Top 10 Leaders in Machine Learning
As we all know, Machine Learning (ML) is a rapidly evolving field that has the potential to revolutionise the way we live and work - and the paradigm shift is already underway.
A subfield of AI, ML is what endows computers with the ability to learn, without explicitly being programmed for a particular task.
It is used to perform complex tasks in a way that is similar to how humans solve problems.
Machine learning fuels all sorts of automated tasks that span across multiple industries, from data security firms that hunt down malware to finance professionals who want alerts for favourable trades.
The AI algorithms are programmed to constantly learn in a way that simulates a virtual personal assistant.
The way machines can learn new tricks gets really interesting (and exciting) when we start talking about deep learning and deep neural networks.
While traditional machine learning algorithms are linear, deep learning algorithms are stacked in a hierarchy of increasing complexity and abstraction. At its simplest, deep learning can be thought of as a way to automate predictive analytics.
A type of advanced machine learning algorithm, known as an artificial neural network, underpins most deep learning models. As a result, deep learning may sometimes be referred to as deep neural learning or deep neural networking.
To stay current with these latest developments, it's important to follow thought leaders, influencers and innovators in the industry.
Here are our Top 10 Leaders in Machine Learning:
10. Andrew Ng
Andrew Ng is a computer scientist and entrepreneur who is a globally recognised leader in AI.
He is the founder of DeepLearning.AI, founder and CEO of Landing AI, general partner at AI Fund, chairman and co-founder of Coursera.
Ng has made significant contributions to the development of deep learning and has worked on a number of high-profile projects, including the Stanford Artificial Intelligence Robot project and the Google Brain project.
He is also the author of several books on machine learning and artificial intelligence.
Ng is a pioneer in online education as a co-founder of deeplearning.ai and Coursera – the world’s largest MOOC platform, which started off with more than 100,000 students enrolling for his popular course CS229A.
Dr Ng has touched countless lives through his work as a computer scientist which led to him being named as one of Time magazine’s 100 most influential people in 2012.
9. Yann LeCun
Yann LeCun is a computer scientist and professor at New York University.
He is one of the pioneers of the field of deep learning and has made significant contributions to the development of convolutional neural networks (CNNs) for image recognition.
LeCun is also the co-recipient of the 2018 ACM A.M. Turing Award for his work on deep learning.
He is also the director of AI Research at Facebook, where he leads the development of deep learning algorithms for a variety of applications.
8. Geoffrey Hinton
Geoffrey Hinton is a computer scientist and professor at the University of Toronto.
He is one of the pioneers of the field of deep learning and has made significant contributions to the development of convolutional neural networks (CNNs) for image recognition.
Hinton is also the co-recipient of the 2018 ACM A.M. Turing Award for his work on deep learning.
Hinton is also a fellow of the Royal Society, a member of the Order of Canada, and a fellow of the Association for Computing Machinery.
7. Fei-Fei Li
Fei-Fei Li is a computer scientist and professor at Stanford University.
She is one of the pioneers of the field of computer vision and has made significant contributions to the development of deep learning algorithms for image recognition.
Li is also the co-founder of AI4ALL, a nonprofit organisation that aims to increase diversity and inclusion in the field of artificial intelligence.
Li is also a fellow of the Association for Computing Machinery and a member of the National Academy of Engineering.
6. Demis Hassabis
Demis Hassabis is a computer scientist and entrepreneur who is the co-founder and CEO of DeepMind, a leading artificial intelligence research company.
Hassabis has made significant contributions to the development of deep reinforcement learning algorithms and has worked on a number of high-profile projects, including the development of AlphaGo, an AI program that defeated the world champion at the game of Go.
Hassabis is also a fellow of the Royal Society and a fellow of the Association for Computing Machinery.
5. Ian Goodfellow
Ian Goodfellow is a computer scientist and researcher who is one of the pioneers of the field of generative adversarial networks (GANs), a type of deep learning algorithm that can generate realistic images and videos.
Goodfellow was also director, and research scientist at Apple, where he worked on developing machine learning algorithms for a variety of applications.
Goodfellow is best known for inventing generative adversarial networks (GAN), using deep learning to generate images. This approach uses two neural networks to generate new data that is similar to the training data.
Goodfellow's work on GANs has been widely recognised and has led to significant advances in the field of machine learning.
He has also made several important contributions to the field of deep learning, including the invention of the adversarial example, which is a type of input to a machine learning model that is intentionally designed to cause the model to make a mistake.
4. Kai-Fu Lee
Kai-Fu Lee is a computer scientist and entrepreneur who is the founder of Sinovation Ventures, a leading venture capital firm that invests in artificial intelligence and robotics startups.
Lee has also held senior positions at Google, Microsoft, and Apple, and has made significant contributions to the development of speech recognition and natural language processing algorithms.
Lee is a pioneer in the field of artificial intelligence and has been recognised for his contributions to the field. He has been named one of the 100 most influential people in the world by Time magazine and has received numerous awards for his work in AI.
3. Andrej Karpathy
Andrej Karpathy is a computer scientist and former director of AI at Tesla and is recognised for his work as a research scientist at OpenAI.
He is one of the pioneers of the field of deep learning and has made significant contributions to the development of convolutional neural networks (CNNs) for image recognition.
Karpathy is also the co-author of several influential papers on machine learning and artificial intelligence.
He has been recognised for his contributions to the field of machine learning and has received numerous awards for his work, including the MIT Technology Review's 35 Innovators Under 35 award.
2. Lex Fridman
Lex Fridman is a research scientist at MIT who has made significant contributions to the development of autonomous vehicles and robotics.
Fridman is also the host of the popular AI podcast that bears his name, where he interviews leading experts in the field of artificial intelligence and machine learning.
Fridman's work on autonomous vehicles has been widely recognised and has led to significant advances in the field.
He has also made several important contributions to the field of machine learning, including the development of a deep learning algorithm that can predict the behaviour of other drivers on the road.
1. Kate Crawford
Kate Crawford is a researcher and professor at USC who has made significant contributions to the study of the social and ethical implications of artificial intelligence and machine learning.
Crawford is also the co-founder of the AI Now Institute, a research institute that focuses on the social and ethical implications of AI.
Crawford is a pioneer in the field of AI ethics and has been widely recognised for her contributions to the field.
She has been named one of the 100 most influential people in the world by Time magazine and has received numerous awards for her work in AI ethics.
Crawford's work has helped to raise awareness of the social and ethical implications of AI and has led to significant advances in the field.
