Notice: The current evaluation report is intended solely for the purpose of soliciting comments. The team kindly requests your valuable feedback and suggestions. We are committed to continuously revising the report based on the available evidence.

Background

From 1950, when the Turing test was proposed, to 2022, when ChatGPT addressed the Turing test, Artificial Intelligence (AI) has undergone decades of innovation and thriving development. Throughout this continuous evolution, numerous influential figures, concepts, events, and achievements have emerged, giving birth to numerous subfields and research topics within AI. These achievements have enriched the AI ecosystem, enabling it to process single tasks such as image classification, augment complex application scenarios like Internet services, and even achieve general intelligence comparable to human beings.

Evaluation Standards

We have identified the top AI achievements that have had significant impacts and have played a crucial role in the development of AI and related disciplines. Our evaluation criteria are as follows:

  • Original or pioneering works in artificial intelligence or its subfields.
  • Works that have significantly contributed to the advancement of artificial intelligence or its subfields.
  • Works that are widely used or cited by industry or academia.

AI100: Top 100 AI achievements (1943-2021)

The data and figures presented here are derived from the technical report that will be released during the 2023 BenchCouncil International Federated Intelligent Computing and Chip Conferences (FICC 2023).

Overview of Top AI achievements

（Please note that the tree diagram can be zoomed in, zoomed out, and moved. You can click on the circles at the branches to expand or collapse the content of the diagram.）

Top AI Achievements

When considering the main contributors, we will only include the following in the list:

  • The first author, including authors with equal contribution.
  • The corresponding author, or the last author if there is no corresponding author.

If you have any comments or suggestions regarding the list, please feel free to email us at benchcouncil.evaluation@gmail.com.

Area Work Year Publications Citation Main
Contributors 		Institution Country
Theory Turing test 1950 Computing machinery and intelligence 21510 Alan Turing Manchester University UK
Complexity theory 1971 The Complexity of Theorem Proving Procedures 10695 Stephen Cook University of Toronto Canada
VC theory 1960-1990 The nature of statistical learning theory 104601 Vladimir Vapnik, Alexey Chervonenkis Institute of Control Sciences Moscow Russia
Automated theorem proving Logic Theorist 1956 The logic theory machine-a complex information processing system 1046 Allen Newell, Herbert Simon Carnegie Mellon University USA
Wang's algorithm 1958-1961 Proving theorems by pattern recognition I (1960) 173 Hao Wang Bell Lab USA
Proving theorems by pattern recognition II (1961) 1083
Toward mechanical mathematics (1960) 456
Davis-Putnam algorithm & DPLL 1960 A Computing Procedure for Quantification Theory 4358 Martin Davis, Hilary Putnam, Donald Loveland Rensselaer Polytechnic Institute, Princeton University, New York University USA
1961 A machine program for theorem-proving 4874
Resolution method 1965 A machine-oriented logic based on the resolution principle 6573 John Robinson Argonne Nalionrd Laboratory USA
Otter 1990s William McCune Argonne National Laboratory USA
Language LISP 1958 Recursive functions of symbolic expressions and their computation by machin (1960) 2491 John McCarthy MIT USA
PROLOG 1973 Alain Colmerauer, Robert Kowalski University of Edinburgh UK
ChatBot ELIZA 1964-1967 ELIZA-a computer program for the study of natural language communication between man and machine 6890 Joseph Weizenbaum MIT USA
Computer power and human reason: From judgment to calculation 5214
SHRDLU 1968-1970 Terry Winograd MIT USA
IBM Watson 2000 David Ferrucci IBM USA
Game Christopher Strachey's Draughts 1951 Logical or non-mathematical programmes 62 Christopher Strachey National Research Development Corporation UK
Chinook 1989-2007 Jonathan Schaeffer University of Alberta Canada
Deep Blue 1996 Feng-hsiung Hsu, Murray Campbell, Arthur Hoane, Jerry Brody IBM USA
Perception Pandemonium 1959 Pandemonium: a paradigm for learning 1611 Oliver Selfridge MIT USA
Knowlege representation Frame 1974 A Framework for Representing Knowledge 14989 Marvin Minsky MIT USA
Cyc 1984 CYC: Using common sense knowledge to overcome brittleness and knowledge acquisition bottlenecks 560 Douglas Lenat MCC USA
Expert system Dendral 1965 Edward Feigenbaum, Bruce Buchanan, Joshua Lederberg, Carl Djerassi Stanford University USA
XCON-R1 1978 R1: A rule-based configurer of computer systems 1682 John McDermott CMU USA
Cluster, Classification, Regression Kmeans 1957 Least squares quantization in PCM (1982) 18533 Stuart Lloyd Bell Lab USA
DBSCAN 1996 A density-based algorithm for discovering clusters in large spatial databases with noise 29901 Martin Ester, Xiaowei Xu University of Munic Germany
Spectral clustering 2000 Normalized Cuts and Image Segmentation 19732 Jianbo Shi, Jitendra Malik, Andrew Ng, Yair Weiss University of Pennsylvania, U.C. Berkeley, Hebrew University USA, Israel
2001 On spectral clustering: Analysis and an algorithm 11945
KNN 1967 Nearest neighbor pattern classification 17605 Thomas Cover, Peter Hart University of Stanford, Stanford Research Institute USA
Ridge 1970 Ridge regression: Biased estimation for nonorthogonal problems 15332 Arthur Hoerl, Robert Kennard University of Delawar USA
SVM 1992 A training algorithm for optimal margin classifiers 63346 Bernhard Boser, Vladimir Vapnik, Corinna Cortes Bell Lab USA
1995 Support-vector networks 16549
Lasso 1996 Regression shrinkage and selection via the lasso 55395 Robert Tibshirani University of Toronto Canada
Dimension reduction , Feature extraction SIFT 1999 Object recognition from local scale-invariant features 24749 David Lowe University of British Columbia Canada
2004 Distinctive image features from scale-invariant keypoints 72302
HOG 2005 Histograms of oriented gradients for human detection 43894 Navneet Dalal, Bill Triggs INRIA France
SURF 2006 Surf: Speeded up robust features 36237 Herbert Bay, Andreas Ess ETH Zurich Switzerland
Kernel PCA 1997 Kernel principal component analysis 3193 Bernhard Schölkopf, Klaus-Robert Muller Max Planck Institute for Biological Cybernetics Germany
1998 Nonlinear component analysis as a kernel eigenvalue problem 10615
NMF 1999 Learning the parts of objects by non-negative matrix factorization 15562 Daniel Lee, H Sebastian Seung Bell Lab, MIT USA
2000 Algorithms for non-negative matrix factorization 11766
Isomap 2000 A global geometric framework for nonlinear dimensionality reduction 16447 Joshua Tenenbaum Stanford University USA
Locally linear embedding 2000 Nonlinear dimensionality reduction by locally linear embedding 18075 Sam Roweis, Lawrence Saul AT&T Labs, University College London USA, UK
t-SNE 2008 Visualizing data using t-SNE 38132 Laurens van der Maaten, Geoffrey Hinton Tilburg University, University of Toronto
 Netherlands, Canada
Neural Network McCulloch-Pitts neuron 1943 logical calculus of the ideas immanent
in nervous activity 		28581 Warren McCulloch, Walter Pitts University of Illinois at Chicago USA
SNARC 1951 Marvin Minsky Princeton University USA
Rosenblatt Perceptron 1958 The perceptron: a probabilistic model for information storage and organization in the brain 17938 Frank Rosenblatt Cornell University USA
1962 Principles of neurodynamics: Perceptrons and the theory of brain mechanisms 9677
Hopfield network 1982 Neural networks and physical systems with emergent collective computational abilities 26481 John Hopfield California Institute of Technology USA
1984 Neurons with graded response have collective computational properties like those of two-state neurons 9293
1985 Neural computation of decisions in optimization problems 8723
Self-organizing map 1982 Self-organized formation of topologically correct feature maps 13313 Teuvo Kohonen Helsinki University of Technolog Finland
DBN 2006 A fast learning algorithm for deep belief nets 20213 Geoffrey Hinton, Yee-Whye The, Ruslan Salakhutdinov University of Toronto, National University of Singapore Canada, Singapore
2006 Reducing the dimensionality of data with neural networks 21334
Back-propagation 1967 A theory of adaptive pattern classifiers 767 Shun'ichi Amari, David Rumelhart, Ronald Williams Kyushu University, UC San Diego, CMU Japan, USA
1986 Learning representations by back-propagating errors 35330
ReLU 1969 Visual feature extraction by a multilayered network of analog threshold elements 186 Kunihiko Fukushima, Xavier Glorot, Yoshua Bengio NHK Broadcasting Science Research Laboratories, University of Montreal Japan, Canada
2011 Deep Sparse Rectifier Neural Networks 11109
Adam 2014 Adam: A method for stochastic optimization 162259 Diederik Kingma, Jimmy Ba OpenAI, University of Toronto USA, Canada
Dropout 2014 Dropout: a simple way to prevent neural networks from overfitting 46447 Nitish Srivastava, Ruslan Salakhutdinov University of Toronto Canada
Batch Normalization 2015 Batch normalization: Accelerating deep network training by reducing internal covariate shift 50391 Sergey Ioffe, Christian Szegedy Google USA
Neocognitron 1980 Neocognitron: A self-organizing neural network model for a mechanism of pattern recognition unaffected by shift in position 8344 Kunihiko Fukushima NHK Broadcasting Science Research Laboratories Japan
LeNet 1989 Backpropagation Applied to Handwritten Zip Code Recognition 15372 Yann LeCun Bell Labl USA
1998 Gradient-based learning applied to document recognition 59141
AlexNet 2012 Imagenet classification with deep convolutional neural networks 142908 Alex Krizhevsky, Geoffrey Hinton University of Toronto Canada
VGG 2014 Very deep convolutional networks for large-scale image recognition 111338 Karen Simonyan, Andrew Zisserman University of Oxford UK
GooleNet (Inception) 2015 Going deeper with convolutions 54115 Christian Szegedy, Vincent Vanhoucke Google USA
2016 Rethinking the inception architecture for computer vision 29223
2017 Inception-v4, inception-resnet and the impact of residual connections on learning 15312
ResNet 2015 Deep Residual Learning for Image Recognition 188934 Kaiming He, Jian Sun Microsoft Research (Asia) China
DenseNet 2017 Densely connected convolutional networks 39133 Gao Huang, Zhuang Liu, Kilian Weinberger Cornell University, Tsinghua University, Facebook AI Research
 USA, China
Mobilenets 2017 Mobilenets: Efficient convolutional neural networks for mobile vision applications 21737 Andrew Howard, Mark Sandler Google USA
2018 Mobilenetv2: Inverted residuals and linear bottlenecks 18118
Squeeze-and-excitation 2018 Squeeze-and-excitation networks 25132 Jie Hu, Gang Sun Momenta, University of Oxford China, UK
R-cnn 2014 Rich feature hierarchies for accurate object detection and semantic segmentation 35745 Ross Girshick, Jitendra Malik UC Berkeley USA
Fast r-cnn 2015 Fast R-CNN 30211 Ross Girshick Microsoft Research USA
Faster r-cnn 2015 Faster R-CNN: Towards real-time object detection with region proposal networks 65754 Shaoqing Ren, Jian Sun Microsoft Research (Asia)
 China
Mask r-cnn 2017 Mask R-CNN 30287 Kaiming He, Ross Girshick Facebook USA
FPN (RetinaNet) 2017 Feature pyramid networks for object detection 22063 Tsung-Yi Lin, Serge Belongie, Piotr Dollar Facebook, Cornell University USA
2017 Focal loss for dense object detection 24933
YOLO 2016 You only look once: Unified, real-time object detection 40287 Joseph Redmon, Ali Farhadi University of Washington, Allen Institute for AI, Facebook AI Research USA
2017 YOLO9000: Better, Faster, Stronger 18709
2018 Yolov3: An incremental improvement 23635
SSD 2016 Ssd: Single shot multibox detector 33293 Wei Liu, Alexander Berg UNC Chapel Hill, Zoox , Google, University of Michigan USA
FCN 2015 Fully convolutional networks for semantic segmentation 43947 Jonathan Long, Evan Shelhamer, Trevor Darrell UC Berkeley USA
U-net 2015 U-net: Convolutional networks for biomedical image segmentation 71959 Olaf Ronneberger, Thomas Brox University of Freiburg Germany
LSTM 1996 Long short-term memory 92138 Sepp Hochreiter, Juergen Schmidhuber Technical University of Munich, IDSIA Germany, Switzerland
Seq2Seq 2014 Learning Phrase Representations using RNN Encoder-Decoder for Statistical Machine Translation 26352 Kyunghyun Cho, Yoshua Bengio, Ilya Sutskever, Quoc V. Le University of Montreal,Jacobs University, University of Maine, Google Canada, Germany, France, USA
2014 Sequence to sequence learning with neural networks 23773
Attention 2015 Neural machine translation by jointly learning to align and translate 31310 Dzmitry Bahdanau, Yoshua Bengio, Minh-Thang Luong, Christopher Manning, Kelvin Xu Jacobs University Bremen, University of Montreal, Stanford University, University of Toronto Germany,Canada,USA
2015 Effective approaches to attention-based neural machine translation 9632
2015 Show, attend and tell: Neural image caption generation with visual attention 11300
Transformer 2017 Attention is all you need 92865 Ashish Vaswani, Noam Shazeer, Niki Parmar, Jakob Uszkoreit, Llion Jones, Aidan Gomez, Lukasz Kaiser Google, University of Toronto USA, Canada
BERT 2018 BERT: Pre-training of deep bidirectional transformers for language understanding 80349 Jacob Devlin, Kristina Toutanova Google USA
GPT 2018 Improving Language Understanding by Generative Pre-Training 6822 Alec Radford, Ilya Sutskever, Jeffrey Wu, Dario Amodei, Tom Brown, Benjamin Mann, Nick Ryder, Melanie Subbiah OpenAI USA
2019 Language models are unsupervised multitask learners 7187
2020 Language models are few-shot learners 15443
ViT 2020 An image is worth 16x16 words: Transformers for image recognition at scale 22968 Alexey Dosovitskiy, Lucas Beyer, Alexander Kolesnikov, Dirk Weissenborn, Xiaohua Zhai, Neil Houlsby Google USA
Swin Transformer 2021 Swin transformer: Hierarchical vision transformer using shifted windows 11034 Ze Liu, Yutong Lin, Yue Cao, Han Hu Microsoft Research Asia, University of Science and Technology of China, Xian Jiaotong University, Tsinghua University China
Neural Language Model 2000 A Neural probabilistic language model 10580 Yoshua Bengio University of Montreal Canada
Word2vec 2013 Distributed representations of words and phrases and their compositionality 40956 Tomas Mikolov, Jeffrey Dean Google USA
2013 Efficient estimation of word representations in vector space 37952
Glove 2014 Glove: Global vectors for word representation 37136 Jeffrey Pennington, Christopher Manning Stanford University USA
GAN 2014 Generative adversarial nets 61187 Ian Goodfellow, Yoshua Bengio University of Montreal Canada
Conditional GAN 2014 Conditional Generative adversarial nets 11325 Mehdi Mirza, Simon Osindero University of Montreal, Yahoo Canada, USA
DCGAN 2015 Unsupervised representation learning with deep convolutional generative adversarial networks 16008 Alec Radford, Soumith Chintala indico Research
, Facebook 		USA
Wassertein GAN 2017 Wasserstein generative adversarial networks 14158 Martin Arjovsky, Leon Bottou Courant Institute of Mathematical Sciences, Facebook USA
CycleGAN 2017 Unpaired Image-to-Image Translation using Cycle-Consistent Adversarial Networks 19686 Jun-Yan Zhu, Taesung Park, Alexei Efros UC Berkeley USA
Pix2Pix 2017 Image-to-image translation with conditional adversarial networks 20017 Phillip Isola, Alexei Efros UC Berkeley USA
StyleGAN 2019 A Style-Based Generator Architecture for Generative Adversarial Networks 8469 Tero Karras, Timo Aila NVIDIA USA
2020 Analyzing and improving the image quality of stylegan 4523
Variational autoencoder 2013 Auto-Encoding Variational Bayes 31045 Diederik Kingma, Max Welling University of Amsterdam Netherlands
Diffusion Model 2015 Deep unsupervised learning using nonequilibrium thermodynamics 2190 Jascha Sohl-Dickstein, Surya Ganguli, Jonathan Ho, Pieter Abbee Stanford University, UC Berkeley USA
2020 Denoising diffusion probabilistic models 4136
GNN 2005 A new model for learning in graph domains 1984 Marco Gori, Franco Scarselli University of Sienna, Hong Kong Baptist University, University of Wollongong Italy, China, Australia
2008 The graph neural network model 6808
GCN 2016 Semi-supervised classification with graph convolutional networks 27798 Thomas Kipf, Max Welling University of Amsterdam Netherlands
GAT 2017 Graph attention networks 11901 Petar Velickovic, Yoshua Bengio University of Cambridge, Montreal Institute for Learning Algorithms UK, Canada
NAS 2016 Neural architecture search with reinforcement learning 5600 Barret Zoph, Quoc V. Le Google USA
Deep compression 2015 Deep compression: Compressing deep neural networks with pruning, trained quantization and huffman coding 9166 Song Han, William Dally Stanford University,Tsinghua University, NVIDIA USA, China
knowledge distillation 2015 Distilling the knowledge in a neural network 16181 Geoffrey Hinton, Oriol Vinyals, Jeff Dean Google USA
ImageNet 2009 Imagenet: A large-scale hierarchical image database 58393 Jia Deng, Li Fei-Fei, Olga Russakovsky Princeton University, Stanford University, University of Michigan, MIT, UNC Chapel Hill USA
2015 Imagenet large scale visual recognition challenge 40459
MS COCO 2014 Microsoft coco: Common objects in context 40062 Tsung-Yi Lin, Piotr Dollar Cornell NYC Tech, Toyota Technological Institute, Facebook, Microsoft, Brown University, California Institute of Technology, University of California at Irvine USA
Reinforce learning Temporal-difference update 1988 Learning to predict by the methods of temporal differences 7556 Richard Sutton GTE Laboratories Incorporated USA
Q Learning 1989 Learning from delayed rewards 9624 Christopher Watkins, Peter Dayan King's College, University of Edinburgh UK
1992 Q-learning 18141
Deep Q Network 2013 Playing atari with deep reinforcement learning 13087 Volodymyr Mnih, Martin Riedmiller, Koray Kavukcuoglu, David Silver Google DeepMind UK
2015 Human-level control through deep reinforcement learning 26305
DDPG 2015 Continuous control with deep reinforcement learning 13697 Timothy Lillicrap, Jonathan Hunt, Daan Wierstra Google DeepMind UK
AlphaGo 2016 Mastering the game of Go with deep neural networks and tree search 16937 David Silver, Aja Huang, Demis Hassabis, Julian Schrittwieser, Karen Simonyan Google DeepMind UK, USA
2017 Mastering the game of go without human knowledge 9655
AlphaFold 2021 Highly accurate protein structure prediction with AlphaFold 15446 John Jumper, Demis Hassabis DeepMind UK
Actor-Critic 1983 Neuronlike adaptive elements that can solve difficult learning control problems 4855 Andrew Barto, Charles Anderson University of Massachusetts, Amherst USA
A3C 2016 Asynchronous methods for deep reinforcement learning 9697 Volodymyr Mnih, Koray Kavukcuoglu DeepMind, University of Montreal UK, Canada
SARSA 1994 Online Q-Learning using Connectionist Systems 2479 Gavin Rummery, Mahesan Niranjan University of Cambridge UK
Williams's REINFORCE 1992 Simple statistical gradient-following algorithms for connectionist reinforcement learning 10190 Ronald Williams Northeastern Universit USA
Policy gradient theorem 1999 Policy gradient methods for reinforcement learning with function approximation 7376 Richard Sutton, Yishay Mansour AT&T Labs USA
Desion Tree, Ensemble learning CART 1984 Classification and regression trees 61639 Leo Breiman, Richard olshen UC Berkeley, Stanford University USA
ID3 1986 Induction of decision trees 29557 Ross Quinlan New South Wales Institute of Technology Australia
C4.5 1993 C4. 5: Programs for machine learning 43386 Ross Quinlan New South Wales Institute of Technology Australia
Bagging 1996 Bagging predictors 34768 Leo Breiman UC Berkeley USA
Random forests 1995 Random decision forests 8450 Tin Kam Ho, Leo Breiman Bell Labs, UC Berkeley USA
2001 Random forests 117057
Boost 1990 The strength of weak learnability 6850 Robert Schapire MIT USA
Adaboost 1997 A decision-theoretic generalization of on-line learning and an application to boosting 26782 Yoav Freund, Robert Schapire Bell Lab USA
Gradient boosting 2001 Greedy function approximation: a gradient boosting machine 24147 Jerome Friedman Stanford University USA
2002 Stochastic gradient boosting 7595
XGBoost 2016 XGBoost: A Scalable Tree Boosting System 31647 Tianqi Chen, Carlos Guestrin University of Washington USA
LightGBM 2017 Lightgbm: A highly efficient gradient boosting decision tree 9460 Guolin Ke, Tie-Yan Liu Microsoft, Peking University USA
Probabilistic graphical model Bayesian network 1982 Reverend Bayes on inference engines: A distributed hierarchical approach 1303 Judea Pearl University of California, Los Angeles USA
1988 Probabilistic reasoning in intelligent systems: networks of plausible inference 32565
LDA 2003 Latent dirichlet allocation 49298 David Blei, Michael Jordan UC Berkeley, Stanford University USA
CRF 2001 Conditional random fields: Probabilistic models for segmenting and labeling sequence data 18044 John Lafferty, Fernando Pereira MIT, University of Pennsylvania USA
Evolutionary algorithms Genetic Algorithm 1975
Adaptation in natural and artificial systems: An introductory analysis with applications to biology, control, and artificial intelligence 		80564 John Holland University of Michigan, Ann Arbor USA
Simulated annealing 1983 Optimization by simulated annealing 56687 Scott Kirkpatrick, Mario Vecchi IBM USA


Top AI Contributors

ID Contributor Grade Institution Country
1 Yoshua Bengio 2.78 University of Montreal Canada
2 Leo Breiman 2.00 UC Berkeley USA
3 Marvin Minsky 2.00 MIT USA
4 Ross Girshick 2.00 Facebook  USA
5 Ross Quinlan 2.00 RuleQuest Research Australia
6 Geoffrey Hinton 1.67 University of Toronto Canada
7 Richard Sutton 1.50 University of Alberta Canada
8 Robert Schapire 1.50 Microsoft USA
9 Kunihiko Fukushima 1.33 Fuzzy Logic Systems Institute Japan
10 Ronald Williams 1.33 Northeastern University USA
11 Alan Turing 1.00 University of Manchester UK
12 Christian Szegedy 1.00 Google USA
13 Christopher Strachey 1.00 University of Oxford USA
14 David Ferrucci 1.00 IBM USA
15 David Lowe 1.00 Google USA
16 Diederik Kingma 1.00 Google USA
17 Douglas Lenat 1.00 Cycorp USA
18 Frank Rosenblatt 1.00 Cornell University USA
19 Hao Wang 1.00 Rockefeller University  USA
20 Jerome Friedman 1.00 Stanford University USA
21 Jian Sun 1.00 Microsoft Aisa China
22 John Holland 1.00 University of Michigan USA
23 John Hopfield 1.00 Princeton University USA
24 John McCarthy 1.00 Stanford University USA
25 John McDermott 1.00 CMU USA
26 John Robinson 1.00 Syracuse University USA
27 Jonathan Schaeffer 1.00 University of Alberta Canada
28 Joseph Weizenbaum 1.00 MIT USA
29 Joshua Tenenbaum 1.00 MIT USA
30 Judea Pearl 1.00 UC Los Angeles USA
31 Kaiming He 1.00 Facebook USA
32 Max Welling 1.00 University of Amsterdam Netherlands
33 Oliver Selfridge 1.00 MIT  USA
34 Robert Tibshirani 1.00 Stanford University USA
35 Stephen Cook 1.00 University of Toronto Canada
36 Stuart Lloyd 1.00 Bell Lab USA
37 Terry Winograd 1.00 Stanford University USA
38 Teuvo Kohonen 1.00 Helsinki University of Technology Finland
39 William McCune 1.00 University of New Mexico USA
40 Yann LeCun 1.00 New York University USA
41 Alexei Efros 0.83 UC Berkeley USA
42 Jeffrey Dean 0.83 Google USA
43 Piotr Dollar 0.83 Facebook USA
44 Ruslan Salakhutdinov 0.83 CMU USA
45 Tsung-Yi Lin 0.83 NVIDIA USA
46 Vladimir Vapnik 0.83 Facebook USA
47 Jitendra Malik 0.75 UC Berkeley USA
48 Koray Kavukcuoglu 0.75 Google USA
49 Quoc V. Le 0.75 Google USA
50 Volodymyr Mnih 0.75 Google USA
51 Christopher Manning 0.70 Stanford University USA
52 Demis Hassabis 0.70 Google USA
53 Karen Simonyan 0.70 Inflection AI UK
54 Alec Radford 0.63 OpenAI USA
55 Alain Colmerauer 0.50 Aix-Marseille University France
56 Alex Krizhevsky 0.50 Dessa  USA
57 Alexander Berg 0.50 University of California Irvine USA
58 Alexey Chervonenkis 0.50 Russian Academy of Sciences Russia
59 Ali Farhadi 0.50 University of Washington USA
60 Allen Newell 0.50 CMU USA
61 Andreas Ess 0.50 ETH Zurich Switzerland
62 Andrew Barto 0.50 University of Massachusetts Amherst USA
63 Andrew Howard 0.50 Google USA
64 Andrew Zisserman 0.50 University of Oxford UK
65 Arthur Hoerl 0.50 University of Delawar USA
66 Barret Zoph 0.50 OpenAI USA
67 Bernhard Scholkopf 0.50 Max Planck Institute for Intelligent Systems Germany
68 Bill Triggs 0.50 Laboratoire Jean Kuntzmann France
69 Carlos Guestrin 0.50 Stanford University USA
70 Charles Anderson 0.50 Colorado State University USA
71 Christopher Watkins 0.50 Royal Holloway UK
72 Daniel Lee 0.50 Tisch University USA
73 David Blei 0.50 Columbia University USA
74 Fernando Pereira 0.50 Google USA
75 Franco Scarselli 0.50 University of Siena Italy
76 Gang Sun 0.50 Momenta China
77 Gavin Rummery 0.50 University of Cambridge UK
78 Guolin Ke 0.50 DP Technology China
79 H Sebastian Seung 0.50 Princeton University USA
80 Herbert Bay 0.50 Earkick Switzerland
81 Herbert Simon 0.50 CMU USA
82 Ian Goodfellow 0.50 Stanford University USA
83 Jacob Devlin 0.50 Google USA
84 Jeffrey Pennington 0.50 Stanford University USA
85 Jie Hu 0.50 Institute of Software, Chinese Academy of Sciences China
86 Jimmy Ba 0.50 University of Toronto Canada
87 John Jumper 0.50 Google USA
88 John Lafferty 0.50 Yale University USA
89 Joseph Redmon 0.50 University of Washington USA
90 Juergen Schmidhuber 0.50 Dalle Molle Institute for Artificial Intelligence Research Switzerland
91 Klaus-Robert Muller 0.50 Max Planck Institute for Intelligent Systems Germany
92 Kristina Toutanova 0.50 Google USA
93 Laurens van der Maaten 0.50 Facebook USA
94 Lawrence Saul 0.50 Flatiron Institute New Zealand
95 Leon Bottou 0.50 New York University USA
96 Mahesan Niranjan 0.50 University of Southampton UK
97 Marco Gori 0.50 University of Siena Italy
98 Mario Vecchi 0.50 MPV Technology USA
99 Mark Sandler 0.50 Google USA
100 Martin Arjovsky 0.50 New York University USA
101 Martin Ester 0.50 Simon Fraser University Canada
102 Mehdi Mirza 0.50 Google Canada
103 Michael Jordan 0.50 UC Berkeley USA
104 Navneet Dalal 0.50 Matician USA
105 Nitish Srivastava 0.50 Apple USA
106 Olaf Ronneberger 0.50 University of Freiburg Germany
107 Petar Velickovic 0.50 University of Cambridge UK
108 Peter Dayan 0.50 Max Planck Institute for Biological Cybernetics Germany
109 Peter Hart 0.50 SRI International AI Center USA
110 Phillip Isola 0.50 MIT USA
111 Richard olshen 0.50 Stanford University USA
112 Robert Kennard 0.50 University of Delawar USA
113 Robert Kowalski 0.50 Imperial College London UK
114 Sam Roweis 0.50 New York University USA
115 Scott Kirkpatrick 0.50 Hebrew University Israel
116 Sepp Hochreiter 0.50 Johannes Kepler University Linz Austria
117 Sergey Ioffe 0.50 Google USA
118 Shaoqing Ren 0.50 NIO China
119 Simon Osindero 0.50 Google USA
120 Song Han 0.50 MIT USA
121 Soumith Chintala 0.50 Meta USA
122 Tero Karras 0.50 NVIDIA USA
123 Thomas Brox 0.50 University of Freiburg Germany
124 Thomas Cover 0.50 Stanford University USA
125 Thomas Kipf 0.50 Google USA
126 Tianqi Chen 0.50 CMU USA
127 Tie-Yan Liu 0.50 Microsoft Research AI4Science China
128 Timo Aila 0.50 NVIDIA Finland
129 Tin Kam Ho 0.50 IBM USA
130 Tomas Mikolov 0.50 CIIRC CTU The Czech Republic
131 Vincent Vanhoucke 0.50 Google USA
132 Walter Pitts 0.50 MIT USA
133 Warren McCulloch 0.50 MIT USA
134 Wei Liu 0.50 Nuro USA
135 William Dally 0.50 Stanford University USA
136 Xiaowei Xu 0.50 University of Arkansas at Little Rock USA
137 Yishay Mansour 0.50 Tel Aviv University Israel
138 Yoav Freund 0.50 UCSD USA
139 David Silver 0.45 Google UK
140 Ilya Sutskever 0.38 OpenAI USA
141 Bernhard Boser 0.33 UC Berkeley USA
142 Corinna Cortes 0.33 Google USA
143 Daan Wierstra 0.33 Google UK
144 David Rumelhart 0.33 University of California, San Diego USA
145 Donald Loveland 0.33 University of Michigan USA
146 Evan Shelhamer 0.33 Google UK
147 Gao Huang 0.33 Tsinghua University China
148 Hilary Putnam 0.33 Harvard University USA
149 Jia Deng 0.33 Princeton USA
150 Jonathan Hunt 0.33 Twitter UK
151 Jonathan Long 0.33 Stanford Medicine USA
152 Jun-Yan Zhu 0.33 CMU USA
153 Kilian Weinberger 0.33 Cornell University USA
154 Li Fei-Fei 0.33 Stanford University USA
155 Martin Davis 0.33 New York City USA
156 Olga Russakovsky 0.33 Princeton USA
157 Oriol Vinyals 0.33 Google USA
158 Serge Belongie 0.33 University of Copenhagen Denmark
159 Shun-ichi Amari 0.33 University of Tokyo Japan
160 Taesung Park 0.33 Adobe USA
161 Timothy Lillicrap 0.33 Google UK
162 Trevor Darrell 0.33 UC Berkeley USA
163 Xavier Glorot 0.33 Google UK
164 Yee-Whye The 0.33 University of Oxford UK
165 Zhuang Liu 0.33 Meta AI Research USA
166 Andrew Ng 0.25 Stanford University USA
167 Arthur Hoane 0.25 IBM USA
168 Bruce Buchanan 0.25 University of Pittsburgh USA
169 Carl Djerassi 0.25 University of Wisconsin-Madison USA
170 Edward Feigenbaum 0.25 Stanford University USA
171 Feng-hsiung Hsu 0.25 MSRA China
172 Han Hu 0.25 MSRA China
173 Jascha Sohl-Dickstein 0.25 Google USA
174 Jerry Brody 0.25 IBM USA
175 Jianbo Shi 0.25 University of Pennsylvania USA
176 Jonathan Ho 0.25 UC Berkeley USA
177 Joshua Lederberg 0.25 Yale University USA
178 Kyunghyun Cho 0.25 New York University USA
179 Martin Riedmiller 0.25 Google Germany
180 Murray Campbell 0.25 IBM USA
181 Pieter Abbee 0.25 UC Berkeley USA
182 Surya Ganguli 0.25 Stanford University USA
183 Yair Weiss 0.25 Hebrew University Israel
184 Yue Cao 0.25 Lightyear AI China
185 Yutong Lin 0.25 Xi'an Jiaotong University China
186 Ze Liu 0.25 University of Science and Technology of China China
187 Aja Huang 0.20 Google USA
188 Dzmitry Bahdanau 0.20 McGill University Canada
189 Julian Schrittwieser 0.20 Google USA
190 Kelvin Xu 0.20 Google USA
191 Minh-Thang Luong 0.20 Google USA
192 Alexander Kolesnikov 0.17 Google USA
193 Alexey Dosovitskiy 0.17 Google USA
194 Dirk Weissenborn 0.17 Inceptive Inc. USA
195 Lucas Beyer 0.17 Google USA
196 Neil Houlsby 0.17 Google USA
197 Xiaohua Zhai 0.17 Google USA
198 Aidan Gomez 0.14 Cohere Canada
199 Ashish Vaswani 0.14 Adept AI Labs USA
200 Jakob Uszkoreit 0.14 Inceptive Inc. USA
201 Llion Jones 0.14 SakanaAI Japan
202 Lukasz Kaiser 0.14 OpenAI USA
203 Niki Parmar 0.14 Stealth Startup USA
204 Noam Shazeer 0.14 Character.ai USA
205 Benjamin Mann 0.13 Anthropic USA
206 Dario Amodei 0.13 Anthropic USA
207 Jeffrey Wu 0.13 OpenAI USA
208 Melanie Subbiah 0.13 Columbia University USA
209 Nick Ryder 0.13 OpenAI USA
210 Tom Brown 0.13 Anthropic USA


Top AI Institutions

Ranking Institution Grade Country
1 Google 13.50 USA
2 UC Berkeley 7.33 USA
3 MIT 7.20 USA
4 Stanford University 6.78 USA
5 University of Toronto 6.25 Canada
6 Bell Lab 6.00 USA
7 University of Montreal 4.00 Canada
8 Microsoft 3.89 USA
9 Facebook 3.31 USA
10 IBM 3.00 USA
11 CMU 2.33 USA
12 Argonne National Laboratory 2.00 USA
12 University of Amsterdam 2.00 Netherlands
12 New South Wales Institute of Technology 2.00 Australia
13 Cornell University 1.83 USA
14 Princeton University 1.53 USA
15 University of Edinburgh 1.50 UK
15 AT&T Lab 1.50 USA
15 NHK Broadcasting Science Research Laboratories 1.50 Japan
15 OpenAI 1.50 USA
15 University of Oxford 1.50 UK
15 University of Cambridge 1.50 UK
16 University of Washington 1.33 USA
16 NVIDIA 1.33 USA
17 California Institute of Technology 1.14 USA
18 Manchester University 1.00 UK
18 Institute of Control Sciences Moscow 1.00 Russia
18 National Research Development Corporation 1.00 UK
18 University of Alberta 1.00 Canada
18 MCC 1.00 USA
18 University of Munic 1.00 Germany
18 University of Delawar 1.00 USA
18 University of British Columbia 1.00 UK
18 INRIA 1.00 France
18 ETH Zurich 1.00 Switzerland
18 Max Planck Institute for Biological Cybernetics 1.00 Germany
18 University of Illinois Chicago 1.00 USA
18 Helsinki University of Technolog 1.00 Finland
18 University of Freiburg 1.00 Germany
18 GTE Laboratories Incorporated 1.00 USA
18 University of Massachusetts Amherst 1.00 USA
18 Northeastern Universit 1.00 USA
18 UC Los Angeles 1.00 USA
18 University of Michigan Ann Arbor 1.00 USA
19 Tsinghua University 0.92 China
20 University of Pennsylvania 0.83 USA
21 Stanford Research Institute 0.50 USA
21 University College London 0.50 UK
21 Tilburg University 0.50 Netherlands
21 National University of Singapore 0.50 Singapore
21 Momenta 0.50 China
21 Technical University of Munich 0.50 Germany
21 IDSIA 0.50 Switzerland
21 Jacobs University 0.50 Germany
21 Yahoo 0.50 USA
21 indico Research 0.50 USA
21 Courant Institute of Mathematical Sciences 0.50 USA
21 Montreal Institute for Learning Algorithms 0.50 Canada
21 King's College 0.50 UK
21 Peking University 0.50 China
22 UNC Chapel Hill 0.45 USA
22 University of Michigan 0.45 USA
23 Rensselaer Polytechnic Institute 0.33 USA
23 New York University 0.33 USA
23 Hebrew University 0.33 Israel
23 Kyushu University 0.33 Japan
23 UC San Diego 0.33 USA
23 Allen Institute for AI 0.33 USA
23 University of Sienna 0.33 Italy
23 Hong Kong Baptist University 0.33 China
23 University of Wollongong 0.33 Australia
24 Zoox  0.25 USA
24 University of Maine 0.25 USA
24 University of Science and Technology of China 0.25 China
24 Xian Jiaotong University 0.25 China
25 Cornell NYC Tech 0.14 USA
25 Toyota Technological Institute 0.14 Japan
25 Brown University 0.14 USA
25 UC Irvine 0.14 USA


Top AI Countries

ID Country Grade
1 USA 73.1
2 Canada 12.6
3 UK 11.5
4 China 4.8
5 Germany 4.1
6 Netherlands 2.5
7 Australia 2.3
8 Japan 2.0
9 Switzerland 1.5
10 France 1.3
11 Russia 1.0
12 Finland 1.0
13 Israel 0.5
14 Singapore 0.5
15 Italy 0.3