Bringing Deep Learning to your hardware of choice, one DeciNet at a time
Training deep learning models is costly and hard, but not as much as deploying and running them in production. Deci wants to help address that.
Deep Learning is probably the most popular form of machine learning at this time. Although not every problem boils down to a deep learning model, in domains such as computer vision and natural language processing deep learning is prevalent.
A key issue with deep learning models, however, is that they are resource hungry. They require lots of data and compute to train, and lots of compute to operate. As a rule, GPUs are known to perform better than CPUs for both training and inference, while some models can’t run on CPUs at all. Now Deci wants to change that.
Deci, a company aiming to optimize deep learning models, is releasing a new family of models for image classification. These models outperform well-known alternatives in both accuracy and runtime, and can run on the popular Intel Cascade Lake CPUs.
We caught up with Deci CEO and co-founder Yonatan Geifman to discuss Deci’s approach and today’s release.