Because the standard for Democrats is perfectionism, but the standard for Republicans is “That’s just Trump being Trump.”

In other words, they didn’t think it through, they got suckered by propaganda.

Some people are going to die-- mostly women. More people are going to have their lives turned upside-down, especially immigrants and ethnic and sexual minorities. Many immigrants, even legal ones, are going to be expelled. Corporations are going to run wild as regulation is abandoned. People are going to be bankrupted by predatory healthcare firms at a much higher rate than now. Every form of corporate pollution, adulteration, cheating and chicanery will be tolerated. The judiciary will be further corrupted. The US will not only withdraw from NATO, but will try to shut it down. Ukraine will be handed to Putin on a platter. Taiwan, the Baltics, Moldova and Poland will be left to fend for themselves. The ethnic cleansing in Gaza will transition even further to a full-scale genocide. Every aspect of government will be handed to corrupt, incompetent fanatics: kakistocracy all the way down. The impartiality of the civil service will be destroyed and the 19th-century spoils system reinstated. Social Security will be privatized and gutted. Obamacare will be eliminated. Congress will hold show trials of Trump’s perceived enemies. Terrorist acts and sabotage of critical infrastructure will massively increase, and the clampdowns that follow will be used to further degrade what few rights we still have.

But at least you won’t have Kamala’s pantsuit to complain about.

They’ll kill off the filibuster as soon as it gets in their way. They don’t care about tradition or institutional continuity. And anyway, the Democrats seldom resort to the filibuster, they just bend over.

Trump and Musk will have a power struggle within a few months. Trump hates the idea that someone’s richer than him, and will want to humiliate him. Trump will dump RFK Jr too, as soon as Jr gets more publicity than Trump. What will be semi-permanent are the careerist shitstains like the Speaker, the God-botherers with their crusade against women, and the anti-immigrant scum.

And royals, like race horses, are not bred for intelligence.

Yeah, it only matters for old-school animal breeders and royal genealogists. It’s a pre-scientific notion.

This is a privacy intrusion that should be banned nationally.

And some subreddits have fascist mods who arbitrarily ban anyone who’s not a alt-right or worse.

Interoperability is a big job, but the extent to which it matters varies widely according to the use case. There are layers of standards atop other standards, some new, some near deprecation. There are some extremely large and complex datasets that need a shit-ton of metadata to decipher or even extract. Some more modern dataset standards have that metadata baked into the file, but even then there are corner cases. And the standards for zero-trust security enclaves, discoverability, non-repudiation, attribution, multidimensional queries, notification and alerting, pub/sub are all relatively new, so we occasionally encounter operational situations that the standards authors didn’t anticipate.

TripAdvisor has better content. Too many Google reviews give a business 1 star because the review author was too stupid to check working hours, or has some incredibly rare digestive condition that they didn’t bother to communicate to the eatery before ordering. Or they expect their Basque waiter to speak fluent Latvian, or to accommodate a walk-in party of 20.

Isn’t yelp a pretty easily replaceable thing?

Yelp is at this stage a completely worthless thing. The only thing they were originally was an aggregator of semi-literate reviews, and a shakedown racket against businesses that pissed off some Karen

Yeah, just like the thousands or millions of failed IT projects. AI is just a new weapon you can use to shoot yourself in the foot.

is all but guaranteed to be possible

It’s more correct to say it “is not provably impossible.”

Someone, somewhere along the line, almost certainly coded rate(2025) = 2*rate(2024). And someone approved that going into production.

If they aren’t liable for what their product does, who is?

The users who claim it’s fit for the purpose they are using it for. Now if the manufacturers themselves are making dodgy claims, that should stick to them too.

If a self-driving car kills someone, the programming of the car is at least partially to blame

No, it is not. It is the use to which the system has been put that is the point at which blame can be assigned. That is what should be verified and validated. That’s where some person is signing on the dotted line that the system is fit for use for that particular purpose.

I can write a simplistic algorithm to guide a toy drone autonomously. So let’s say I GPL it. If an airplane manufacturer then drops that code into an airliner, and fail to test it correctly in scenarios resembling real-life use of that plane, they’re the ones who fucked up, not me.

No liability should apply while coding. When that code is deployed for use, there should be liability if it is unfit for its intended use. If your AI falsely denies my insurance claim, your ass should be on the line.

Yeah, all these systems do is worsen the already bad signal/noise ratio in online discourse.

Unless there is a huge disclaimer before every interaction saying “THIS SYSTEM OUTPUTS BOLLOCKS!” then it’s not good enough. And any commercial enterprise that represents any AI-generated customer interaction as factual or correct should be held legally accountable for making that claim.

There are probably already cases where AI is being used for life-and-limb decisions, probably with a do-nothing human rubber stamp in the loop to give plausible deniability. People will be maimed and killed by these decisions.

They are a product of lack of control over the stadistical output.

OK, so describe how you control that output so that hallucinations don’t occur. Does the anti-hallucination training set exceed the size of the original LLM’s training set? How is it validated? If it’s validated by human feedback, then how much of that validation feedback is required, and how do you know that the feedback is not being used to subvert the model rather than to train it?

It’s a problem, but not a bug any more than the result of a car hitting a tree at high speed is a bug.

You’re attempting to redefine “bug.”

Software bugs are faults, flaws, or errors in computer software that result in unexpected or unanticipated outcomes. They may appear in various ways, including undesired behavior, system crashes or freezes, or erroneous and insufficient output.

From a software testing point of view, a correctly coded realization of an erroneous algorithm is a defect (a bug). It fails validation (a test for fitness for use) rather than verification (a test that the code correctly implements the erroneous algorithm).

This kind of issue arises not only with LLMs, but with any software that includes some kind of model within it. The provably correct realization of a crap model is still crap.