It should get it wrong 0% of the time because it is a computer that should have predictable results about basic things like requiring a car to be present to be washed.

We have already thrown just about all the Internet and then some at them. It shows that LLMs can not think or reason. Which isn't surprising, they weren't meant to.

The second sentence is worthless garbage rambling that repeats the same point as the first sentence.

LLMs are not children. Children can have experiences, learn things, know things, and grow. Spicy autocomplete will never actually do any of these things.

Yeah I straight up misread the question, so I would have gotten it wrong.

Or at least they can't reason the way we do about our physical world.

No, they cannot reason, by any definition of the word. LLMs are statistics-based autocomplete tools. They don't understand what they generate, they're just really good at guessing how words should be strung together based on complicated statistics.

Yeah, I guess. You could make the argument the answer should just be "Drive."

It’s trained on Reddit. Sarcasm is it’s default

It could be, although one concise sentence with the reason for the answer is better. The first sentence is optimal.

Yeah, it was a joke. People appear to have had a hard time with catching that though, lol

It is not true so you may stop if you want

No, I completely agree. My personal view is that these systems are more intelligent than the haters give them credit for, but I think this simplistic "it's just autocomplete" take is a solid heuristic for most people - keeps them from losing sight of what they're actually dealing with.

I'd say LLMs are more intelligent than they have any right to be, but not nearly as intelligent as they can sometimes appear.

The comparison I keep coming back to: an LLM is like cruise control that's turned out to be a surprisingly decent driver too. Steering and following traffic rules was never the goal of its developers, yet here we are. There's nothing inherently wrong with letting it take the wheel for a bit, but it needs constant supervision - and people have to remember it's still just cruise control, not autopilot.

The second we forget that is when we end up in the ditch. You can't then climb out shaking your fist at the sky, yelling that the autopilot failed, when you never had autopilot to begin with.

Could end up in a pun chain too

and what is going to happen is that some engineer will band aid the issue and all the ai crazy people will shout “see! it’s learnding!”
and the ai snake oil sales man will use that as justification of all the waste and demand more from all systems

just like what they did with the full glass of wine test. and no ai fundamentally did not improve. the issue is fundamental with its design, not an issue of the data set

AI is getting pretty good

42 out of 53 models said to walk to the carwash.

I feel like we're the only ones that expect "all-knowing information sources" should be more writing seriously than these edgelord-level rizzy chatbots are, and yet, here they are, blatantly proving they are chatbots that should not be blindly trusted as authoritative sources of knowledge.

They also polled 10,000 people to compare against a human baseline:

Turns out GPT-5 (7/10) answered about as reliably as the average human (71.5%) in this test. Humans still outperform most AI models with this question, but to be fair I expected a far higher "drive" rate.

That 71.5% is still a higher success rate than 48 out of 53 models tested. Only the five 10/10 models and the two 8/10 models outperform the average human. Everything below GPT-5 performs worse than 10,000 people given two buttons and no time to think.

LLMs are a long long way from primetime

I just tried it on Braves AI

The obvious choice, said the motherfucker 😆

I think the “fancy auto complete” meme is a disingenuous thought stopper, so I speak against it when I see it.

I can respect that. I've criticized it plenty myself too. I think this is just me knowing my audience and tweaking my language so at least the important part of my message gets through. Too much nuance around here usually means I spend the rest of my day responding to accusations about views I don't even hold. Saying anything even mildly non-critical about AI is basically a third rail in these parts of the internet.

These systems do seem to have some kind of internal world model. I just have no clue how far that scales. Feels like it's been plateauing pretty hard over the past year or so.

I'd be really curious to try the raw versions of these models before all the safety restrictions get slapped on top for public release. I don't think anyone's secretly sitting on actual AGI, but I also don't buy that what we have access to is the absolute best versions in existence.

This here is the point most people fail to grasp. The AI was taught by people. And people are wrong a lot of the time. So the AI is more like us than what we think it should be. Right down to it getting the right answer for all the wrong reasons.
We should call it human AI. Lol.

My gods, I love those. We should link to some.

The same 29% that keeps fascists in power around the world.

I watched this in a YouTube Shorts format a week ago, where they ask a few models about walking or driving to the car wash.

They have some more funny ask AI shorts.

You're failing into the same trap. When the letters on the screen tell you something, it's not necessarily the truth. When there is "I'm reasoning" written in a chatbot window, it doesn't mean that there is a something that's reasoning.

By now it's kind of getting clear that fundamentally it's the best version of the thing that we get. This is a primetime.
For some time, there was a legit question of "if we give it enough data, will there be a qualitative jump", and as far as we can see right now, we're way past this jump. Predictive algorithm can form grammatically correct sentences that are related to the context. That's it, that's the jump.
Now a bunch of salespeople are trying to convince us that if there was one jump, there necessarily will be others, while there is no real indication of that.

I'm not talking about the quality of LLMs (they suck, in so many different ways…).

I'm criticizing the experiment setup, it is not really statistically sound. Doing 10 tests each with 52 different models is almost bound to have one model be correct 100% of the time (even if the true probability is closer to 50%), by pure chance. Doing 100 tests each might yield very different results with none of them answering correct 100% of the time. Or put another way, the p-values of the tests performed are pretty high, not <0.05, so the results don't really say what they purport to say.

I think the overall poor showing is pretty damning even if one or two models accidentally stumbled into being right 10/10 times.

The funny thing is, in order to get it to the dumber model, they have to run people's queries through a model that selects the appropriate model first. This is resulted in new headaches for AI fans

What is the wrong answer though? It is a stupid question. I would look at you sideways if you asked me this, because the obvious answer is "walk silly, the car is already at the car wash". Otherwise why would you ask it?

Which is telling because when asked to review the answer, the AI's that I have seen said, you asked me how you were going to get to the car wash. Assumption the car was already there.

Like I said the person above, there is no wrong answer. Its all about assumptions. It is a stupid trick question that no one would ask.

Those humans used AI to answer the question. /j

Where is the car?

This is the exact question a person would ask when they to have a gotcha answer. Nobody would ask this question, which makes it suspect to a straight forward answer.

Yeah seems like the training on human data makes it so most AIs will answer at least as unreliable as humans. 71% saying walk from the human side is crazy

And yet the best models outdid humans at this "car wash test." Humans got it right only 71.5% of the time.

I mean if they fix specific reasoning test answers (like the strawberry one) this doesn't actually make reasoning better tho. It just optimizes for benchmarks

I'm not doing it on behalf of anyone. Should we ignore the technology because we don't like the specific people who are developing it?

You should consider reading the article before "just sayin."

Gemini 3 pro said that this was a "great logic puzzle" and then said that if my goal is to wash the car, then I need to drive there.

It's so obvious I didn't even need to be British to understand you are being totally serious.

Yeah that's also something that you have to train for, i'm not super aware of the technicals but model routing is definitely important to the AI companies. I suspect that's part of why they can pretend that "inference is profitable" as they are already trying to squeeze it down as much as possible.

I've been feeding a bunch of documents I wrote into gemini last week to spit out some scripts for validation I couldn't be arsed to write. It's done a surprisingly comprehensive job and when wrong has been nudged right with just a little abuse..

I'm still all fuck this shit and can't wait for the pop, but for comparison openai was utterly brain dead given the same task. I think I actually made the model worse it was so useless.

Half the issue is they're calling 10 in a row "good enough" to treat it as solved in the first place.

A sample size of 10 is nothing.

Frankly would like to see some error bars on the "human polling". How many people rapiddata is polling are just hitting the top or bottom answer?

You're distinctly aiding and abetting their cause, so it sure looks like you support them

In fact, I prefer the use of local AIs and dislike how the field is being dominated by big companies like Google or OpenAI. Unfortunately personal preferences don't change reality.

I wonder if the routing is actually going to decrease the overall costs or increase them... Routing looks like it introduces new, unavoidable factors that would cause the costs to increase.