Two AI models pass test to determine if a machine can think like a human

OpenAI's GPT-4.5 and Meta's Llama-3.1 models have passed the Turing Test, a benchmark proposed by Alan Turing in the 1950s to assess whether machines can exhibit intelligent behaviour indistinguishable from humans that has always been held up as a sort of tipping point on the maturity and sophistication of Artificial Intelligence (AI).

- Vishal Mathur

NEW DELHI:

Researchers Cameron R. Jones and Benjamin K. Bergen from the University of California San Diego, found that GPT-4.5 performed so convincingly that judges identified it as human 73% of the time—significantly more often than they correctly identified actual human participants. Meta's Llama-3.1-405B achieved a 56% success rate, essentially matching human performance (around 50%), while baseline models ELIZA and GPT-40 were correctly identified as non-human with only 23% and 21% win rates respectively.

"When prompted to adopt a human-like persona, GPT-4.5 was judged to be the human 73% of the time: significantly more often than interrogators selected the real human participant," Jones and Bergen stated in their study, which awaits peer review.

The experiment employed a three-party design where participants engaged in simultaneous five-minute conversations with both a human and an AI system before determining which was which. This methodology, tested across two independent populations—undergraduate students and prolific workers—provides the first robust evidence that any system passes the original three-party Turing test.