MetaMind delivers Artificial Intelligence enterprise solutions via its AI platform and Smart Module offerings. The general-purpose platform can predict outcomes for language, vision and database tasks, and delivers best in class accuracies on standard benchmarks. As well as this, MetaMind's 'General Object Classification' module can be calibrated to identify objects with human-like accuracy. There's a module that's specifically built to recognize food, which has huge implications in app development and the food industry. With the vision module's ability to identify the positions of objects and classify each pixel in an image, the technology is also poised to have a huge impact in the medical industry.

Richard Socher, co-Founder and CTO at MetaMind, is interested in developing new deep learning models that learn useful features, capture compositional structure in multiple modalities and perform well across different tasks. We caught up with him for a quick chat, ahead of his talk at the Deep Learning Summit later this month.

What are the key factors that have enabled recent advancements in deep learning?

More data, more compute power and a better understanding of a lot of aspects of neural networks.

What advancements excite you most in the field?

I am excited about seeing the recent influx of deep learning groups who have now also started working in natural language processing.

When I started in 2010 there was still a lot of skepticism about applying neural networks to language problems.
People were not convinced that a variable length structure like a sentence could or should be squeezed into a single fixed size structure like a distributed vector.

We've come a long way in the last 4 years and this and several related assumptions are not questioned anymore by a large part of the community.

What are the practical applications of your work and what sectors are most likely to be affected?

There are too many to be listed here but here are a few interesting ones:

- medical applications in radiology

- sentiment analysis and all of its applications in marketing, finance and customer satisfaction

- food classification for keeping track of your calories

- question answering for really being able to sift through the ever increasing amount of information

The Deep Learning Summit is taking place in San Francisco on 29-30 January. You can get more information and register here.