When training neural networks to recognise things, what you need is a big pile of training data. You then need a subsequent pile of testing data to verify that the network is working as you’d expect.

An experimental computing system physically modeled after the biological brain "learned" to identify handwritten numbers with an overall accuracy of 93.4%. The key innovation in the experiment was a ...

video: Neuronal silencing periods facilitate an advantageous mechanism for temporal sequence identification and demonstrate a useful new AI mechanism for ATM's equipped with secure handwriting ...

As part of its Build developer conference, Microsoft today announced Project Ink Analysis, a new service under its Cognitive Services brand of AI products that will allow developers to add support for ...