/* ---- Google Analytics Code Below */

Thursday, January 31, 2019

InfoQ interviews Google on Quantum Neural Nets

Further examination of this, based on two papers in Google Research, provides a less technical and critical view.

Exploring Quantum Neural Nets   by  Sergio De Simone in InfoQ

An important area of research in quantum computing concerns the application of quantum computers to training of quantum neural networks. The Google AI Quantum team recently published two papers that contribute to the exploration of the relationship between quantum computers and machine learning. 

In the first of the two papers, "Classification with Quantum Neural Networks on Near Term Processors", Google researchers propose a model of neural networks that fits the limitation of current quantum processors, specifically the high levels of quantum noise and the key role of error correction.

The second paper, "Barren Plateaus in Quantum Neural Network Training Landscapes", explores some peculiarities of quantum geometry that seem to prevent a major issue with classical neural networks, known as the problem of vanishing or exploding gradients.

InfoQ took the chance to speak with Google senior research scientist Jarrod McClean to better understand the importance of these results and help frame them in a larger context.  ... "

No comments: