Articles

TensorFlow.js is a JavaScript library for training and deploying Machine Learning (ML) models in the browser (client-side) and on Node.js (server-side). In this article, I want to describe my experience in building an App (that I recently published on Google Play Store) with this javascript ML library.

However, instead of just going straight into how I built this app using TensorFlow.js, I want to first describe the conditions/needs that led to this choice. I also want to touch a little bit on some other approaches that I realized could be possible that you can take to build an App leveraging machine learning. Finally, I want to leave behind some lessons I learned through this experience and would love your thoughts if you have been experimenting with ML in Apps.


Source de l’article sur DZONE (AI)

As AI has taken on ever greater importance in the priority of organizations around the world, it is understandable that efforts are underway to protect the intellectual property of algorithms that have strategic importance.

A recent paper from IBM Research highlights one strategy being worked on to provide this protection. Their approach takes inspiration from the digital watermarking that helps to protect video, audio and photos.


Source de l’article sur DZONE (AI)