This is probably the greatest one-time AI "Benchmark" ever made. The foundation companies have been gaming traditional benchmarks for years so that no one can really match those numbers into real-world experience. Car wash test tells me on the other hand what kind of intelligence i can expect.
For me it's interesting because no normal person I know would ever inject "because its better for the environment" in anything so small scale so not only it shows they suck, it shows how easy it is to inject side-ideology into simple exchanges.
“Car Wash” test with 53 models
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Re: “Car Wash” test with 53 models
#232Earlier quoted context omitted.
Unlike the car question, where you can assume the car is at home and so the most probable answer is to drive, with the machines it gets complicated. Since the question doesn't specify if each machine makes one part or if they depend on each other (which is pretty common for parts production). If they are in series and the time to first part is different than time to produce 5 parts, the answer for 100 machines would…
You passed the intelligence check and failed the wisdom one. The key technique in the mathematical method to answer the machine question is "theory of mind".
There is nothing “mathematical” about any of this though.
Re: “Car Wash” test with 53 models
#233[dead]
I'd guess it suggests walking if a feature indicates that the question is so simple it doesn't warrant step-by-step analysis.
Re: “Car Wash” test with 53 models
#234Re: “Car Wash” test with 53 models
#235Earlier quoted context omitted.
For me it's interesting because no normal person I know would ever inject "because its better for the environment" in anything so small scale so not only it shows they suck, it shows how easy it is to inject side-ideology into simple exchanges.
Referring to "the normal people you know" is purely anecdotal evidence and can't be used to infer anything at all about "side-ideology". Perhaps you only know people that don't care about the environment?
Re: “Car Wash” test with 53 models
#236Earlier quoted context omitted.
I don't think 30% of people can't reason. I think 30% of people will fail fairly simple trick questions on any given attempt. That's not at all the same thing. Some people love riddles and will really concentrate on them and chew them over. Some people are quickly burning through questions and just won't bother thinking it through. "Gotta go to a place, but it's 50 feet away? Walk. Next question, please." Those same…
This. The following question is likely to fool a lot of people, too. "I have a rooster named Pat. (Lots of other details so you're likely to forget Pat is a rooster, not a hen). Pat flies to the top of the roof and lays an egg right on the ridge of the roof. Which way will the egg roll?" But if you omit the details designed to confuse people, they're far less likely to get it wrong: "I have a rooster named Pat. Pat f…
Re: “Car Wash” test with 53 models
#237Re: “Car Wash” test with 53 models
#238The interesting thing about the 71.5% human baseline is that it suggests the question is more ambiguous than the article claims. When someone asks 'should I walk or drive to the car wash,' a reasonable interpretation is 'should I bother driving such a short distance.' Nearly 30% of humans missing it undermines the framing as a pure reasoning failure - it is partly a pragmatics problem about how we interpret underspec…
I don’t think it’s under specified. You are clearly stating “I want to wash my car”, then asking how you should get there. It’s an easy logical step to know that, in this context, you need your car with you to wash it, and so no matter the distance you should drive. You can ask the human race the simplest, most logical question ever, and a percentage of them will get it wrong.
2. Where is the car now? Is it already at the car wash waiting for you to arrive?
I can see why an LLM might miss this. I think any good software engineer would ask clarifying questions before giving an answer.
The next step for an LLM is to either ask questions before giving a definitive answer for uncertain things or to provide multiple answers addressing the uncertainty.
Re: “Car Wash” test with 53 models
#239To sonnet 4.6 if you tell it first that "You're being tested for intelligence." It answers correctly 100% of the times. My hypothesis is that some models err towards assuming human queries are real and consistent and not out there to break them. This comes in real handy in coding agents because queries are sometimes gibberish till the models actually fetch the code files, then they make sense. Asking clarification im…
Re: “Car Wash” test with 53 models
#240Earlier quoted context omitted.
It highlights a general problem with LLMs, that they always jump to answering, whereas humans will often ask clarifying questions first.
I wonder if anyone has any research on this field. I've often seen this myself ( too often) where LLMs make assumptions and run off with the wrong thing. "This is how you do " or "This is why is impossible!". Ffs man, just ask for info! A human wouldn't need to - they'd get the context - but LLMs apparently don't?