I burned down a forest to confirm
Don’t ask it to name an NFL team that doesn’t end with ‘s’
DeepSeek eventually gets it, but it’s DeepThink takes a good ten minutes of racing ‘thoughts’ and loops to figure it out.
I burned down a forest to confirm
Don’t ask it to name an NFL team that doesn’t end with ‘s’
DeepSeek eventually gets it, but it’s DeepThink takes a good ten minutes of racing ‘thoughts’ and loops to figure it out.
They’re not talking about how great it is at counting letters. This is just using a technology for something it wasn’t meant for and then going on about how it’s useless. If you want to disprove the hype, using evidence that hadn’t been known for the entire production run of commercial LLMs would probably be better.
If it cannot be used for something it wasn’t intended, then it isn’t intelligence. And since language processing is both what it is made from and intended for, this shows that there is no emergent intelligent understanding of its actual speciality function, it’s just a highly refined autocomplete with some bolted-on extras.
Not that more research couldn’t necessarily find that mysterious theoretical threshold, but the focus on public-facing implementations and mass application is inefficient to the point of worthlessness for legitimate improvement. Good for killing people and disrupting things though.
no shit. death to ad men. but LLMs aren’t for most of these stunts. that’s part of the problem but it’s like saying my bike is bad at climbing trees. at least the bike isn’t being advertised for arbory
It sucks at other things too. Counting errors are just really easy to objectively verify.
People like Altman claim they can use LLM for creating formal proofs, advancing our knowledge of physics and shit. Fat chance when it can’t even compete with a toddler at counting.