Back in the days before dash cams I got let off with warnings a few times. Once in a while they actually are human beings, but that’s rare when they’re on a month end quota filling mission.

This is exactly the tactic the officer was employing here (for a sub $25 theft), not showing the accused the evidence so they don’t know what the police might or might not know.

At some point in the process, there is “discovery” where both sides share their evidence before trial to avoid going to trial for stupid stuff (like this.) But you usually have to engage thousands of dollars of legal services before discovery is available, again over a sub $25 theft allegation.

The officer sweating her for driving through his town on the day somebody porch pirated somebody else is really ridiculous.

That’s how they’re running it, and there are a whole lot of people who would prefer it to run that way in the future.

What should be happening is: when falsely accused and exonerated in court, you get a judgement against the LEA for treble damages for your costs to rebut their false claims.

False claims are going to happen, but if they’re costing the police thousands of dollars per instance, that should slow them down. I’m more than happy to pay increased taxes to put that deterrent on the agencies.

using your own fucking servers

And/or peer to peer mesh. Personally, I WANT a system that has peak performance AND multiple fallbacks to prevent blackout single point of failure situations.

The closest thing to “Smart TVs” in our home are Blu-Ray players, and they’ve never been network connected.

I like the ViewSonics we have, and we’ve had a series of NUCs over the years, but lately I’m finding that the N100/N150 fanless PCs like this are perfectly capable of HTPC duty: https://www.amazon.com/dp/B0CWV439YW

Sounds good to me.

I’d rather wear Fleather than eat feat.

Yeah… we have a 55" 4K tv, and from across the room you sort of have to squint to tell the difference between 4K and 1080p, up close sure, but I don’t watch screens that big from that close.

I like the idea of lab grown leather that’s tweaked for desirable properties, thickness, toughness, suppleness…

Instead of calling it chaos, call it losing their jobs - being forced to move hundreds of miles if they want to earn decent money again…

Can you see the difference without your glasses?

The real thing most people are trying to hold onto is stability, because chaos benefits the powerful. AI is just the latest agent of chaos, from their perspectives.

640K of RAM is all anybody will ever need.

1920x1080 is plenty, if the screen is under 50" and the viewer is more than 10’ away.

I used to have 20/10 vision, this 20/20 BS my cataract surgeon says I have now sucks.

If you’re sitting 3’ from the screen, sure. Even 8K is better, if your hardware can drive it.

Depends on your eyes quite a bit, too. If I’m sitting more than 15’ back from a 55" screen, 1080p is just fine. Put on my distance glasses and I might be able to tell the difference with 4K.

this issue is impossible to discuss without conflating it with general economics and wealth imbalance

It’s not conflating, the two issues are inextricably linked.

General economics and wealth imbalance can be addressed with or without the chaos of AI disrupting the job market. The problem is: chaos acts to drive wealth imbalance faster, so any change like AI in the jobs market is just shaking things up and letting more people fall through the cracks faster.

The first was never “AI” in a CS context

Mostly because CS didn’t start talking about AI until after popular perception had pushed calculators into the “dumb automatons” category.

Image classifiers came after CS drew the “magic” line for what qualifies as AI, so CS has piles of academic literature talking about artificially intelligent image classification, but public perception moves on.

The definition has been pretty consistent since at least Alan Turing, if not earlier.

I think Turing already had adding machines before he developed his “test.”

The current round of LLMs seem more than capable of passing the Turing test if they are configured to try to. In the 1980s, the Eliza chat program could pass the Turing test for three or four exchanges with most people. These past weeks, I have had extended technical conversations with LLMs and they exhibit sustained “average” knowledge of our topics of discussion. Not the brightest bulb on the tree, but they’re widely read and can pretty much keep up with the average bear on the internet in terms of repeating what others have written.

Meanwhile, there’s a virulent public perception backlash calling LLMs “dumb automatons.” Personally, I don’t care what the classification is. “AI” has been “5 years away from realization” my whole life, and I’ve worked with “near AI” tech all that time. The current round of tools have made an impressive leap in usefulness. Bob Cratchit would have said the same about an adding machine if Scrooge had given him one.

The problem with AI in a “popular context” is that it has been a forever moving target. Old mechanical adding machines were better at correctly summing columns of numbers than humans, at the time they were considered a limited sort of artificial intelligence. All along the spectrum it continues. 5 years ago, image classifiers that can sit and watch video feeds 24-7, accurately identifying things that happen in the feed with better than human accuracy (accounting for human lack of attention, coffee breaks, distracting phone calls, etc.) those were amazing feats of AI - at the time, and now they’re “just image classifiers” much as Alpha-Zero “just plays games.”

A year ago AI answers were only successfully compiling for me about 60% of the time. Now they’re up over 80%, and I’m no longer in the loop when they screw up, they get it right on the first try 80% of the time, then 96% of the time by the 2nd try, 99% by the third try, 99.84% of the time by the 4th try, and the beauty is: they retry for themselves until they get something that actually compiles.

Now we can talk about successful implementation of larger feature sets…

I had similar experiences a few months back, like 6-8. Since Anthropic Sonnet 4.0 things have changed significantly. 4.5 is even a bit better. Competing models have been similarly improving.