This week in The History of AI at AIWS.net – Yoshua Bengio, Geofrrey Hinton, and Yann LeCun receive the Turing Award 2018

This week in The History of AI at AIWS.net – Yoshua Bengio, Geofrrey Hinton, and Yann LeCun receive the Turing Award 2018

This week in The History of AI at AIWS.net – the ACM named Yoshua Bengio, Geoffrey Hinton, and Yann LeCun recipients of the Turing Award in 2018 for breakthroughs that made deep neural networks critical in computing. The Turing Award is one of the most prestigious awards in the field, as it is often considered the Nobel Prize of Computer Science. Other winners include Marvin Minsky and Judea Pearl, both of whom made enormous contributions to Artificial Intelligence.

Yoshua Bengio is a Canadian computer scientist, most notable for his works on neural networks and deep learning. He is an influential scholar, being one of the most cited computer scientists. In the 1990s and 2000s, he helped make deep advancements in the field of deep learning. Bengio is also a Fellow of the Royal Society.

Yann LeCun is a French computer scientist, renowned for his work on deep learning and artificial intelligence. He is also notable for contributions to robotics and computational neuroscience. He is the Silver Professor of the Courant Institute of Mathematical Sciences at NYU. In addition, LeCun is the Chief AI Scientist for Facebook.

Geoffrey Hinton is an English-Canadian cognitive psychologist and computer scientist. He is most notable for his work on neural networks. He co-authored the seminal paper on backpropagation, “Learning representations by back-propagating errors”, in 1986. He is also known for his work into Deep Learning. Hinton, along with Yoshua Bengio and Yann LeCun (who was a postdoctorate student of Hinton), are considered the “Fathers of Deep Learning”.

The History of AI Initiative considers this award and the recipients important because they play an important role in Deep Learning, which is a field of Machine Learning, part of Artificial Intelligence. It is an acknowledgement of how far AI has developed, and thus, is a part of the History of AI.

This week in The History of AI at AIWS.net – Marvin Minsky and Seymour Papert published an expanded edition of Perceptrons

This week in The History of AI at AIWS.net – Marvin Minsky and Seymour Papert published an expanded edition of Perceptrons

This week in The History of AI at AIWS.net – Marvin Minsky and Seymour Papert published an expanded edition of Perceptrons in 1988. The original book was published in 1969. The original book explored the concept of the “perceptron”, but also highlighted its limitations. The revised and expanded edition of the book added a chapter countering criticisms of the book made in the twenty years after its publication. The original Perceptrons were pessimistic in its predictions for AI, and was thought to have been a cause for the first AI winter.

Marvin Minksy was an important pioneer in the field of AI. He penned the research proposal for the Dartmouth Conference, which coined the term “Artificial Intelligence”, and he was a participant in it when it was hosted the next summer. Minsky would also co-founded the MIT AI labs, which went through different names, and the MIT Media Laboratory. In terms of popular culture, he was an adviser to Stanley Kubrick’s acclaimed movie 2001: A Space Odyssey. He won the Turing Award in 1969.

Seymour Papert was a South African-born mathematician and computer scientist. He was mainly associated with MIT for his teaching and research. He was also a pioneer in Artificial Intelligence. Papert was also a co-creator of the Logo programming language, which is used educationally.

The History of AI initiative considers this republication important because it revisited and furthered discourses on AI. The original book was also a cause for the first AI winter, a pivotal event in the history of AI. Furthermore, Marvin Minsky was one of the founders of AI. Thus, HAI sees Perceptrons (republished 1988) as meaningful in the development of Artificial Intelligence.

This week in The History of AI at AIWS.net – the Alvey Programme was launched by the British government

This week in The History of AI at AIWS.net – the Alvey Programme was launched by the British government

This week in The History of AI at AIWS.net – the Alvey Programme was launched by the British government in 1983. It is a project developed in response to Japan’s own Fifth Generation Computer project. There was no specific focus or directive, but rather the program was to support research in knowledge engineering in the UK.

Originally, the UK was invited to Japan’s FGP, and they created a committee chaired by John Alvey, a technology director at British Telecom. In the end, they rejected Japan’s invitation and formed the Alvey Programme. John Alvey was not involved in this initiative itself though.

This project was created in response to Japan’s Fifth Generation Computer program, funded by the Japanese Ministry of Trade and Industry in 1982. The goal of this program was to create computers with massively parallel computing and logic programming and to propel Japan to the top spots in advanced technology. This will then create a platform for future developments in AI. By the time of the program’s end, the opinion of it was mixed, divided between considering it a failure or ahead of its time.

Another program that rivalled the Alvey Programme was America’s Strategic Computing Initiative, founded in 1983 after the first AI winter in the 70s. The initiative supported projects that helped develop machine intelligence, from chip design to AI software. The DoD spent a total of 1 billion USD (not adjusted for inflation) before the program’s shutdown in 1993. Although the initiative failed to reach its overarching goals, specific targets were still met.

Although the results of the Alvey Programme and other computer and AI projects (Fifth Generation and SCI) in the 80s were mixed, they helped bring funding back to AI development after the first AI winter in the 70s. The History of AI marks the Alvey Programme as an important event in AI due to its marker in AI development in the 1980s.

 

This week in The History of AI at AIWS.net – Marvin Minsky and Seymour Papert published Perceptrons

This week in The History of AI at AIWS.net – Marvin Minsky and Seymour Papert published Perceptrons

This week in The History of AI at AIWS.net – Marvin Minsky and Seymour Papert published Perceptrons in 1969. The book explored the concept of the “perceptron”, but also highlighted its limitations. It was also pessimistic in its predictions for AI, and was thought to have been a cause for the first AI winter. There was a revised and expanded edition published in 1988, which added a chapter countering criticisms of the book made in the twenty years after its publication.

Marvin Minksy was an important pioneer in the field of AI. He penned the research proposal for the Dartmouth Conference, which coined the term “Artificial Intelligence”, and he was a participant in it when it was hosted the next summer. Minsky would also co-founded the MIT AI labs, which went through different names, and the MIT Media Laboratory. In terms of popular culture, he was an adviser to Stanley Kubrick’s acclaimed movie 2001: A Space Odyssey. He won the Turing Award in 1969.

Seymour Papert was a South African-born mathematician and computer scientist. He was mainly associated with MIT for his teaching and research. He was also a pioneer in Artificial Intelligence. Papert was also a co-creator of the Logo programming language, which is used educationally.

The History of AI initiative considers this publication important because it furthered discourses on AI, specifically on perceptrons. The book was also a cause for the first AI winter, a pivotal event in the history of AI. Furthermore, Marvin Minsky was one of the founders of AI. Thus, HAI sees Perceptrons as meaningful in the development of Artificial Intelligence.

This week in The History of AI at AIWS.net – Unimate became 1st first labor industrial robot

This week in The History of AI at AIWS.net – Unimate became 1st first labor industrial robot

This week in The History of AI at AIWS.net – Unimate, an industrial robot developed in the 50s, becomes the first to work in New Jersey in 1961.

Unimate was invented by George Davol, who filed the patent in 1954. Davol met Joseph Engelberger in 1956, and the two paired up to found Unimation, the first robot manufacturing company. Davol and Engelberger promoted Unimate at The Tonight Show. Engelberger then exported industrial robotics to outside the US as well.

The Unimate worked at a General Motors assembly line at the Inland Fisher Guide Plant in New Jersey. The robot transported die castings from asssembly lines and welded parts on autos. It did this job because it was considered dangerous for human workers, due workplace hazards such as toxic fumes. The robot had the appearance of a box connected to an arm, with systematic tasks stored in a drum memory.

Although this machine was not directly connected to Artificial Intelligence, it was a precursor to developments in that field. By implementing a robot that can do tasks, this project was taking the first steps towards AI. Thus, the HAI initiatve considers this a milestone in the History of AI.

This week in The History of AI at AIWS.net – “Learning Multiple Layers of Representation” by Geoffrey Hinton was published

This week in The History of AI at AIWS.net – “Learning Multiple Layers of Representation” by Geoffrey Hinton was published

This week in The History of AI at AIWS.net – “Learning Multiple Layers of Representation” by Geoffrey Hinton was published in October 2008. The paper proposed new approaches to deep learning. In place of backpropagation, another concept Hinton introduced prior, Hinton proposes multilayer neural networks. This is so because backpropagation faced limitations such as requiring labeled training data. The paper can be read here.

Deep learning is a part of the broader machine learning field in Artificial Intelligence. The process is a method that is based on artificial neural networks with representation learning. It is “deep” in that it uses multiple layers in the networks. In the modern day, it has been utilised in various fields with good results.

Geoffrey Hinton is an English-Canadian cognitive psychologist and computer scientist. He is most notable for his work on neural networks. He is also known for his work into Deep Learning. Hinton, along with Yoshua Bengio and Yann LeCun (who was a postdoctorate student of Hinton), are considered the “Fathers of Deep Learning.” They were awarded the 2018 ACM Turing Award, considered the Nobel Prize of Computer Science, for their work on deep learning.

This paper is important in the History of AI because it introduces new perspective on deep learning. Instead of another ground-breaking concept like backpropagation, Hinton shows another method in the field. Geoffrey Hinton is also an important role in Deep Learning, which is a field of Machine Learning, part of Artificial Intelligence.