This may be a test, but, it also is proof. AI is not capable of thinking and allowing it's programming is too dangerous to continue. The only entity that thinks and conducts the scientific method are human beings.
Computers don't need oxygen!
25 July 2023
By Celeste Biever
The world’s best artificial intelligence (AI) systems (click here) can pass tough exams, write convincingly human essays and chat so fluently that many find their output indistinguishable from people’s. What can’t they do? Solve simple visual logic puzzles.
In a test consisting of a series of brightly coloured blocks arranged on a screen, most people can spot the connecting patterns. But GPT-4, the most advanced version of the AI system behind the chatbot ChatGPT and the search engine Bing, gets barely one-third of the puzzles right in one category of patterns and as little as 3% correct in another, according to a report by researchers this May1.
The team behind the logic puzzles aims to provide a better benchmark for testing the capabilities of AI systems — and to help address a conundrum about large language models (LLMs) such as GPT-4. Tested in one way, they breeze through what once were considered landmark feats of machine intelligence. Tested another way, they seem less impressive, exhibiting glaring blind spots and an inability to reason about abstract concepts.
“People in the field of AI are struggling with how to assess these systems,” says Melanie Mitchell, a computer scientist at the Santa Fe Institute in New Mexico whose team created the logic puzzles (see ‘An abstract-thinking test that defeats machines’)....
The world’s best artificial intelligence (AI) systems (click here) can pass tough exams, write convincingly human essays and chat so fluently that many find their output indistinguishable from people’s. What can’t they do? Solve simple visual logic puzzles.
In a test consisting of a series of brightly coloured blocks arranged on a screen, most people can spot the connecting patterns. But GPT-4, the most advanced version of the AI system behind the chatbot ChatGPT and the search engine Bing, gets barely one-third of the puzzles right in one category of patterns and as little as 3% correct in another, according to a report by researchers this May1.
The team behind the logic puzzles aims to provide a better benchmark for testing the capabilities of AI systems — and to help address a conundrum about large language models (LLMs) such as GPT-4. Tested in one way, they breeze through what once were considered landmark feats of machine intelligence. Tested another way, they seem less impressive, exhibiting glaring blind spots and an inability to reason about abstract concepts.
“People in the field of AI are struggling with how to assess these systems,” says Melanie Mitchell, a computer scientist at the Santa Fe Institute in New Mexico whose team created the logic puzzles (see ‘An abstract-thinking test that defeats machines’)....
