Such a system can then be applied to new data, effectively automating the task of tagging pictures. Deep learning allows you to automatically turn your data into a system that 'understands' how to map the pictures to the tags, learning only from examples, without requiring any manual tweaking or custom engineering. Consider a large collection of pictures, with some tags associated with each picture ('dog', 'cat', etc). Deep learning is especially good at making sense of 'perceptual' data, like images, videos, or sound.

You can automate a lot of different tasks that way. In most applications, what we call 'Deep learning' can be thought of as a way to turn lots of data, annotated by humans, into a piece of software that can automatically annotate new data in a way that's similar to what humans would do. You are well-known as the author of the Keras package, an open source neural network for deep learning in Python: what is deep learning?ĭeep learning is a specific approach to machine learning, that has turned out to be a lot more powerful and flexible than previous approaches. My main research interest is to understand the problem of abstraction and reasoning in AI - how to go from perception to abstract, highly-generalizable models. Most recently I've worked on papers on machine translation, computer vision, and applying deep learning to theorem proving. On the side, I do research on a range of topics. I also contribute to TensorFlow, Google's machine learning framework, which Keras integrates with. So I believe there's a pretty good alignment between what I do and what people think I do.

I work on the Brain team at Google in Mountain View, where I spend most of my time developing Keras. In my case, I'm probably best known for creating Keras, the deep learning framework. That's a sharp observation, there's usually a discrepancy between what people are known for, what they would like to be known for, and what they're actually working on. But first, what people actually do and popular impressions of what they do infamously diverge. I want to find out more about what you do. Feel free to reach out to us at and you’re a software engineer and artificial intelligence researcher at Google. To coincide with the release of this book, I had the pleasure of interviewing François via e-mail. François Chollet is an AI & deep learning researcher, author of Keras, a leading deep learning framework for Python, and has a new book out, Deep Learning with Python.

Keras francois chollet