I do think it's more likely that it knew the answers to all of them, either because it was part of its training data set or because at some point some user told it the correct answer than that it figured those out by some sort of reasoning process.
Well, at least this can be tested. Is anybody here a good riddle master? Then please devise a good one, but do not write the answer here - or write it backwards, or whatever. Then Darat can present it to Co-Pilot, and we’ll see.
Well, it's probably a small percentage, but I think it must be more than zero, or else wouldn't we still be stuck in the Stone Age?
Of course it is greater than zero, but do we need to compare AI’s to the best among us. What about comparing to the likes of me who can’t solve a single riddle, and has hardly ever had an original thought?
www.forbes.com
That is something that is well known. Check everything that it produces. People have been in trouble for blindly accepting what AI has said.Interesting article discussing not just the accuracy of generative AI but the AIs’ confidence in their accuracy.
OpenAI Newly Released SimpleQA Helps Reveal That Generative AI Blatantly And Alarmingly Overstates What It Knows
OpenAI released SimpleQA, a new benchmark for generative AI. During the work, they uncovered a serious qualm about AI being supremely overconfident. Here's the scoop.
The thing is, no AI is needed for such a routine task. Just have an array of sensors that trip an automated arm (or whatever robot tool is needed) as the items to be packaged, assembled, etc. passes a certain point. It's been done for years now, no AI needed.
Not in a quiz setting.
When it it comes to it, I would be pretty confident that all these bots will be absolutely useless at solving novel problems that a properly trained human will be able to solve. They still are chatbots after all, just ones with access to huge (pirated) libraries.
And I am more than confident that most humans even with training and education would fail at solving "novel problems", my evidence is the 50 plus years I've been observing humans.
Rote recall of arbitrary data is something computers are especially good at. That's why we invented them and gave them work that monetizes rote recall of arbitrary data. It's no surprise that a computer with access to every joke ever written is able to perform rote recall of punchlines for an arbitrary list of setups.
neurosciencenews.com
I think it is more a matter of a practical lmitation of one specific class of AI. I think time and time again we have to unravel the investor/marketing bubble hype to get to the strand of reality. LLMs are great for marketing and making investors drool because they make great demonstrations and as a result unfortunately have become necessary for a company to get a tick from the "financial analysts". But their real world use is quite limited and are not going to create huge share price increases!
Something that raised the hair at the back of neck is that the big data crunchers, like OpenAI may use "synthetic" data to further train their models. With of course that synthetic word meaning computer generated text. Have they never put a microphone near to a speaker outputting the mike's input?
