convolutional neural networks
Better, More Efficient Neural Inferencing Means Embracing Change
Artificial intelligence is running into some age-old engineering tradeoffs. For example, increasing the accuracy of neural networks typically means increasing the size of the networks. That requires more compute ...Full Article
Honey I Shrunk the Model: Why Big Machine Learning Models Must Go Small
Bigger is not always better for machine learning. Yet, deep learning models and the datasets on which they’re trained keep expanding, as researchers race to outdo one another while ...Full Article
Federated Learning Applied to Cancer Research
The ability to share and analyze data while protecting patient privacy is giving medical researchers a new tool in their efforts to use what one vendor calls “federated learning” ...Full Article
MIPS-Based Platform Targets AI App Developers
High-end computing platforms are emerging to support AI applications like inferencing and training so-called edge applications ranging from IoT networks to autonomous vehicles. The latest entry comes from Wave ...Full Article
