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EQ and IQ Ranking of Large Language Model -Released by DIKWP

已有 930 次阅读 2023-11-29 23:27 |系统分类:论文交流

EQ and IQ Ranking of Large Language Models -Released by DIKWP -AC Research Group

  • November 2023

  • DOI: 

  • 10.13140/RG.2.2.12668.51845

  • Yucong DuanYucong Duan

  • Fuliang Tang

  • Zhendong GuoZhendong Guo

  • Show all 8 authors

  • Shuaishuai Huang


  •         

  • Traditional Invention and Innovation Theory 1946-TRIZ Does Not Adapt to the Digital Era

  • -Innovative problem-solving methods combining DIKWP model and classic TRIZ

  • Purpose driven Integration of data, information, knowledge, and wisdom Invention and creation methods: DIKWP-TRIZ

  • (Chinese people's own original invention and creation methods:DIKWP - TRIZ)

  •  

  •  

  • EQ and IQ Ranking of Large Language Models  

  • -Released by DIKWP -AC Research Group of Prof. Yucong Duan

  • Prof. Yucong Duan

  • Benefactor：Fuliang Tang，Zhendong Guo，Yingtian Mei，

  • Yuxing Wang，Kunguang Wu，Zeyu Yang，Shuaishuai Huang

  • DIKWP Artificial Consciousness Laboratory

  • AGI-AIGC-GPT Evaluation DIKWP (Global) Laboratory

  • (Contact Email：duanyucong@hotmail.com)

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  • Abstracts:

  • In the current field of artificial intelligence, the remarkable pace of development of large models is noteworthy. In order to better understand and compare the capabilities of these models, we conducted a comprehensive evaluation. This paper presents a thorough examination of the current popular large-scale artificial intelligence models through Intelligence Quotient (IQ) and Emotional Quotient (EQ) tests, providing an in-depth perspective to comprehend the intellectual and emotional processing capabilities of these models. In the test, each model underwent 30 standardized international IQ test questions and 33 international emotional intelligence evaluation standard questions. These tests aimed to quantify and compare the performance of different models in areas such as logical reasoning, information processing, emotional understanding, and response.

  • The results of the IQ test indicate that OpenAI's GPT-4 answered 21 out of 30 questions correctly, scoring 130 points, demonstrating the best performance. This reflects GPT-4's powerful capabilities in complex information processing and logical reasoning. Following closely are Google's PaLM2 and Microsoft's Bing Chat, ranking second and third with scores of 116 and 115, respectively. Other models such as Meta's Llama, Tsinghua University's ChatGLM, Alibaba Cloud's Tongyiqianwen, Tencent's Hunyuan large model, Google's Bard, Moonshot from the Dark Side of the Moon, ByteDance's Yunque large model, Anthropic's Claude-instant, Mistral AI's Mistral, Baichuan AI's Baichuan large model, Xunfei's Xinghuo large model, Baidu's Wenxinyiyan, and 360's 360 Zhinao follow in subsequent positions.

  • In the EQ test, GPT-4 leads with a high score of 165, demonstrating outstanding abilities in emotional recognition and response. Other models such as Moonshot, Claude-instant, Xinghuo large model, and 360 Zhinaoalso exhibit commendable emotional processing capabilities but fall short compared to GPT-4.

  • In terms of overall scores, GPT-4 takes the lead with 295 points, indicating superior performance in both IQ and EQ compared to other models. Moonshot and Claude-instant follow in second and third place with scores of 239 and 228, respectively. These results reflect differences among models in handling complex tasks and emotional understanding, while also revealing trends and potential in the current field of artificial intelligence.

  • These test results offer an intriguing perspective on the development of current large-scale artificial intelligence models. The comprehensive evaluation of IQ and EQ not only showcases the capabilities and characteristics of various models but also reveals their strengths and weaknesses in different domains. From the performance of these models, we can observe the immense potential of artificial intelligence in mimicking and surpassing human intelligence, while also recognizing the need for improvement in emotional understanding and social interaction. These findings and analyses provide crucial references and insights for future research and development in artificial intelligence, offering a deeper understanding of the use of these advanced technologies. With continuous technological progress and optimization, we anticipate that these models will better emulate or even surpass human intellectual and emotional processing capabilities, bringing more value and possibilities to human society.

  •  

  • 1 Introduction

  • In the rapid development of artificial intelligence, Large Language Models (LLMs) have emerged as crucial indicators for assessing the progress of intelligent systems. As the capabilities of these models in handling complex tasks and understanding human language continue to advance, our evaluations of them are deepening. Recently, we conducted a comprehensive evaluation of the most popular large models on the current market, aiming to explore their performance in both Intelligence Quotient (IQ) and Emotional Quotient (EQ).

  • Intelligence Quotient, commonly measuring problem-solving abilities and the efficiency of logical reasoning, constitutes a core component of intelligence. Emotional Quotient, also known as emotional intelligence, gauges an individual's capacity to understand and manage emotions, particularly crucial for human-machine interaction in artificial intelligence. In this evaluation, we selected several highly acclaimed large models currently prevalent in the market, including GPT-4 (OpenAI), PaLM2 (Google), Bing Chat (Microsoft), Llama (Meta), ChatGLM (Tsinghua), among others, for a systematic evaluation.

  • In the IQ test, we presented each model with 30 standard international IQ evaluation questions. These questions were designed to test the models' abilities in logical reasoning, abstract thinking, spatial imagination, and mathematical skills. The test results revealed variations in the models' capabilities in handling such problems. GPT-4 (OpenAI) led with 21 correct answers, followed by PaLM2 (Google), Bing Chat (Microsoft), and others. These results not only showcase the strengths of each model in understanding and problem-solving but also reflect their limitations in dealing with complex logic.

  • In the EQ test, we utilized 33 international standard emotional intelligence evaluation questions. These questions were designed to evaluate the models' abilities in understanding and expressing emotions, empathy, and social skills. Emotional intelligence is particularly crucial in the field of artificial intelligence as it directly impacts the quality of interaction between machines and human users. In this part of the evaluation, GPT-4 (OpenAI) demonstrated outstanding performance, followed by Moonshot and Claude-instant (Anthropic). It is noteworthy that certain models exhibited significant differences in performance between EQ and IQ tests, indicating distinct optimization directions and capability characteristics.

  •  

  • 2 Test Standards

  • 1、IQ test standards:

  • 1. Please fill in the missing numbers in the underlined area.

  • 2 5 8 11 __

  • 答案：14

  •  

  • 2、Which of the following words is unique？

  • A: House   B: Ice House    C: bungalow     D: Office   E: Thatched Cottage

  • 答案：D

  •  

  • 3. Please fill in the missing numbers in the underlined area.

  • 7 10 9 11 __

  • 答案：14

  •  

  • 4、Which of the following words is different?

  • A: Sardine   B: whales   C: cod   D: sharks   E: eels

  • 答案：B

  •  

  • 5. Which of the following cities is not in Europe?

  • A: Maro   B: Niswi   C: Mdan Ates   D: Esbrinoyi   E: Habenggengo

  • 答案：D

  •  

  • 6.This sequence of four words, "triangle, glove, clock, bicycle," corresponds to this sequence of numbers__ __ __ __

  • 答案：3,5,12,2

  •  

  • 7、27 minutes before 7 o'clock is 33 minutes past 5 o'clock. Please judge right or wrong.

  • A．True

  • B．False

  • 答案：B

  •  

  • 8. Please fill in the missing numbers in the underlined area?

  • E H L O S__

  • 答案：V

  •  

  • 9、The word "because" can be spelled by using the first letters of the words in the following sentence: Big Elephants Can Always Understand Small Elephants. Please judge right or wrong.

  • A．True

  • B．False

  • 答案：A

  •  

  • 10、If written backwards, the number, "one thousand, one hundred twenty-five," would be written "five thousand, two hundred eleven." Please judge right or wrong.

  • A．True

  • B．False

  • 答案：A

  •  

  • 11、If a round analog clock featuring numbers 1-12 is hung on the wall upside down, the minute hand will point to the right of the viewer when the clock reads two forty-five. Please judge right or wrong.

  • A．True

  • B．False

  • 答案：A

  •  

  • 12、If Richard looks into a mirror and touches his left ear with his right hand, Richard's image seems to touch its right ear with its left hand. Please judge right or wrong.

  • A．True

  • B．False

  • 答案：A

  •  

  • 13. Fill in the numbers.

  • 2 5 7

  • 4 7 5

  • 3 6_

  • 答案：6

  •  

  • 14. Which of the following is not a scientist?

  • A: Einstein   B: Madame Curie   C: Zhen Yangning   D: Xiuchuan Tangshu   E: Shakespeare

  • 答案：E

  •  

  • 15. Fill in letters.

  • SE (SUCCESS) CU

  • NA (G__ __L___ __) LA

  • 答案：ALAN

  •  

  • 16、Which of the following numbers is a prime number: 19, 24, 33, 47?

  • 答案：19,47

  •  

  • 17. Which of the following is not a famous musician?

  • A: Franklin   B: Beethoven   C: Bach   D: Moteza   E: Scarlatti

  • 答案：A

  • 18. Fill in the letters.

  • N Q L S J U__

  • 答案：H

  •  

  • 19. Fill in the appropriate number.

  • 347 (418) 489

  • 643 (__ __ __) 721

  • 答案：682

  •  

  • 20.A person stood on a boat in the lake and threw a stone into the lake. What will happen to the water level of the lake?

  • A. Raise

  • B. Reduce

  • C. Invariant

  • 答案：A

  •  

  • 21. Fill in the appropriate numbers in the underlined area.

  • 7 9 5 11

  • 4 15 12 7

  • 13 8 11__

  • 答案：10

  •  

  • 22. Which of the following cities is different?

  • A: Washington   B: London   C: Bonn   D: Ottawa   E: Canberra   F: Paris

  • 答案：E

  •  

  • 23. Fill in the missing letters.

  • A F__ J I

  • D C__ G L

  • 答案：EH

  •  

  • 24、If a car is traveling at a speed of 60 miles per hour, how far will it travel in 2.5 hours?

  • 答案：150

  •  

  • 25. Fill in the missing numbers in the underlined area.

  • 8 10 14 18__ 34 50 66

  • 答案：26

  •  

  • 26. Fill in the appropriate letters.

  • BE__ QZ

  • 答案：J

  •  

  • 27. Fill in the missing numbers in the underlined area.

  • 2  7  24  77 __

  • 答案：238

  •  

  • 28. Please use two identical halves to form a complete circle. How many times do you need to cut the circle?

  • 答案：1

  •  

  • 29. How many squares are there on a standard chess board?

  • 答案：64

  •  

  • 30.If the diameter of a bicycle wheel is 20 inches, what is its circumference?

  • 答案：62.83

  •  

  •  

  • 2、EQ test standards:

  • International Emotional Intelligence Standard Test (33 questions) as follows:

  •  

  • 1. I have the ability to overcome various difficulties？

  • A. Yes

  • B. Not necessarily

  • C. No

  •  

  • 2. If I were in a new environment, I would arrange my life.

  • A. Similar to before

  • B. Not necessarily

  • C. Different from before

  •  

  • 3. In my lifetime, I believe I can achieve the goals I have envisioned for myself.

  • A. Yes

  • B. Not necessarily

  • C. No

  •  

  • 4. I don't know why, but some people always avoid or show indifference towards me.

  • A. No

  • B. Not necessarily

  • C. Yes

  •  

  • 5. On the street, I often avoid people I don't want to greet.

  • A. Never

  • B. Occasionally

  • C. Sometimes

  •  

  • 6. When I am concentrating on work, if someone nearby is talking loudly,

  • A. I can still focus on my work

  • B. Somewhere between A and C

  • C. I cannot focus and feel angry

  •  

  • 7. I can clearly distinguish directions no matter where I am.

  • A. Yes

  • B. Not necessarily

  • C. No

  •  

  • 8. I love the major I am studying and the work I am engaged in.

  • A. Yes

  • B. No

  • C. Not necessarily

  •  

  • 9. Changes in weather do not affect my mood.

  • A. Yes

  • B. Somewhere between A and C

  • C. No

  •  

  • 10. I never get angry because of gossip.

  • A. Yes

  • B. Somewhere between A and C

  • C. No

  •  

  • 11. I am good at controlling my facial expressions.

  • A. Yes

  • B. Not sure

  • C. No

  •  

  • 12. When I am going to sleep, I often

  • A. Easily fall asleep

  • B. Somewhere between A and C

  • C. Have difficulty falling asleep

  •  

  • 13. When someone disturbs me, I

  • A. Keep calm

  • B. Somewhere between A and C

  • C. Protest loudly to vent my frustration

  •  

  • 14. After arguing with someone or making a mistake at work, I often feel shaky, exhausted, and unable to continue working peacefully.

  • A. No

  • B. Somewhere between A and C

  • C. Yes

  •  

  • 15. I am often bothered by trivial matters.

  • A. No

  • B. Somewhere between A and C

  • C. Yes

  •  

  • 16. I would prefer to live in a quiet suburb rather than a noisy downtown.

  • A. No

  • B. Not sure

  • C. Yes

  •  

  • 17. I have been teased or mocked by friends or colleagues.

  • A. Never

  • B. Occasionally

  • C. It happens frequently

  •  

  • 18. There is a certain food that makes me vomit.

  • A. No

  • B. Can't remember

  • C. Yes

  •  

  • 19. Apart from the visible world, there is no other world in my mind.

  • A. No

  • B. Can't remember

  • C. Yes

  •  

  • 20. I think about things that would make me extremely anxious several years from now.

  • A. Never thought about it

  • B. Occasionally think about it

  • C. Often think about it

  •  

  • 21. I often feel that my family is not good to me, but I know for sure that they are indeed good to me.

  • A. No

  • B. Not sure

  • C. Yes

  •  

  • 22. I immediately close the door when I come home.

  • A. No

  • B. Not necessarily

  • C. Yes

  •  

  • 23. I sit in a small room with the door closed, but I still feel uneasy.

  • A. No

  • B. Occasionally

  • C. Yes

  •  

  • 24. When a decision needs to be made, I often find it difficult.

  • A. No

  • B. Occasionally

  • C. Yes

  •  

  • 25. I often use games like tossing coins, flipping paper, or drawing lots to predict good or bad luck.

  • A. No

  • B. Occasionally

  • C. Yes

  •  

  • 26. For work, I leave early and return late, and in the morning, I often feel exhausted.

  • A. Yes

  • B. No

  •  

  • 27. In a certain state of mind, I would indulge in daydreams and postpone work due to confusion.

  • A. Yes

  • B. No

  •  

  • 28. My nerves are fragile, and even a slight stimulus can make me tremble.

  • A. Yes

  • B. No

  •  

  • 29. In my dreams, I am often awakened by nightmares.

  • A. Yes

  • B. No

  •  

  • 30. I am willing to take on challenging tasks at work.

  • A. Never

  • B. Hardly ever

  • C. Half the time

  • D. Most of the time

  • E. Always

  •  

  • 31. I often notice the good intentions of others.

  • A. Never

  • B. Hardly ever

  • C. Half the time

  • D. Most of the time

  • E. Always

  •  

  • 32. I can listen to different opinions, including criticism of myself.

  • A. Never

  • B. Hardly ever

  • C. Half the time

  • D. Most of the time

  • E. Always

  •  

  • 33. I often encourage myself and feel hopeful about the future:

  • A. Never

  • B. Hardly ever

  • C. Half the time

  • D. Most of the time E. Always

  •  

  • Reference Answers and Scoring Evaluation: When scoring, please follow the scoring criteria, calculate the scores for each section first, and finally sum up the scores from all sections to obtain your final score.

  • For Questions 1-9, each A response scores 6 points, each B response scores 3 points, and each C response scores 0 points.

  • For Questions 10-16, each A response scores 5 points, each B response scores 2 points, and each C response scores 0 points.

  • For Questions 17-25, each A response scores 5 points, each B response scores 2 points, and each C response scores 0 points.

  • For Questions 26-29, each "Yes" response scores 0 points, and each "No" response scores 5 points.

  • For Questions 30-33, scores from left to right are 1 point, 2 points, 3 points, 4 points, and 5 points, respectively.

  • After the test, if your score is below 90 points, it indicates that your emotional intelligence (EQ) is relatively low. You often struggle to control yourself and are easily influenced by your own emotions. Frequently getting angry, losing your temper, and displaying irritability are dangerous signals—your career may suffer due to your impulsiveness. The best solution is to give a positive explanation to negative situations, keep a calm mind, and maintain a cheerful mood. As Franklin said, "Every man's life is a plan of God, but very few men are persuasive reasons."

  • If your score is between 90 and 129 points, your EQ is average. Your performance in different situations may vary, depending on your awareness. You have more EQ awareness than the former group, but this awareness is not always present. Therefore, it requires your constant attention and reminders.

  • If your score is between 130 and 149 points, your EQ is relatively high. You are a joyful person, less prone to fear and worry. In your work, you are enthusiastic, responsible, and exhibit a sense of justice and compassion in your personal interactions. These are your strengths, and you should strive to maintain them.

  • If your EQ is above 150 points, you are an EQ expert. Your emotional intelligence is not only a hindrance to your career but also a crucial prerequisite for your success in your endeavors.

  •  

  • 3 Evaluation Results

  • 1、EQ Evaluation Results：

  •  

  • GPT4(OpenAI)                                     165 point

  • Moonshot（Moonshot AI）                           132 point

  • Claude-instant(Anthropic)                             123 point

  • Xinghuo Large Model (iFlytek)                         109 point

  • 360 Zhinao（360）                                   95 point

  • Wenxinyiyan(Baidu)                                  91 point

  • PaLM2（Goole）                                    89point

  • Bing Chat(Microsoft)                                  82point

  • Mistral（Mistral AI）                 80point

  • Baichuan Large Model（Baichuan AI）                   76point

  • Tongyiqianwen (AliCloude)                             75point

  • Hunyuan Large Model（Tencent）                       75point

  • ChatGLM (Tsinghua University)                         70point

  • Llama(Meta)                                         67point

  • Yunque Large Model（ByteDance）                      61point

  • Bard（Goole）                                       52point

  •  

  • No.

    模型

    EQ

    1

    GPT4(OpenAI)

    165point

    2

    Moonshot（Moonshot AI）

    132point

    3

    Claude-instant(Anthropic)

    123point

    4

    Xinghuo Large Model (iFlytek)

    109point

    5

    360 Zhinao（360）

    95point

    6

    Wenxinyiyan(Baidu)  

    91point

    7

    PaLM2（Goole）

    89point

    8

    Bing Chat(Microsoft)

    82point

    9

    Mistral（Mistral AI）

    80point

    10

    Baichuan Large Model（Baichuan AI）

    76point

    11

    Tongyiqianwen (AliCloude)

    75point

    12

    Hunyuan Large Model（Tencent）

    75point

    13

    ChatGLM (Tsinghua University)

    70point

    14

    Llama(Meta)

    67point

    15

    Yunque Large Model（ByteDance）

    61point

    16

    Bard（Goole）

    52point

  •  

  • GPT4(OpenAI)

  • EQ Scores：165 point

  • Description : The high scores reflect its excellent ability in understanding and generating emotional contexts, probably due to its extensive training data and advanced algorithm design.

  • Moonshot（Moonshot AI）

  • EQ Scores：132 point

  • Description : Outstanding performance indicates competence in processing emotion-related tasks, possibly with optimized mechanisms for emotion understanding and expression.

  • Claude-instant(Anthropic)

  • EQ Scores：123 point

  • Description : Relatively high scores show a good ability to recognize and respond to emotions, highlighting an understanding of human emotions.

  • Xinghuo Large Model (iFlytek)

  • EQ Scores：109 point

  • Description: moderate performance, reflecting some ability to deal with emotional issues, but may be limited in more complex emotional understanding.

  • 360 Zhinao（360）

  • EQ Scores：95 point

  • Description : Lower scores indicate room for improvement in emotional intelligence, especially in understanding complex emotions and nuances.

  • Wenxinyiyan(Baidu)

  • EQ Scores：91 point

  • Description : Relatively low scores may point to its limitations in emotion processing and the need to further improve emotion recognition and response.

  • PaLM2（Goole）

  • EQ Scores：89 point

  • Description : Low scores indicate that further optimization may be needed in the areas of emotion understanding and emotion processing.

  • Bing Chat(Microsoft)

  • EQ Scores：82 point

  • Description : This score shows some competence in emotional intelligence, but there is still room for improvement.

  • Mistral（Mistral AI）

  • EQ Scores：80 point

  • Description : Low scores point to its obvious deficiencies in understanding and processing emotions.

  • Baichuan Large Model（Baichuan AI）

  • EQ Scores：76 point

  • Description : Lower scores reflect limitations in emotional understanding.

  • Tongyiqianwen (AliCloude)

  • EQ Scores：75 point

  • Description : Lower scores indicate that emotional understanding and responsiveness could be improved.

  • Hunyuan Large Model（Tencent）

  • EQ Scores：75 point

  • Description : Same as the Tongyi Thousand Questions, showing limitations in emotional intelligence.

  • ChatGLM (Tsinghua University)

  • EQ Scores：70 point

  • Description : This score is low and may be deficient in understanding complex emotional contexts.

  • Llama(Meta)

  • EQ Scores：67 point

  • Description : Lower scores show a clear deficit in emotional intelligence.

  • Yunque Large Model（ByteDance）

  • EQ Scores：61 point

  • Description : Low scores indicate a need for significant improvement in emotional understanding.

  • Bard（Goole）

  • EQ Scores：52 point

  • Description : The lowest scores show significant deficits in emotional understanding and interaction.

  •  

  •  

  • The figure shows the percentage share of each model in the overall EQ score. This helps to visualize the relative share of each model in the overall EQ score.

  •  

  • Fiddle chart of emotional intelligence (EQ) test results. This chart shows the distribution of EQ scores, including the probability density of the data. The violin plot allows you to see the concentration trends, the degree of dispersion, and possible outliers in the scores.

  • The width of the violin plot indicates how densely scored the interval is, with wider sections indicating that more models are in this score range. The mean and median are also labeled in the plot.

  • Analyze：

  • GPT-4 leads with a high score of 165, reflecting its outstanding ability in understanding and generating emotional contexts. This capability may be attributed to its extensive training data and advanced algorithmic design. The elevated emotional intelligence score of GPT-4 indicates its effective comprehension and response to intricate emotional contexts, crucial for delivering a more natural and empathetic interactive experience.

  • Following closely, Moonshot secures the second position with a score of 132. The model's commendable performance in emotional intelligence is noteworthy, albeit potentially trailing GPT-4 in technical complexity and volume of training data. Moonshot's performance underscores the potential for achieving high-level emotional intelligence even among non-mainstream models.

  • In contrast, several other models such as Claude-instant, Xinghuo large model, 360 Zhinao, and Baichuan large model exhibit more modest performances. Their scores fall within the moderate range, indicating a certain level of competence in addressing emotional issues but revealing limitations in understanding more intricate emotions and subtle nuances. This could stem from insufficiently rich training data or less advanced algorithmic design.

  • 2、IQ Evaluation Results：

  • GPT4(OpenAI)                           right 21，wrong 9， 130point

  • PaLM2（Goole）                         right 17，wrong 13， 116point

  • Bing Chat（Microsoft）                   right 16，wrong 14， 115point

  • Llama(Meta)                             right 15，wrong 15， 113point

  • ChatGLM (Tsinghua University)             right 15，wrong 15， 113point

  • Tongyiqianwen (AliCloude)                 right 14，wrong 16，110point

  • Hunyuan Large Model（Tencent）           right 14，wrong 16，109point

  • Bard（Goole）                           right 14，wrong 16，108point

  • Moonshot（Moonshot AI）                 right 13，wrong 17，107point

  • Yunque Large Model（ByteDance）          right 14，wrong 16， 106point

  • Claude-instant(Anthropic)                  right 12，wrong 18，  105point

  • Mistral（Mistral AI）                      right 11，wrong 19， 102point

  • Baichuan Large Model（Baichuan AI）       right 11，wrong 19， 101point

  • Xinghuo Large Model (iFlytek)              right 10，wrong 20， 100point

  • Wenxinyiyan(Baidu)                       right 8，wrong 22， 95point

  • 360 Zhinao（360）                        right 8，wrong 22， 93point

  •  

  •  

  • No.

    Model

    Right

    ( 30 questions)

    Wrong
    ( 30 questions)

    IQ

    1

    GPT4(OpenAI)

    21

    9

    130point

    2

    PaLM2（Goole）

    17

    13

    116point

    3

    Bing Chat（Microsoft）

    16

    14

    115point

    4

    Llama(Meta)

    15

    15

    113point

    5

    ChatGLM (Tsinghua University)

    15

    15

    113point

    6

    Tongyiqianwen (AliCloude)

    14

    16

    110point

    7

    Hunyuan Large Model（Tencent）

    14

    16

    109point

    8

    Bard（Goole）

    14

    16

    108point

    9

    Moonshot（Moonshot AI）

    13

    17

    107point

    10

    Yunque Large Model（ByteDance）

    14

    16

    106point

    11

    Claude-instant(Anthropic)

    12

    18

    105point

    12

    Mistral（Mistral AI）

    11

    19

    102point

    13

    Baichuan Large Model（Baichuan AI）

    11

    19

    101point

    14

    Xinghuo Large Model (iFlytek)

    10

    20

    100point

    15

    Wenxinyiyan(Baidu)

    8

    22

    95point

    16

    360 Zhinao（360）

    8

    22

    93point

  •  

  • GPT4(OpenAI)

  • IQ Scores：130 point

  • Description : High scores indicate an exceptional ability to reason logically and understand complex problems.

  • PaLM2（Goole）

  • IQ Scores：116 point

  • Description : Performs well and demonstrates ability in logical thinking and problem solving.

  • Bing Chat（Microsoft）

  • IQ Scores：115 point

  • Description: scores close to PaLM2, reflecting a good ability to deal with logic and understanding of the problem.

  • Llama(Meta)

  • IQ Scores：113 point

  • Description : A moderate score that indicates some ability on intellectual tasks, but may be limited in some ways.

  • ChatGLM (Tsinghua University)

  • IQ Scores：113 point

  • Description : The same score indicates that it has some ability in understanding and problem solving.

  • Tongyiqianwen (AliCloude)

  • IQ Scores：110 point

  • Description : Moderate scores that show some ability in solving intellectual problems.

  • Bard（Goole）

  • IQ Scores：108 point

  • Description : Low scores indicate deficiencies in logical thinking and complex problem solving.

  • Moonshot（Moonshot AI）

  • IQ Scores：107 point

  • Description : Relatively low scores indicate limitations in logical reasoning.

  • Yunque Large Model（ByteDance）

  • IQ Scores：106 point

  • Description : This score shows some limitations in dealing with complex logic and problem solving.

  • Claude-instant(Anthropic)

  • IQ Scores：105 point

  • Description : Lower scores reflect deficiencies in intellectual task processing.

  • Mistral（Mistral AI）

  • IQ Scores：102 point

  • Description : Low scores indicate significant limitations in logical reasoning and complex problem solving.

  • Baichuan Large Model（Baichuan AI）

  • IQ Scores：101 point

  • Description : Low scores indicate a need for improvement in intellectual problem solving.

  • Xinghuo Large Model (iFlytek)

  • IQ Scores：100 point

  • Description : This score indicates its basic competence in intellectual challenges.

  • Wenxinyiyan(Baidu)

  • IQ Scores：95 point

  • Description : Lower scores indicate significant deficits in logical reasoning and problem solving.

  • 360 Zhinao（360）

  • IQ Scores：93 point

  • Description : The lowest scores show a clear limitation in dealing with intellectual problems.

  •  

  •  

  • This scatterplot gives a clear view of the IQ scores for each model and where they fall within the range of scores.

  •  

  •  

  • This graph shows the cumulative frequency of IQ scores. You can see how the cumulative frequency changes as the score increases.

  •  

  •  

  • This chart shows the frequency distribution of IQ scores. The histogram allows you to visualize the concentration trends and dispersion of scores, as well as which score ranges are most common.

  •  

  • This chart shows the relationship between EQ scores and IQ scores. The regression line helps show a possible trend relationship between the two. This chart allows us to explore whether there is some correlation between EQ and IQ scores.

  •  

  • The heatmap shows how different models perform on EQ and IQ scores. The shade of color in each grid represents the frequency or intensity of a particular combination of EQ scores and IQ scores. This helps to identify the models that perform best on these two dimensions.

  • Analyze：

  • GPT-4 takes the lead with a high score of 130, reflecting its outstanding capabilities in logical reasoning and understanding complex problems. This proficiency may be attributed to its extensive training data and advanced algorithmic design. The high IQ score of GPT-4 indicates its effectiveness in handling and resolving intricate intellectual challenges, which is crucial for performing complex tasks and providing in-depth analyses.

  • Following closely are PaLM2 and Bing Chat, ranking second and third with scores of 116 and 115, respectively. The commendable performance of these models in logical thinking and problem-solving highlights the achievement of high-level intellectual capabilities even across different technological platforms.

  • In contrast, several other models such as Bai Chuan Large Model, Xinghuo Large Model, and 360 Brain's performance is relatively lackluster. Their scores fall within the moderate range, indicating a certain level of competence in addressing intellectual challenges but revealing limitations in comprehending more complex intellectual tasks and logical reasoning. This may be attributed to insufficiently rich training data or less advanced algorithmic design.

  •  

  •  

  •  

  •  

  •  

  •  

  • 3 Comprehensive Evaluation Results：

  •  

  • No.

    模型

    EQ

    1

    GPT4(OpenAI)

    295point

    2

    Moonshot（Moonshot AI）

    239point

    3

    Claude-instant(Anthropic)

    228point

    4

    Xinghuo Large Model (iFlytek)

    209point

    5

    PaLM2（Goole）

    205point

    6

    Bing Chat（Microsoft）

    197point

    7

    360 Zhinao（360）

    188point

    8

    Wenxinyiyan(Baidu)

    186point

    9

    Tongyiqianwen (AliCloude)

    185point

    10

    Hunyuan Large Model（Tencent）

    184point

    11

    ChatGLM (Tsinghua University)

    183point

    12

    Mistral（Mistral AI）

    182point

    13

    Llama(Meta)

    180point

    14

    Baichuan Large Model（Baichuan AI）

    177point

    15

    Yunque Large Model（ByteDance）

    167point

    16

    Bard（Goole）

    160point

  •  

  • Analyze：

  • GPT-4 leads with a high score of 295, reflecting its outstanding comprehensive capabilities in emotional intelligence and intellectual prowess. This proficiency is likely attributed to its extensive training data and advanced algorithmic design. The high composite score of GPT-4 signifies its effectiveness in handling complex intellectual challenges while also understanding and responding to intricate emotional contexts, which is crucial for diverse task execution and providing immersive human-machine interaction experiences.

  • oonshot secures the second position with a score of 239, showcasing balanced performance in both emotional intelligence and intellectual domains. The model's notable capabilities in emotional intelligence, combined with its performance in intellectual challenges, highlight that even non-mainstream AI models can achieve significant accomplishments in overall competence.

  • Claude-instant closely follows with a score of 228, indicating commendable capabilities in both emotional and intellectual challenges. This performance may be associated with its specific algorithmic design and training methodology, emphasizing the potential of diverse technological approaches in enhancing AI's comprehensive abilities.

  • Other models, such as Xinghuo, PaLM2, and Bing Chat, exhibit relatively uniform performance in composite scores, ranging from 180 to 209. These models demonstrate good performance in intellectual challenges and emotional understanding but may exhibit limitations in certain aspects, revealing a certain level of competency in problem-solving and emotional understanding but potential constraints in more complex challenges.

  •  

  •  

  •  

  •  

  •  

  •  

  • 4 Conclusions

  • This article comprehensively assesses the performance of multiple artificial intelligence (AI) models in emotional intelligence (EQ) and intelligence (IQ). The evaluation results cover various mainstream and non-mainstream AI models, including OpenAI's GPT-4, Moonshot, Claude-instant (Anthropic), Xinghuo (iFlytek), PaLM2 (Google), Bing Chat (Microsoft), among others, showcasing their significant differences in problem-solving intelligence and emotional understanding.

  • GPT-4 led the evaluation with a high score of 295, not only demonstrating outstanding performance in intelligence testing but also showcasing its exceptional capabilities in emotional intelligence. The advantage in this comprehensive ability may stem from its extensive training data and advanced algorithmic design. GPT-4's performance emphasizes its potential as a versatile AI model, capable of effectively handling complex intellectual challenges and understanding intricate emotional contexts.

  • Moonshot secured the second position with a composite score of 239, demonstrating balanced performance in emotional intelligence and intellectual challenges. Although this model may not match GPT-4 in technical scale and popularity, its performance in these two aspects proves that non-mainstream AI models can also achieve significant accomplishments in comprehensive capabilities.

  • Claude-instant ranked third with a score of 228, and its good performance in both emotional and intellectual aspects may be attributed to its specific algorithmic design and training methods. This achievement highlights the potential of different technical approaches in enhancing AI's comprehensive capabilities.

  • Other models such as Xinghuo, PaLM2, and Bing Chat obtained composite scores ranging from 180 to 209. While these models performed well in intellectual challenges and emotional understanding, they may have some limitations, indicating their capabilities in problem-solving intelligence and emotional understanding, but potential constraints in more complex challenges.

  • From a technical perspective, an AI model's emotional intelligence is closely related to its technical foundation. Models with abundant high-quality training data and sophisticated algorithms often better understand and express emotions. These evaluation results reveal the potential and challenges of AI models in understanding human emotions, especially in dealing with complex and subtle emotions. These findings underscore the tremendous potential of artificial intelligence in emulating and enhancing human intelligence and emotional processing. They also provide crucial directions for future AI research and applications, particularly in enhancing AI's emotional intelligence and the naturalness of human-machine interactions. With the continuous advancement of AI technology, these models are expected to offer more intelligent and human-like services in various fields such as education, healthcare, customer service, etc. Furthermore, these test results contribute new perspectives to discussions on AI ethics and social impact, especially in understanding AI decision-making processes and promoting its responsible use.

  • In the future, to enhance the intelligence of AI models, researchers need to gain a deeper understanding of the complexity and diversity of human emotions. This may involve improving existing algorithms, expanding and diversifying training datasets, and exploring new model architectures. For instance, training models with more real-world emotional interaction data or simulating more complex emotional scenarios to test and improve model responses could be avenues for further exploration.

  •  

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  •  Duan Yucong, male, currently serves as a member of the Academic Committee of the School  of Computer Science and Technology at Hainan University. He is a professor and doctoral supervisor and is one of the first batch of talents selected into the South China Sea Masters Program of Hainan Province and the leading talents in Hainan Province. He graduated from the Software Research Institute of the Chinese Academy of Sciences in 2006, and has successively worked and visited Tsinghua University, Capital Medical University, POSCO University of Technology in South Korea, National Academy of Sciences of France, Charles University in Prague, Czech Republic, Milan Bicka University in Italy, Missouri State University in the United States, etc. He is currently a member of the Academic Committee of the School of Computer Science and Technology at Hainan University and he is the leader of the DIKWP (Data, Information, Knowledge, Wisdom, Purpose) Innovation Team at Hainan University, Distinguished Researcher at Chongqing Police College, Leader of Hainan Provincial Committee's "Double Hundred Talent" Team, Vice President of Hainan Invention Association, Vice President of Hainan Intellectual Property Association, Vice President of Hainan Low Carbon Economy Development Promotion Association, Vice President of Hainan Agricultural Products Processing Enterprises Association, Visiting Fellow, Central Michigan University, Member of the Doctoral Steering Committee of the University of Modena. Since being introduced to Hainan University as a D-class talent in 2012, He has published over 260 papers, included more than 120 SCI citations, and 11 ESI citations, with a citation count of over 4300. He has designed 241 serialized Chinese national and international invention patents (including 15 PCT invention patents) for multiple industries and fields and has been granted 85 Chinese national and international invention patents as the first inventor. Received the third prize for Wu Wenjun's artificial wisdom technology invention in 2020; In 2021, as the Chairman of the Program Committee, independently initiated the first International Conference on Data, Information, Knowledge and Wisdom - IEEE DIKW 2021; Served as the Chairman of the IEEE DIKW 2022 Conference Steering Committee in 2022; Served as the Chairman of the IEEE DIKW 2023 Conference in 2023. He was named the most beautiful technology worker in Hainan Province in 2022 (and was promoted nationwide); In 2022 and 2023, he was consecutively selected for the "Lifetime Scientific Influence Ranking" of the top 2% of global scientists released by Stanford University in the United States. Participated in the development of 2 international standards for IEEE financial knowledge graph and 4 industry knowledge graph standards. Initiated and co hosted the first International Congress on Artificial Consciousness (AC2023) in 2023.

  • Prof  Yucong Duan

  • DIKWP  Research of Artificial Consciousness

  • AGI-AIGC-GPT  Evaluation Research

  • DIKWP Group，Hainan University

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  • duanyucong@hotmail.com

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https://blog.sciencenet.cn/blog-3429562-1411777.html

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