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Inverted Turing Test: Is GPT-4 More Human-like than Humans?

The Turing Test proposed by Alan Turing in 1950 aims to evaluate machine intelligence by making it difficult for humans to distinguish between machines and humans through textual communication. Recently, scientists at the University of California, San Diego, explored the ability of AI and humans to differentiate each other when reading conversation logs rather than engaging in direct communication. They designed the Inverted Turing Test and the Shifted Turing Test. The results showed that the accuracy of AI judges was lower than that of humans who participated in direct communication, and in some cases, the AI even mistakenly identified another AI as a human. This indicates that in the absence of direct communication...

14.7k 4 hours ago
Inverted Turing Test: Is GPT-4 More Human-like than Humans?

Models

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Pangu-NLP-N2-32K-5.0.1.1

Huawei

Pangu-NLP-N2-32K-5.0.1.1

-

Input tokens/M

-

Output tokens/M

32

Context Length

QianfanHuijin-8B

Baidu

QianfanHuijin-8B

-

Input tokens/M

-

Output tokens/M

32

Context Length

Qianfan-Llama-VL-8B

Baidu

Qianfan-Llama-VL-8B

-

Input tokens/M

-

Output tokens/M

32

Context Length

Pangu-NLP-N1-128K-3.2.36

Huawei

Pangu-NLP-N1-128K-3.2.36

-

Input tokens/M

-

Output tokens/M

128

Context Length

Qwen_v2.5_3b_Instruct

Alibaba

Qwen_v2.5_3b_Instruct

$1

Input tokens/M

-

Output tokens/M

32

Context Length

ERNIE-4.5-21B-A3B-Paddle

Baidu

ERNIE-4.5-21B-A3B-Paddle

-

Input tokens/M

-

Output tokens/M

-

Context Length

ERNIE-4.5-0.3B

Baidu

ERNIE-4.5-0.3B

$0.1

Input tokens/M

$0.4

Output tokens/M

128

Context Length

Yi-Large-Turbo

01-ai

Yi-Large-Turbo

-

Input tokens/M

-

Output tokens/M

16

Context Length

ERNIE-3.0

Baidu

ERNIE-3.0

-

Input tokens/M

-

Output tokens/M

4

Context Length

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