[-AI-3.5]Top 10 important persons in the history of machine learning

Abstract

機械学習は、コンピューターが自己学習する能力を持つ技術です。人工知能の分野で発展しています。機械学習は、数学、統計学、コンピュータ科学などのさまざまな分野の技術を組み合わせることで、コンピューターが大量のデータを処理し、シミュレーションに基づいた予測を行うことができます。この記事では、機械学習技術の歴史で最も重要な10人の人物を紹介し、機械学習技術の発展と将来の進展について学ぶことができます。アーサー・サミュエル、アラン・チューリング、ジョン・マッカーシー、ジェフリー・ヒントン、ヨシュア・ベンジオ、フランソワ・ショレ、イアン・グッドフェロー、リチャード・サットンが紹介されています。彼らの功績により、機械学習は現代の人工知能の発展に大きな影響を与えたといえます。

Table of contents

• Introduction
• Arthur Samuel
• Alan Turing
• John McCarthy
• Geoffrey Hinton
• Yoshua Bengio
• François Chollet
• Ian Goodfellow
• Richard Sutton
• Conclusion

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Introduction

Machine learning is a technology that gives computers the ability to learn autonomously. It has developed in the field of artificial intelligence. Machine learning combines various technologies from fields such as mathematics, statistics, and computer science. With machine learning, computers can process vast amounts of data and make simulated predictions. This article introduces the ten most important figures in the history of machine learning, allowing you to learn how machine learning technology has developed and how it will continue to evolve in the future.

Arthur Samuel

Arthur Samuel was one of the pioneers who began research on machine learning in the 1950s, and his contributions are immeasurable. He adopted machine learning in various fields and developed numerous applications that yielded results. For example, in 1959, he developed an automatic checker program that could beat humans. He also developed an early version of a pattern recognition algorithm that allowed programs to learn as human opponents in games.

His accomplishments are noteworthy in the history of machine learning, and many researchers are further evolving their research based on his work. Additionally, his research achievements are being utilised in various areas such as natural language processing, pattern recognition, image recognition, and speech recognition.

Alan Turing

Alan Turing is one of the most famous figures in the history of machine learning. He invented the Turing machine and revolutionized the field of computer science. His achievements helped the Allied Forces win World War II by developing a method to decipher Nazi Germany’s encryption. He also made significant contributions to the field of artificial intelligence. His proposed Turing Test has become a world- renowned criterion for judging whether a machine can think like a human. Alan Turing has made a great contribution to the field of machine learning and has had a significant impact on today’s digital revolution.

John McCarthy

John McCarthy is known as the father of machine learning. In the Dartmouth Conference he organized in 1956, the concept of artificial intelligence was first proposed. He developed the Lisp programming language for robots and led the development of Logic Theorist, the first program in the field of artificial intelligence. He had a genius and creative idea to make artificial intelligence practical. He contributed to the subsequent development by establishing the research fields of machine learning and artificial intelligence. Thanks to his contribution, machine learning has evolved as it is today.

Jeffrey Hinton

Geoffrey Hinton is one of the most important figures in modern machine learning. He has provided innovative solutions to many problems in the field of machine learning. He has developed powerful algorithms based on applied mathematics and made significant contributions to the development of artificial neural networks. He is also well-known for creating a new paradigm for deep learning. And he launched the project Google Brain, expanding the breadth of research. Hinton’s contributions have had a significant impact on the development of machine learning and are among the most important contributions to modern artificial intelligence.

Joshua Bengio

Yoshua Bengio is an important figure in modern machine learning and one of the pioneers of deep learning. He is known for his research on long and short-term learning in neural networks, which has had a significant impact on modern deep learning. He also developed TensorFlow. Some of his contributions to research include deep generative models, neural machine translation, and image recognition using deep learning. He will continue to have a profound impact on the evolution of machine learning.

François Chouleur

François Chollet is one of the important figures in modern machine learning. Through numerous research and presentations that contributed to the development of machine learning, he is highly valued. In particular, as the Chief Scientist of Google Brain and a member of the TensorFlow development team, he played an important role in designing a deep learning framework. He also contributed to the research on artificial intelligence and natural language processing, including GPT-2. Chollet has had a significant impact on the field of machine learning, and is expected to contribute even more to its further development in the future.

Ian Goodfellow

Ian Goodfellow is famous for his development of GAN in deep learning. GAN is a network that uses two models (a generative model and a discriminative model) to generate data, which can make photos, sounds, and other data more real. He is also well-known for his research in convolutional neural networks and has played an important role in the field of image and speech recognition. Goodfellow’s research has enabled us to deal with non-existent data and create more advanced image and speech generation techniques. Currently, Goodfellow has stepped down from his research and is working as a Venture Capitalist supporting startups based on machine learning technology.

Richard Sutton

Richard Sutton, an authority on reinforcement learning, is one of the leading pioneers in the field of computer science. His research, which elucidated the fundamental elements of reinforcement learning, has had a significant impact on the machine learning community and has impressed many researchers. Among his accomplishments is Reinforcement Learning: An Introduction. His research activities at Carnegie Mellon University and the University of Alberta, where he taught, have also been recognised as contributing to the advancement of reinforcement learning. His specialised knowledge of reinforcement learning remains essential, and will continue to have a significant impact on technological progress in the future.