told me the white line running past the bottom of the broken tooth is a nerve.

It appears to be a 1970s bike (I would take a stab at a Yamaha LT3) and by that period shutter speeds of 1/500 or 1/1000 were readily available amongst better quality cameras. That would be plenty to get a clear shot of the spokes on what would be a relatively slow moving bike (I would assume <40km/h, likely noticeably less). I've got several 50s era cameras that have 1/500 top speeds, so even if the bike was new at the time of the photo it didn't require a new camera to take the shot.

I would not say having the inside foot off the peg and held forward in this situation is an indicator of the photo being fake, seeing as it's a common behaviour when riding dirt bikes.

The watermark is noticeably more readable in the Facebook image I linked though, and it does say photography (even there it is somewhat blurred though, so assuming it was actually clear in the original source that copy is a few recompressions along the chain).

The dates of the other sources however are what really convinces me it's not AI. After all, who was doing good quality photorealistic AI image generation in 2021?

The one I was thinking of is this one from a Facebook page, but looking around a bit more there's also this one from someone's instagram. The instagram one is mainly notable because it dates the image back further to at least 2021, making it even more unlikely to be AI generated.

The common attribution appears to be this Instagram account but google images didn't show me one from that account when looking for other version of the photo and I'm not about to make an instagram account in order to scroll through years of photos looking for the potential original.

Seems legit enough to me. The next rack of tomatoes would only be ~2m away after all given the gaps between rows aren't going to be massive. Pretty sure the sharpness issues are primarily from repeated JPEG recompression data loss - you can find a better quality version of the image by searching 'carmine spina tomatoes' which both looks less compressed in the far ground and dates from at least 2022 (so before mass popularity of AI generation).

I think a mud track with occasional bits of gravel is basically what the display is suggesting, it's just that the mud is dry.