by Admin | Nov 20, 2020 | Chronicles, News
This week in The History of AI at AIWS.net – Rodney Brooks published “Elephants Don’t Play Chess” in 1990. The paper proposed a “group-up approach” to developing AI, in contrast with Classical AI. Brooks dubbed this approach “Nouvell AI”. The paper can be read and downloaded here.
In the abstract, Brooks wrote – “We explore a research methodology which emphasizes ongoing physical interaction with the environment as the primary source of constraint on the design of intelligent systems. We show how this methodology has recently had significant successes on a par with the most successful classical efforts.”
Rodney Brooks is an Australian roboticist. He was a Panasonic Professor of Robotics at the Massachusetts Institute of Technology, as well as the former director of the MIT Computer Science and Artificial Intelligence Laboratory. Brooks also advocated for an actionist approach in terms of robotics. He also linked robotics to Artificial Intelligence.
The History of AI initiative sees this paper as important because it shows an alternate vision for AI and its development. Although it diverges from other methods of AI, it was still pioneering AI in a different way. Thus, HAI considers the paper as a relevant marker in the History of AI.
by Admin | Nov 13, 2020 | Chronicles, News
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.
by Admin | Nov 8, 2020 | News
Dr Lorraine Kisselburgh is the inaugural Chair of ACM’s global Technology Policy Council, where she oversees technology policy engagement in the US, Europe, and other global regions. Drawing on 100,000 computer scientists and professional members, ACM’s public policy activities provide nonpartisan technical expertise to policy leaders, stakeholders, and the general public about technology policy issues, including the 2017 Statement on Algorithmic Transparency and Accountability and the 2020 Principles for Facial Recognition Technologies.
The History of AI Board warmly welcomes Dr. Lorraine Kisseburgh.
by Admin | Nov 6, 2020 | Chronicles, News
This week in The History of AI at AIWS.net – the ACM named Yoshua Bengio, Geofrrey 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.
by Admin | Oct 30, 2020 | Chronicles, News
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.
