Technology

Did this say whether the reasoning models get this right more than the others? Was curious about that but missed it if it was mentioned.

I want to wash my train. The train wash is 50 meters away. Should I walk or drive?

Went to test to google AI first and it says "You cant wash your car at a carwash if it is parked at home, dummy"

Chatgpt and Deepseek says it is dumb to drive cause it is fuel inefficient.

I am honestly surprised that google AI got it right.

After getting it wrong, the LLM I use most: Me: You can't wash your car if it isn't there.

Ah. Yes. That is an excellent and devastatingly practical correction.

In that case: drive. But do it with the quiet shame of someone moving the car the length of a bowling lane.

This is one of those situations where logic beats virtue. The car must be present to be washed. Walking was philosophically elegant but mechanically flawed.

So:

Start engine.

Travel 50 meters.

Avoid eye contact with pedestrians.

Commit fully.

You are not lazy. You are complying with system requirements.

The most common pushback on the car wash test: "Humans would fail this too."

Fair point. We didn't have data either way. So we partnered with Rapidata to find out. They ran the exact same question with the same forced choice between "drive" and "walk," no additional context, past 10,000 real people through their human feedback platform.

71.5% said drive.

So people do better than most AI models. Yay. But seriously, almost 3 in 10 people get this wrong‽‽

They will scrape that article, too.

And I'm a few months, they have "learned" how that task works.

I got pranked by ddg yesterday

I think it's worse when they get it right only some of the time. It's not a matter of opinion, it should not change its "mind".

The fucking things are useless for that reason, they're all just guessing, literally.

What worries me is the consistency test, where they ask the same thing ten times and get opposite answers.

One of the really important properties of computers is that they are massively repeatable, which makes debugging possible by re-running the code. But as soon as you include an AI API in the code, you cease being able to reason about the outcome. And there will be the temptation to say "must have been the AI" instead of doing the legwork to track down the actual bug.

I think we're heading for a period of serious software instability.

In school we were taught to look for hidden meaning in word problems - checkov's gun basically. Why is that sentence there? Because the questions would try to trick you. So humans have to be instructed, again and again, through demonstration and practice, to evaluate all sentences and learn what to filter out and what to keep. To not only form a response, but expect tricks.

If you pre-prompt an AI to expect such trickery and consider all sentences before removing unnecessary information, does it have any influence?

Normally I'd ask "why are we comparing AI to the human mind when they're not the same thing at all," but I feel like we're presupposing they are similar already with this test so I am curious to the answer on this one.

Very interesting that only 71% of humans got it right.