
Sign up to save your podcasts
Or


Learning to read, think and communicate effectively is part of the curriculum for every young student. But Dr. Adam Trischler, Research Manager and leader of the Machine Comprehension team at Microsoft Research Montreal, would like to make it part of the curriculum for your computer as well. And he’s working on that, using methods from machine learning, deep neural networks, and other branches of AI to close the communication gap between humans and computers.
Today, Dr. Trischler talks about his dream of making literate machines, his efforts to design meta-learning algorithms that can actually learn to learn, the importance of what he calls “few-shot learning” in that meta-learning process, and how, through a process of one-to-many mapping in machine learning, our computers not may not only be answering our questions, but asking them as well.
By Researchers across the Microsoft research community4.8
8080 ratings
Learning to read, think and communicate effectively is part of the curriculum for every young student. But Dr. Adam Trischler, Research Manager and leader of the Machine Comprehension team at Microsoft Research Montreal, would like to make it part of the curriculum for your computer as well. And he’s working on that, using methods from machine learning, deep neural networks, and other branches of AI to close the communication gap between humans and computers.
Today, Dr. Trischler talks about his dream of making literate machines, his efforts to design meta-learning algorithms that can actually learn to learn, the importance of what he calls “few-shot learning” in that meta-learning process, and how, through a process of one-to-many mapping in machine learning, our computers not may not only be answering our questions, but asking them as well.

341 Listeners

155 Listeners

213 Listeners

306 Listeners

90 Listeners

505 Listeners

478 Listeners

56 Listeners

133 Listeners

95 Listeners

124 Listeners

589 Listeners

26 Listeners

35 Listeners

136 Listeners