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1.       Amit Singhal: Former Senior Vice President at Google Search, played a crucial role in enhancing Google's search algorithms using AI techniques.

2.       Andrew Ng: Co-founder of Google Brain and Coursera, Ng is a computer scientist and entrepreneur. He has played a key role in popularizing online education in machine learning and AI.

3.       Cade Metz: A journalist covering AI and technology, currently with The New York Times, providing insightful commentary on developments in the field.

4.       Chris Manning: A professor at Stanford University, known for his work in natural language processing and machine learning.

5.       Corinna Cortes: Head of Google Research, NY, and a computer scientist known for her contributions to machine learning, support vector machines, and algorithmic trading.

6.       Cynthia Breazeal: An associate professor at MIT and founder of Jibo, Inc., known for her work in social robotics and human-robot interaction.

7.       Cynthia Rudin: Professor at Duke University, specializing in machine learning, interpretable models, and applications in healthcare.

8.       Danny Lange: Vice President of AI and Machine Learning at Unity Technologies, with extensive experience in AI research and industry applications.

9.       Daphne Koller: A computer scientist and entrepreneur, co-founder of Coursera, and professor at Stanford University with expertise in probabilistic graphical models and machine learning.

10.   Demis Hassabis: Co-founder and CEO of DeepMind, a leading AI research lab acquired by Google. Hassabis has been involved in the development of AI systems that have achieved remarkable success in games like Go.

11.   Drew Houston: Co-founder and CEO of Dropbox, with an interest in the application of AI in cloud services and collaboration tools.

12.   Fei-Fei Li: A professor at Stanford University and a co-director of the Stanford Institute for Human-Centered AI (HAI), specializing in computer vision and AI ethics.

14.   Francisco J. Martin: Founder and CEO of BigML, focusing on machine learning and predictive analytics.

15.   Gary Marcus: A cognitive scientist and entrepreneur, known for his work in artificial intelligence and the co-founder of Robust.AI.

16.   Geoffrey Hinton: A computer scientist and a leading figure in deep learning. Hinton has made significant contributions to neural networks and machine learning.

17.   Hany Farid: A computer scientist and a professor at the University of California, Berkeley. Farid is known for his work in digital forensics, image analysis, and combating digital manipulation.

18.   Hugo Larochelle: Research Scientist at Google Brain and an associate professor at the University of Montreal, known for his work in deep learning and neural networks.

19.   Ian Goodfellow: A computer scientist and an AI researcher at Apple. Goodfellow is known for his work on generative adversarial networks (GANs), a class of machine learning systems.

21.   Ilya Sutskever: Co-founder of OpenAI and Chief Scientist at OpenAI, known for his contributions to deep learning and neural network research.

22.   Jeff Dean: Senior Fellow and Senior Vice President at Google, leading the Google Brain team, and contributing to advancements in deep learning and distributed systems.

23.   Jitendra Malik: A computer vision researcher and professor at UC Berkeley, known for his work in object recognition and scene understanding.

24.   John McCarthy: One of the founders of AI, coined the term "artificial intelligence."

25.   Jürgen Schmidhuber: A computer scientist and AI researcher, co-founder of NNAISENSE, known for his contributions to neural networks and deep learning.

26.   Kate Crawford: A senior principal researcher at Microsoft Research and a leading scholar in the areas of AI ethics, fairness, and the societal impacts of AI.

27.   Kate Darling: A researcher at the MIT Media Lab, known for her work in social robotics and the ethical implications of AI.

28.   Marvin Minsky: Co-founder of the MIT AI Lab and a pioneer in the field of artificial intelligence.

29.   Michael Jordan: A professor at the University of California, Berkeley, with expertise in machine learning, statistics, and artificial intelligence.

30.   Oren Etzioni: CEO of the Allen Institute for Artificial Intelligence (AI2) and a professor at the University of Washington, specializing in machine learning and natural language processing.

31.   Pieter Abbeel: A professor at the University of California, Berkeley, and Co-founder of OpenAI, known for his work in machine learning, robotics, and reinforcement learning.

32.   Raia Hadsell: Research Scientist and Head of the Robotics team at DeepMind, focusing on deep learning and robotics.

33.   Raj Reddy: A computer scientist and a recipient of the Turing Award, known for his contributions to AI, robotics, and computer science education.

34.   Sebastian Thrun: Founder of Google X, Thrun is a computer scientist and entrepreneur. He played a key role in the development of Google's self-driving car and is associated with the field of autonomous systems.

35.   Shafi Goldwasser: A professor at Stanford University and MIT, known for her work in cryptography, computational complexity, and AI.

36.   Stuart Russell: A professor at the University of California, Berkeley, co-author of the influential AI textbook "Artificial Intelligence: A Modern Approach."

37.   Tom Mitchell: Professor at Carnegie Mellon University and a leading researcher in machine learning, with a focus on human-robot interaction.

38.   Yann LeCun: A computer scientist and Chief AI Scientist at Facebook. LeCun is known for his work on convolutional neural networks (CNNs) and his contributions to the development of deep learning.

39.   Yoshua Bengio: A computer scientist and a professor at the University of Montreal. Bengio is recognized for his contributions to deep learning, particularly in the development of recurrent neural networks (RNNs) and long short-term memory networks (LSTMs).

40.   Zoubin Ghahramani: Chief Scientist at Uber and a professor at the University of Cambridge, specializing in probabilistic machine learning.