What’s Next for Deep Learning?
According to AI/DL pioneer's what will be next in the Deep Learning,
Ilya Sutskever, Research Director of OpenAI:
- Deeper models, models that need fewer examples for training.
Christian Szegedy, Senior Research Scientist at Google:
- Become so efficient that they will be able to run on cheap mobile devices.
Pieter Abbeel, Associate Professor in Computer Science at UC Berkeley:
- Significant advances in deep unsupervised learning and deep reinforcement learning. CS 294: Deep Reinforcement Learning, Spring 2017 Course from Pieter.
Ian Goodfellow, Research Scientist at OpenAI:
- Neural networks that can summarize what happens in a video clip, and will be able to generate short videos. Neural networks that model the behavior of genes, drugs, and proteins and then used to design new medicines.
Koray Kavukcuoglu & Alex Graves, Research Scientists at Google DeepMind:
- An increase in multimodal learning and a stronger focus on learning that persists beyond individual datasets.
Charlie Tang, Deep learning startup & Machine Learning group, University of Toronto:
Deep learning algorithms ported to commercial products, much like how the face detector was incorporated into consumer cameras in the past ten years.
Reference: MIT Open course