Now, researchers at MIT have developed an entirely new way of approaching these complex problems, using simple diagrams as a ... journal Transactions of Machine Learning Research, in a paper ...

Edge computing is booming. The idea of taking compute out of the data center, and bringing it as close as possible to where data is generated, is seeing lots of traction. Estimates for edge ...

Machine learning is compute-intensive and it turns out that traditional compute hardware is not well-suited for the task. In a presentation to the Hadoop Users Group UK in October, Graphcore CTO Simon ...

If you’ve looked into GPU-accelerated machine learning projects ... impressive results it can wring out of even the lowliest hardware. [Thanks to Ishan for the tip.] ...

Hover over this diagram to see how a neural turing machine shifts its attention over its old memory values to create new values. Unfortunately, while there are a plethora of conferences and journals ...

Semiconductor giant AMD acquired Brium, a stealth startup that helps optimize AI software for different hardware ...

Graphics Cards AMD just gave us our first glimpse of FSR 4's 'Redstone' update, with a host of machine learning-based improvements Hardware AMD says 'there is a ton of interest' in FSR 4 and that ...

Machine learning and deep learning tasks demand substantial computing power. Whether you’re training a convolutional neural ...

This means being aware of the data and the machine learning tasks at hand, while also being aware of the hardware the model will be deployed on. The DeciNets announced today are geared for image ...