Top 10 Pioneers of the AI Revolution

We kick off our list with Kate Crawford,  a renowned scholar and researcher whose research into AI development has played a significant role in the advancement of AI systems. Crawford has been instrumental in bringing attention to the ethical and social implications of AI and advocating for greater transparency, accountability, and fairness in the development and deployment of AI systems. One of her most notable contributions has been her work on the social implications of data, particularly with respect to issues of bias, discrimination, and privacy. In her research, Crawford has highlighted the ways in which AI systems can perpetuate and amplify existing social inequalities and the need for greater attention to be paid to the social and ethical implications of AI. Her work has helped to raise awareness of the need for more inclusive and equitable AI systems.

Crawford has also been a strong advocate for greater transparency and accountability in the development and deployment of AI. In her research, she has emphasized the need for greater transparency in the data and algorithms used to train AI systems, as well as the need for accountability mechanisms to ensure that AI systems are used in a fair and just manner. Her work has helped to shape debates about the regulation and governance of AI systems and has influenced the development of ethical guidelines and standards for AI. In addition to her research, Crawford has also been involved in policy and advocacy work related to AI. She has advised governments, non-governmental organizations, and companies on issues related to AI ethics, and has been a vocal advocate for the need to ensure that AI benefits all members of society, not just a privileged few. Her advocacy work has helped to shape public discourse about the social and ethical implications of AI and has contributed to the development of more responsible and equitable approaches to AI development and deployment.

Our next pioneer is Dr Fei-Fei Li, who has made critical contributions to the development of machine learning, computer vision, and natural language processing. Her research and advocacy work has been instrumental in advancing AI and in making its development more accessible and inclusive. One of Dr Li's most notable contributions to AI is her work on computer vision, which has been critical to the development of autonomous vehicles, facial recognition systems, and other applications that rely on image and video analysis. Her research has focused on developing algorithms that can identify objects and scenes in images and videos with a high degree of accuracy, even in complex and dynamic environments. Her work has been foundational to the development of modern computer vision and has had a significant impact on the field of AI.

Dr Li has also been a strong advocate for the democratization of AI, and for making the benefits of AI accessible to everyone. In 2017, she co-founded AI4ALL, a nonprofit organization that aims to increase diversity and inclusion in AI education and research. The organization provides education and mentorship opportunities to underrepresented groups, including women, people of colour, and people from low-income backgrounds. Through AI4ALL, Dr Li has worked to create a more diverse and inclusive AI community and to ensure that AI is developed and used in a responsible and ethical manner. She has served as a member of the National Security Commission on AI, advising the US government on issues related to AI and national security, and has also worked with industry leaders to develop ethical and responsible AI practices. Her work has helped to shape public policy and industry practices related to AI and has contributed to the development of more responsible and inclusive approaches to AI.

Ian Goodfellow is a leading figure in the field of artificial intelligence (AI), who has played a critical role in advancing the development of deep learning and generative adversarial networks (GANs). His contributions to the field of AI have been transformative, and have had a significant impact on the way that AI systems are developed and deployed. GANs are a type of neural network that can generate new data that is similar to a given set of input data. Goodfellow's development of GANs has been instrumental in enabling AI systems to generate realistic images, videos, and other types of data, with applications ranging from video game development to medical imaging.

Goodfellow has also been a strong advocate for the democratization of AI, and for making the benefits of AI accessible to everyone. He has been a vocal advocate for open-source software and data and has worked to create tools and resources that make it easier for researchers and developers to build and deploy AI systems. His work has helped to create a more open and accessible AI community and has contributed to the development of more innovative and effective AI systems. In addition to his research and advocacy work, Goodfellow has also been involved in policy and industry initiatives related to AI. He has worked with industry leaders to develop ethical and responsible AI practices and has served as an advisor to government agencies on issues related to AI and national security. His work has helped to shape public policy and industry practices related to AI and has contributed to the development of more responsible and ethical approaches to AI development and deployment.

Next up we have Kai-Fu Lee, a prominent figure in the AI industry who has played a critical role in advancing the development and deployment of AI technologies in China and globally. His contributions to the field of AI have been transformative, and have had a significant impact on the way that AI systems are developed, deployed, and used. One of Lee's most significant contributions to advancing AI is his work on speech recognition and natural language processing. He was a key member of the team that developed the first continuous speech recognition system for the Mandarin language, which was a major breakthrough in the field of natural language processing. His work on speech recognition and natural language processing has been critical to the development of intelligent virtual assistants and other AI systems that rely on human-computer interaction.

Lee has also been a strong advocate for the development and deployment of AI technologies in China and globally. He founded Sinovation Ventures, a venture capital firm that invests in AI startups, and has worked to promote the development of AI technologies in China and other countries. He has also been a vocal advocate for the ethical and responsible deployment of AI technologies and has called for greater transparency and oversight in the development and deployment of AI systems. In addition to his research and advocacy work, Lee has also been involved in policy and industry initiatives related to AI. He has served as an advisor to the Chinese government on issues related to AI and has worked with industry leaders to develop ethical and responsible AI practices. His work has helped to shape public policy and industry practices related to AI and has contributed to the development of more responsible and ethical approaches to AI development and deployment.

Next up we have Andrew Ng, Founder & CEO of Landing AI, Co-Founder of Coursera, and an Adjunct Professor at Stanford University’s Computer Science Department. Ng has held key positions in big tech firms including Google and Baidu and was a key member of the team that developed the deep learning algorithm that enabled machines to recognise images and speech with unprecedented accuracy. ​As a leader in machine learning, especially in developing large-scale online learning algorithms, Ng has played a critical role in defining the future of AI. His efforts have opened up numerous possibilities for both research and industry to address challenges that stem from AI.  In 2011, he led the development of Stanford University's main MOOC (Massive Open Online Courses) platform and taught an online Machine Learning course that was offered to over 100,000 students leading to the founding of Coursera where he is currently Chairman and Co-founder.

Ng’s research has been instrumental in the development of intelligent virtual assistants, self-driving cars, and other AI systems that rely on machine learning. In 2013, he was named to the Time 100 list of the most influential persons in the world. Ng has also been a strong advocate for the democratisation of AI, and for making the benefits of AI accessible to everyone. He founded Coursera, an online education platform that provides courses on AI and other technologies to millions of students around the world. He has also worked to create tools and resources that make it easier for researchers and developers to build and deploy AI systems. His work has helped to create a more open and accessible AI community and has contributed to the development of more innovative and effective AI systems. In addition to his research and advocacy work, Ng has also been involved in policy and industry initiatives related to AI. He has worked with industry leaders to develop ethical and responsible AI practices and has served as an advisor to government agencies on issues related to AI and national security. His work has helped to shape public policy and industry practices related to AI and has contributed to the development of more responsible and ethical approaches to AI development and deployment.

Mustafa Suleyman is a British entrepreneur and computer scientist who has played a critical role in the development of artificial intelligence (AI) and its impact on society. He is best known as the co-founder of DeepMind, an AI research lab that has developed groundbreaking AI systems and algorithms. Suleyman co-founded DeepMind in 2010 along with Demis Hassabis and Shane Legg. The company quickly gained recognition for its innovative work in the field of deep learning, particularly in the areas of image and speech recognition. In 2015, DeepMind's AlphaGo program defeated the world champion at the ancient board game Go, marking a significant milestone in the development of AI.

Suleyman has been a strong advocate for the responsible development and deployment of AI. He has been vocal about the need for transparency and ethical considerations in AI development and has worked to develop guidelines and frameworks for responsible AI use. He has also called for increased diversity and inclusion in the tech industry, particularly in the development of AI systems. In addition to his work at DeepMind, Suleyman has been involved in various initiatives related to the use of AI for social good. He has worked with organizations such as the UN and the Red Cross to develop AI systems that can be used to address humanitarian issues, such as disaster response and healthcare access. In 2017, he was named one of the 100 most influential people in the world by Time magazine. He has also been recognized for his work on AI ethics and governance and has been appointed to various advisory roles related to AI policy.

The first of the three “AI godfathers” on this list, Yoshua Bengio is a Canadian AI researcher who has played a critical role in the development of deep learning and its impact on advancing AI. He is known for his pioneering work in the area of neural networks, which has revolutionised the way that computers process and learn from data. Bengio's research has focused on developing algorithms that can learn to recognise patterns and relationships in large data sets. He has made significant contributions to the development of deep learning techniques, such as convolutional neural networks and recurrent neural networks, which are now widely used in image recognition, natural language processing, and other AI applications.

Bengio has also been a strong advocate for the ethical and responsible use of AI. He has been vocal about the need for transparency and accountability in AI development and has called for increased focus on developing AI systems that are aligned with human values and priorities. In addition to his research, Bengio has been involved in numerous initiatives related to the use of AI for social good. He has worked with organizations such as the International Committee of the Red Cross and the United Nations to develop AI systems that can be used to address humanitarian issues, such as disaster response and healthcare access. Bengio's contributions to the field of AI have been widely recognized. He has received numerous awards and accolades, including the Turing Award, which is considered the most prestigious award in computer science. He has also been named one of the most influential people in the field of AI by various organisations and publications.

Our number 3 spot goes to Sam Altman, the co-founder of the buzzy AI research and deployment group OpenAI. Propelled into a beacon of the AI revolution since the release of ChatGPT last November, Altman’s contribution to the development of generative AI has proved instrumental in shaping the next phase of AI innovation. The generative AI chatbot has set off a big tech frenzy, leading major big tech players including Google and Meta move huge amounts of resources into the development and advancement of AI. It has also led huge tech companies, such as Microsoft and Tesla to invest heavily in OpenAI’s research and development of AI, accelerating the advancement and global adoption of AI technologies. 

But Altman’s role in pushing the AI revolution expands far beyond the creation of ChatGPT. As the former president of Y Combinator, a startup accelerator that has helped launch companies such as Airbnb, Dropbox, and Reddit, Altman has been at the forefront of many groundbreaking AI projects and has been an influential figure in the technology industry for over a decade. Altman has been a key investor in several AI startups, including DeepMind, which was acquired by Google in 2015 for a reported $500 million. He has also been an active supporter of AI education and outreach, having taught a course on startup strategies at Stanford University and spoken at numerous conferences and events around the world. Altman has also been an advocate for ethical AI development and has been vocal about the potential risks associated with AI. In a 2018 interview with MIT Technology Review, Altman spoke about the importance of creating AI systems that are transparent, explainable, and accountable. He has also been a proponent of using AI to solve some of the world's most pressing problems, such as climate change and healthcare.

Our second-place spot goes to Yann LeCun, another “AI godfather” known for his significant contributions to the development of deep learning, a subfield of machine learning that uses neural networks to analyse and process complex data. His work has been instrumental in advancing the AI revolution, making it possible for machines to learn and process information in ways that were previously thought impossible. One of LeCun's most notable contributions to AI is the development of convolutional neural networks (CNNs), which are used extensively in image and speech recognition. In the 1990s, LeCun pioneered the use of CNNs for image recognition, leading to breakthroughs in the field and making it possible for computers to recognize and classify images with a high degree of accuracy. This work was foundational to the development of modern computer vision and has been applied in a wide range of applications, from self-driving cars to medical imaging.

Beyond his research contributions, LeCun has also played an important role in advancing the field of AI through education and mentorship. He has trained numerous researchers and students in the field of deep learning and has been an advocate for making AI more accessible to a wider range of people. In 2013, LeCun founded the Facebook AI Research (FAIR) group, which has since become one of the leading research organizations in the field. Under his leadership, FAIR has made significant contributions to the development of AI, including advances in computer vision, natural language processing, and robotics. In recognition of his contributions to the field of AI, LeCun has received numerous awards and honours. Along with Geoffrey Hinton and Yoshua Bengio, Le Cun was awarded the Turing Award in 2018. He has also been elected to the National Academy of Engineering, the National Academy of Sciences, and the American Academy of Arts and Sciences.

Our number one spot goes to Geoffrey Hinton, a British-Canadian computer scientist and AI researcher widely considered to be the most influential figure in the history of the AI industry. Known as one of the three “godfathers of AI”, Hinton’s pioneering work on deep learning and his development of neural networks has revolutionised the way that computers process and learn from data. He co-authored a landmark paper with David Rumelhart and Ronald Williams on the concept of backpropagation – a way of training artificial neural networks hailed as "the missing mathematical piece" needed to supercharge machine learning. This concept has played a key role in developing algorithms that can learn to recognise patterns and relationships in large data sets and made critical contributions to the development of deep learning techniques, such as convolutional neural networks and deep belief networks, which are now widely used in image recognition, natural language processing, and other AI applications.

Hinton has also been a strong advocate for the ethical and responsible use of AI. He has been vocal about the need for transparency and accountability in AI development and has called for increased focus on developing AI systems that are aligned with human values and priorities. He recently resigned from his senior position at Google to warn the world about the dangers of AI and has been vocal about protecting the world from the risks of the technology. Hinton has also been involved in numerous initiatives related to the use of AI for social good. He has worked with organisations such as the International Committee of the Red Cross and the United Nations to develop AI systems that can be used to address humanitarian issues, such as disaster response and healthcare access. In recognition of his massive contributions to the AI industry, Hinton has received numerous awards and accolades, including the Turing Award, in 2018, which is considered the "Nobel Prize of Computing."